Data + Modelling 2012

2012

Issue 9 Summer

DATA & MODELLING

TOOLS, TECHNIQUES AND APPLICATIONS FOR THOSE INVOLVED IN THE UNDERSTANDING, INTERPRETATION AND PRESENTATION OF ACTIVITY PATTERNS

■ Big data + smart city = new models ■ Using big data to predict the future

■ The intersection of data and human behaviour

■ Online data, networks, simulations and participation

■ New models, new skills

■ The rise of the data scientist

Sponsored by:

In association with:

Image: Eric Fischer

Issue 9 | Summer 2012

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DATA & MODELLING INTRODUCTION

Cover: smart technologies can be used to tell us meaningful stories about human behaviour patterns. Eric Fischer’s geo-tagged images, for example, visualise where photos are taken, and by who. Blue points on the map are photos taken by locals (people who have taken pictures in this city dated over a range of a month or more), red points by tourists (people who seem to be a local of a different city and who took pictures in this city for less than a month); yellow points are pictures where it can’t be determined whether or not the photographer was a tourist. The maps are ordered by the number of pictures taken by locals, in this case, in London, UK

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he future is a foreign country: we will do things very differently there. The challenge for movement and place professionals is to help make viable plans today for an uncertain tomorrow. Movement, living, working and leisure patterns are morphing faster than ever before on the back of rapid technological advances and social change. How can we model today for digitally-savvy generations whose behaviour patterns evolve as rapidly as new technologies?

Yet, innovators in the ever-expanding circle of professionals involved in making better places are rising to these complex challenges. This publication explores a cross-section of the many and varied responses that are emerging from practitioners, consultants and academics across Europe and beyond.

Modelling World 2012 is the must-attend showcase for those interested in these developments.

Outputs from new models and tools that ‘measure’ the complex matrix of accessibility, place quality and urban value are becoming increasingly important to risk-averse politicians, policymakers and investors. Robust evidence is needed to underpin strategies for promoting growth and maximising investment potential. Modelling World will explore the ways in which approaches new and old are being fused together to create innovative models, tools, processes and methodologies – informed, evidence-based, and scientific – but also adaptable, flexible and cost-effective.

Juliana O’Rourke, Editor

CONTENTS

DATA & MODELLING is produced twice yearly and distributed alongside the other companion activities within the Landor Group, including Local Transport Today, New Transit and Parking Review magazines, and the annual Traffic and Transport Software Directory, ITS Review and Placemaking publications. Other parts of our knowledge network include www.TransportXtra.com, www.rudi.net (Resource for Urban Design Information), and the Travel 2020, Modelling World, Open Data and UK and European Rail Stations annual events. The next issue will be published in October 2012.

EDITORIAL OFFICES Apollo House, 359 Kennington Lane London SE11 5QY EDITORS Juliana O’Rourke E: juliana.orourke@landor.co.uk Rik Thomas E: ed.ltt@landor.co.uk EDITORIAL DIRECTOR Peter Stonham E: ed.ltt@landor.co.uk MANAGING DIRECTOR Rod Fletcher E: rod.fletcher@landor.co.uk CLIENT PARTNERSHIPS MANAGER Daniel Simpson E: daniel.simpson@landor.co.uk SUBSCRIPTIONS Michelle Forde E: subs@landor.co.uk PRINTERS Hastings Printing Company Ltd, Drury Lane St Leonards-on-Sea, East Sussex TN38 9BJ

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A new world of data, analysis, communication and modelling?

Possibilities for the analysis of movement, living and activity patterns on a scale as yet unprecedented

Learning from other disciplines How can we keep what is good, borrow where applicable and apply innovation in new environments, asks Tom Van Vuren

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The intelligent and creative use of data Companies such as IBM, EC Harris and Space Syntax are developing new data capture and analysis techniques

CCTV data for behavioural insight; microsimulation modelling Behavioural and identity tracking is adding to the toolkit for data capture and analysis of activity patterns; microsimulation at junctions

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Big data: opportunities for exploration and engagement The data revolution is changing relationships: open data, scenario testing tools, ‘games’ and 3D visualisation are enabling debate

3D movies: making the case for change Bringing together data collection, quantitative analysis, modelling and visualisation to produce high-resolution 3D movies

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Bluetooth tracking for data capture The introduction of Bluetooth tracking has had a real impact on cutting survey and data capture costs

A LUTI model with a difference The Leicester and Leicestershire Integrated Transport Model represents the most detailed land-use application built to date

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© Landor LINKS Ltd 2012

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There’s a new world of data available: how do we harness it for analysis, communication and modelling ?

Decision-makers, analysts, forecasters, behavioural modellers and a raft of kindred professionals are moving into a new world of data capture and presentation.This move holds out possibilities for the analysis of movement, living and activity patterns on a scale as yet unprecedented. It is an exciting, but potentially overwhelming, prospect. By Juliana O’Rourke and Peter Stonham

From data that is hard won, and expensive to obtain, we are on the brink of creating a vast pool of information sources and models for use in scenarios where existing tools may be ineffective and inflexible as well as costly. For government and business, the benefits are potentially huge – helping with better decision-making and appraisal. In an era of localism and support for neighbourhood planning, we need to adopt approaches that support analysis of the full range of possibilities around how, where and when people wish to move and behave. The creation of such rich evidence bases will impact heavily on investment and development priorities, enabling politicians and policy-makers to make more informed decisions on the back of a much deeper understanding of place and movement.

The amount of data in the world continues to explode. Our ability to analyse large data sets – big data – means that organisations from professional practices to the public sector are faced with a steep data analysis learning curve.

Research by McKinsey suggests that leaders in every sector will have to grapple with the implications of big data.

‘The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things (IoT) will fuel exponential growth in data for the foreseeable future,’ it states (see panel on facing page).

Significant value can potentially be unlocked from the ability to carry out deep analysis across the spectrum of human movement and behaviour patterns.

McKinsey’s own research suggests that, in the developed economies of Europe, government administrators could save more than €100 billion in operational efficiency improvements alone by using big data, and that users of services enabled by personal location data could capture €400 billion in consumer surplus.

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Opportunities for modellers These opportunities are good news for those whose work involves data and modelling. In future, there will be a shortage of the talent necessary for organisations to take advantage of big data, adds McKinsey.

‘By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions,’ it states.

Of course, the regulatory machine needs to grind through a few gears before big data can be used really effectively. Policies related to privacy, security, intellectual property and liability all need to be addressed in a big data world. Access to data is mission critical, and companies will increasingly need to integrate information from multiple data sources, often from third parties, and the incentives must be in place to enable this, says McKinsey.

Maximising investment This data revolution, coupled with swift advances in digital technologies, is changing the relationship between designers, planners, elected representatives and communities involved in place and movement, says consultant and digital media specialist Peter Warman (see page 27). Scenario testing tools and ‘games’, 3D visualisation systems, real-time data tracking and collaborative management tools are enabling public debate and discussion to come before, and not after, decision-making relating to transport and urban infrastructure investments. Good models can help us to maximise investment strategies by highlighting development opportunities through enabling the realisation of true value, so channelling investment into key sites and infrastructure schemes.

An explosion in the availability of tracking, digital and online data opens up opportunities for cities, city planners, and transport professionals. We face a potential leap in the extent and depth of the analytic capability that will be available, and equally key changes in the costs of providing them, says Steer Davies Gleave’s John Swanson, who will be discussing this theme at Modelling World 2012

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The accelerating pace of technological and social change means that, inevitably, many professional areas are in the front line for a major rethink of capability; an issue that will be explored in full at the Modelling World event in London during July. Take the large-scale, robust models developed to date by the transport modelling profession, for example. These models – essentially ‘simplified’ descriptions of a system used to predict and evaluate change – are currently widely used to predict impacts and evaluate options for infrastructure investment and planning.

Many such models, suggests a recent paper from the Australian Victoria Transport Policy Institute, Improving Methods for Evaluating The Effects and Value of Transportation System Changes, tend to be biased in various ways that exaggerate the benefits of roadway capacity expansion and undervalue the impacts and benefits of strategies that encourage use of alternative modes. ‘Commonly used models tend to undervalue alternative modes and other travel demand management (TDM) solutions. TDM planning requires models that can predict the impacts of various changes, such as improvements in alternative modes, pricing reforms and marketing strategies,’ states the report.

Similarly, some models focus on quantitative factors (travel speed, operating costs and crash rates) and undervalue qualitative factors such as travel convenience, comfort and security – the challenge of accommodating qualitative

data in models is also on the Modelling World agenda. Many models traditionally use travel survey and census data to determine transport demands, establish baseline conditions and identify trends.

However, ‘the travel surveys they are based on tend to ignore or undercount nonmotorised travel, and so undervalue nonmotorised transportation improvements for achieving transportation planning objectives’.

Other models may ignore the parking and vehicle ownership cost savings that may result when travellers shift from car travel to alternative modes, and many ignore the safety benefits that result from reductions in total vehicle mileage. Widely used integrated transportation and land use models are costly to develop and complex to use, and may be difficult to apply, particularly for the evaluation of the iterative, smaller-scale projects that are beginning to be favoured over large scale initiatives in an age of austerity.

Rising to the challenges Transport modelling has, says Mott Macdonald’s Tom Van Vuren, coordinator of the Modelling World programme, always attracted professionals from a ‘broad church’; making progress through learning from other disciplines (read Tom's article on page 11). But lately, he admits to wondering whether this very positive inclination to knowledge-share may be waning. Have we, he asks, fallen victim to Group Think,

“The creation of rich evidence bases will impact heavily on investment and development priorities, enabling politicians and policy-makers to make more informed decisions on the back of a much deeper understanding of place and movement”

whipping ourselves into a frenzy of protecting the status-quo? ‘Inevitably,’ says Van Vuren, ‘new and different transport model approaches would contravene the guidance in WebTAG – but is that really such a big problem? I have never believed that WebTAG should be used as a brake on innovation. Forcing UK best practice (as encapsulated in WebTAG) on projects anywhere in the world, where data, skills or future growth are so much more uncertain, makes little sense.’

New approaches Some of the best evolving approaches model the behaviour and needs of individual transport users, or agents, rather than aggregate groups and can do so with data from new sources from location tracking with Bluetooth (see Nick O’Neil's article on page 33), and face recognition (see Peter Stonham’s article on page 17).

New types of models can, in some cases, more realistically reflect activities such as

The Internet of Things (IoT): connecting things as well as people A recent report, Machine-to-Machine Communications: Connecting billions of devices, from the Organisation for Economic Co-operation and Development (OECD), outlines the potential impact of machine-to-machine communication (M2M) and the Internet of Things.

According to Rudolf Van der Berg of the OECD’s Science, Technology and Industry Directorate, the internet will soon move from connecting people to connecting things. In 2017, he writes, in OECD-countries, an average family with two teenagers could have 25 things that are connected to the internet: telephones, TV, tablets, printers, sports gear and health devices. Tens of billions of connected devices by 2025 is not farfetched. This data derived from these devices will facilitate, he says, the development of smart transport, smart cities, smart energy and smart health. ‘With 60 per cent of the households in OECD countries using broadband and more than 99 per cent of populated areas covered by mobile networks, the world is at the onset of another digital revolution.’

Urban Design & Masterplanning Improving Space

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walking, queuing, shopping and cycling, and the effects of factors such as parking supply and price, public transport quality, waiting time, the quality of the pedestrian environment and local land use accessibility factors.

Recent simulation models are also evolving, now incorporating elements from conventional traffic, economic and land use models and, increasingly, high quality movies that marry pedestrian modelling and 3D visualisations. A partnership between SKM Colin Buchanan and Wagstaffs Design, for example, uniquely brings together data collection, quantitative analysis, modelling and visualisation (see the article on page 30).

Smart growth In a decade that sees Governments determined to seek ‘smart growth’, transport and travel systems must focus on improving the user experience, achieving sustainability and contributing to both economic and social growth. Seamlessness requires that resources are used optimally: the convergence of transport infrastructure, operations and systems with the digital world is already changing the way we think about and use transport. Seamless transport requires the connection of traditional transport systems and networks with other infrastructure and services, such as water, energy and telecommunications – all an essential part of today’s society (see the aticle by IBM’s Chris Cooper on page 13). Transport infrastructure models will increasingly integrate with wider project lifecycles – another issue that will be explored in depth at Modelling World.

Smart investment in connectivity must strike a balance between providing highquality service and keeping investment rand operational costs low. We need to think in terms of mobility systems rather than modes and modal networks.

Modelling such smart growth in all its complexity requires key stakeholders and professionals alike to reflect on current practice. A final observation from the Victoria Transport Policy Institute report is that modellers should work to stay abreast of current research and improvements – which most good modellers do. This means looking to create models that take advantage of the data explosion, and that use comprehensive economic evaluation models accounting for all significant impacts, including road and parking facility costs, consumer costs, accidents, pollution emissions, and impacts on land use development patterns.

Ford and ‘joined-up’ mobility

Even the Ford motor company is getting behind smart transport systems. During his keynote address at the 2012 Mobile World

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“Smart cities and big data may be the hot topics of today, but the implications of how the city is being wired, how it is generating new data, how this data might force new theories and models relevant to our understanding, how we might use our strategic models and intelligence to plan the city, building on this new understanding – these are all crucial questions to be explored” As digital technologies are increasingly deployed in transport networks, data generated by their operations can offer new perspectives onto a city’s overall dynamics, say researchers at the Senseable Cities Lab at MIT. ‘When Singaporeans move through the city, sensors and digital networks are at play, supporting their movements: electronic road pricing gantries, car-counting loop detectors, and public transport smart cards generate data as part of their operations. In collaboration with Singapore’s Land Transport Authority, the Senseable City Lab has developed three interactive applications as part of the Visual Explorations Urban Mobility project that provide insight into the wealth of information that the data generated by Singapore's transportation infrastructure offer. Through these applications, experts and citizens alike can gain a better understanding on how Singaporeans move through urban space. The interactive combination, and exploration, of these different data can also inspire new services and tools supporting current, and future, urban mobility options.

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Smart cities, big data and the new research agenda Units such as the Centre for Advanced Spatial Analysis (CASA) at the Bartlett Faculty of the Built Environment, University College London, and the Senseable Cities Lab at Massachussetts Institute of Technology (MIT), Boston, USA, are pioneering smart cities research, drawing on cutting edge modelling, complexity, visualisation and computation techniques.

The new approaches were outlined at a recent CASA event in London, at which MIT took part. Smart cities involve hardware, software, data and ‘orgware’ ...we see these developments mainly in the delivery of services, such as transport services, to urban populations, says CASA. ‘They provide radically new data sources with respect to routine behaviours, with the potential to provide us with new ideas and new horizons for improving many aspects of urban social and economic life.’ CASA researchers are developing tools for online mapping, participation, modelling and tagging that define this new agenda for research and practice (see images, left).

Professor Michael Batty, Chair of the CASA Management Board, is a respected researcher into urban planning and design using mathematical modelling. Back in 2009, Batty wrote that models are being developed as much for their exploratory and discursive value in a wider participatory process of developing robust but contingent knowledge than for their ability to generate good theory. Over the past years, he has noted the ‘revolution in tracking human and other motion in digital form that enables the collection of multiple attributes at the finest of scales of urban observation’.

For a long time, he suggests, the city models we have built have tended to see cities as being in equilibrium where change occurs slowly over years and decades, but that this is changing as new data sources providing space and time streams provide us with new views of urban structure and pattern that could well demonstrate that cities are much less stable structures than we have previously perceived.

In 2012, in an editorial in Environment and Planning B: Planning and Design, Batty summed up some of his ideas on smart cities and big data. In the 1980s, he says, the focus on instrumenting the city using network technologies was enshrined in the idea of the wired city. But

what has changed is the development of ‘ubiquitous devices of comparatively low cost that can be deployed to sense what is happening over very small time scales – seconds and faster – as well as over very fine levels of spatial resolution’. Such devices, he writes, range from purpose-built sensors to individual hand-held devices that are as mobile as those using them provide massive capability to store and transmit data that pertains to movement and activity levels across space and time. ‘Some of the most elaborate applications,’ he adds, ‘involve transport’.

Integrating and linking data There are vast quantities of information, he says, ‘much of it of doubtful quality so far but it will improve’, associated with social media and networking. ‘The idea of integrating much of this diverse data together to add value to our conceptions of how it might be linked to other more traditional data, as well as focusing it on specific ways to make cities more efficient and more equitable, has come to define the smart cities movement.’

Many large-scale IT companies, he notes, see the next great wave of applications related to groups rather than individuals, and these are seen most clearly in how large groups behave with respect to routine activities in cities. ‘IBM, Cisco, Siemens, and a host of other companies are investing heavily in systems that can be used to mine traffic and related data which lie at the basis of an improved understanding of how cities function, as well as enabling new methods of improving the efficiency of such systems with respect to their operation and the quality of the experience from the point of view of the traveller. We are just beginning to grasp the nature of “big data”,’ he suggests.

‘This kind of data is available continuously and in this sense, it does not only encapsulate routine and relatively stable behaviours but, over sufficiently long periods of time, one can begin to extract changes to the structure and form of the city and the way people behave.’

New data begets new theory, notes Batty.

‘Most urban theory, and indeed planning and design 50 years or more ago, was predicated on radical and massive change

Modelling the London riots In August 2011, London and other cities in the UK experienced looting, rioting and violence. Much of the subsequent discourse has concentrated on the adequacy of the police response, specifically in terms of the resources available and tactics used. CASA has created a mathematical model of the disorder which can be used to examine the effect of varying policing arrangements.

The model is capable of simulating and replicating the general emergent patterns of the events and focuses on three fundamental aspects: the apparently-contagious nature of riot participation; the relative positioning of suspect addresses and riot locations; and the deterrent effect of the police.

CASA uses the model to demonstrate that the spatial configuration of London meant that some areas were naturally at higher risk than others.

to city form and structure through instruments such as new towns, large-scale highway building, redevelopment, and public housing schemes. Planning was little concerned with smaller-scale development except its design, for nowhere was the function of the city understood in terms of how small spaces and local movements sustained the city. New data and big data are changing all of this.

‘Smart cities and big data may be the hot topics of today, but the implications of how the city is being wired, how it is generating new data, how this data might force new theories and models relevant to our understanding, how we might use our strategic models and intelligence to plan the city, building on this new understanding – these are all crucial questions to be explored. Our need to understand how all these dimensions are coalescing, merging, complementing, and substituting for one another has never been more urgent. It constitutes a major challenge for planning and design in the near future.’

Catch up with CASA speaker at Modelling World 2012

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Congress in Barcelona, Ford executive chairman Bill Ford outlined a plan for a ‘joined up mobility’ solution that will help avoid a potential future of what he called ‘global gridlock – a never-ending traffic jam that wastes time, energy and resources.’

Ford called for partnership between the automotive, passenger transport and telecommunications industries to create an inter-connected transportation network as part of the solution.

‘Our cars operate on more than a million lines of code and have more processing power than many of today’s laptops,’ he pointed out. ‘They have a hundred times the sensory capacity of many smartphones and yet all of that potential is essentially just

sitting there. Whether you look at it as a business opportunity or as a human rights issue, how we move around our world in the future is one of the most compelling challenges we face. We need a system that uses real-time data to optimise personal mobility on a massive scale, without trade-offs or compromises for individual travellers.’

Localism and engagement Through crowd-sourced and social mediabased information, the public is enabled to become much more directly involved in urban infrastructure decision-making. And, suggests Colin Pooley of Lancaster

University, as mobile internet applications and devices become pervasive, ubiquitous, and central to social belonging and cultural participation, the concept of mobilityrelated environmental and social justice should become more relevant to movement models. ‘Modern life is underpinned by intensifying forms of automation, sensing technologies, real-time data gathering and analysis, and surveillance. At various points in the 20th century there were opportunities to produce a transport infrastructure that delivered more socially and environmentally just patterns of everyday mobility, but such opportunities were lost as subsequent decisions reinforced existing mobility inequalities.’

(from top left) Transport and movement data, such as that gathered from mobile phone tracking and bike hire schemes, says Jon Reades, Centre for Advanced Spatial Analysis (CASA) at UCL, and in particular the behavioural data derived from smart ticketing, is essential to realising the smarter city.

Added to this, computer visualisation – another theme we'll be investigating at Modelling World – communicates more complex data more powerfully than ever before, says Reades. Although the ongoing costs of creating and maintaining open data should not be underestimated, open data and visualisation offer new ways to harness ‘big data’ for operational and strategic goals, while engaging the public, academia, and policymakers

We need to view the automobile as one element of a transportation ecosystem, and look for new ways to optimise the entire system, says Ford Motor Company’s Bill Ford. We need a system that uses real-time data to optimise personal mobility on a massive scale, without trade-offs or compromises for individual travellers. A smart system that ties all modes of travel into a single network linking together public and personal transportation. Pedestrian walkways, bicycles, buses, planes, trains, automobiles – everything fully integrated and optimised to save time, conserve resources and lower emissions

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Learning from other disciplines How can we as transport modellers take what is good in the profession, borrow where applicable from other professions, and apply innovation in new environments, reducing costs and supporting decision-making where we can add the greatest value, asks Tom Van Vuren?

Transport modelling has always attracted professionals from a broad church. I have worked with many a civil engineer, in fact I am one myself, and over the years my colleagues, students and mentors have included geographers, mathematicians, physicists and social scientists. I even once worked with a biologist –who coincidentally had completed a PhD on the subject of snails…

You won't be surprised to hear me say that transport modelling is not easy. The large geographical areas that our models cover; the intricate short term dynamics and interactions between vehicles, traffic control and transport infrastructure, the maddeningly complex and often irrational behaviour of travellers, our increasing desire as a profession to make models more complex mathematically but also quicker to compute, the constantly changing environment that our analytical tools need to reflect, the influence of weather and random events; it all adds up to one of the trickiest and most fascinating modelling areas I could imagine. An American colleague quoted to me last year: ‘Transport modelling, it is not rocket science. It is much more difficult than that!’

He was referring tongue-in-cheek to the Los Alamos National Laboratory – the birthplace of the atom bomb. In the late 1990s scientists there threw their weight, brains and super-computing power at understanding and simulating traffic flow.

More than a decade later, all I have seen from this effort are a few research papers.

I'll stick my neck out: we are generally clever people with clever tools. We have lots to offer other disciplines. We can also be insular and a bit arrogant. Without a Masters degree, grey hairs and an intimate knowledge of WebTAG, surely you cannot be taken seriously? The modelling profession seems to forget that much of the progress that we have achieved over the years has been through learning from other disciplines, exploiting analogies (fluid mechanics, communication networks, market research), benefiting from breakthroughs elsewhere. What is now known as the Frank-Wolfe algorithm, was originally presented by its authors in a naval journal, long before transport modelling was commonplace, and only discovered by the profession in the 1970s.

Similar stories can be told about the application and development of discrete choice theory, now such an integral part of demand forecasting.

Last year, the Transport Modelling Forum was renamed Modelling World. Doing this reflected three intentions: broadening the offering from just modelling to include data and visualisation. And last year, for the first time, the conference offered three parallel streams, and quite successfully; bringing in speakers, exhibitors and attendees from other disciplines, seeking to introduce new ideas. Remember the plenary about risk analysis?; exploring other areas where the skills and techniques developed in transport modelling may also be of use.

The opportunities for transport modellers applying their skills elsewhere are obvious.

Some of my brightest transport modelling colleagues are already providing more general modelling and quantitative analysis services in Mott MacDonald, and to a whole range of non-transport clients, including in health, housing and tourism. My team has become a focal point for good practice in complex VBA programming in EXCEL, and for advanced GIS applications. This is my point: perhaps it is time to shed the modelling prefix, and be proud to be modellers full stop. With the change in title could come a freedom to explore other areas of similar complexity, and with similar characteristics: long and short term dynamics, wide geographic coverage, socioeconomic segmentation and response behaviour, and a new opportunity to discover different, better ways of representing the complexities of transport systems, than the software driven reality of the past two decades.

Inevitably, new and different transport model approaches would contravene the guidance in WebTAG. Is that really such a big problem? In a recent on-line discussion one of the other participants complained that transport modellers have fallen victim to Group Think, whipping ourselves into a frenzy of protecting the status-quo. I have never believed that WebTAG should be used as a brake on innovation. Of course, for major infrastructure investments a common methodology, common

“I'll stick my neck out: we are generally clever people with clever tools. We have lots to offer other disciplines. The modelling profession seems to forget that much of the progress that we have achieved over the years has been through learning from other disciplines and benefiting from breakthroughs elsewhere

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assumptions, common and minimum standards make eminent sense. But there are so many other applications of transport models where such rigour may be misplaced, limiting realism where existing tools are just not suitable, or making analytical support unaffordable. Forcing UK best practice (as encapsulated in WebTAG) on projects anywhere in the world, where data, skills or future growth are so much more uncertain, makes little sense. I may be abusing the term, but the concept of frugal innovation, developing tools and techniques where none existed, and at minimal costs, is relevant and exciting.

Which takes me back to this year’s Modelling World. With its roots still firmly planted in transport modelling, the event offers, even more so than last year, insights from other disciplines, exhibitors with products that you have not seen before, speakers that have new and exciting points to make. I know that for years I have looked in vain for that breakthrough in speed improvements, for affordable visualisation and a better way in which to understand and represent real travel behaviour, and particular change in behaviour (what so many policies now seek to achieve). I will scour the programme and exhibition for names, faces, concepts and products that I have not come across before, intending to learn something quite radical to use in my work during 2012. I hope you will join me.

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FOR MORE INFORMATION CALL - 0844 272 2394

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What does ‘smarter mobility’ really mean?

The core of being smart is in the intelligent and creative use of data. This will make transport more accessible, adaptable, predictable and above all, more sustainable.

So how can we best harness data to unlock the new mobility? It’s as easy as LTP, says IBM’s Chris Cooper A common theme among many futuristic views of our personal mobility is the way in which data will be used to make transportation smarter. But do we all agree what ‘smarter’ actually means? For myself, the real significance of smarter transport is in changing the relationships between citizens, transport providers and the state. It will impact all our professional lives – notably in the ways in which we deploy our resources, and how we operate and measure our organisations. The core of being smart though, is in the intelligent and creative use of data. This will make transport more accessible, adaptable, predictable and above all, more sustainable.

To achieve a smarter transport model, based on a high level of information exchange, several key elements must first come together: a critical and almost perfect mass of data which can be turned into knowledge; an audience which can interact with, and benefit from this knowledge; a fundamental multifaceted trust between provider and consumer.

External factors (such as carbon reduction, sustainability and congestion reduction) will serve to act as economic and cultural drivers for such change. And alongside this a set of accounting measures for a new commercial paradigm that the market can consume will need to be set out.

Finally, the world of transport for both the provider and consumer must

3D Visualisation Bringing projects to life

because travel outcomes will be based upon three criteria: Current and intended location: L The time now, and the time by which it is desired to arrive at destination: T ‘Prioritised Preferences’ or the ‘value for money' driver – How fast, how much, and in what style: P This LTP quotient will, I believe, set the trend for the next generation of interactions between a transport provider and its customer’s needs.

Travel behaviour

unreservedly embrace the true idea of mobility. By this I mean the removal of barriers between transport silos, in order to facilitate seamless journeys in the best available way, irrespective of mode.

The move to such intelligent mobility is not inevitable. It will require seeding and nurturing as it grows in scope and uptake.

The end-game could be described in the following way: the consignment (be it a person or a package), seamlessly reaches a destination based upon the most efficient travel outcome at that time, according to the travel rules prescribed by the user. The use of rules is required

A starting point that we can see today is how new and smarter use of data already enables a change in traveller behaviour.

This then influences transport providers in what they provide, creating new business platforms – and is likely to challenge established legislation and regulatory constraints too.

The new paradigm is evident in the use of data from personal smartphones and the bi-directional relationship that sees the constant flow of information between the device and a service provider. The service provider aggregates data from multiple sources, and then provides personalized, and immediate, information back to the device. Since the device is a wallet, and a translator too, the citizen can travel unimpeded by traditional barriers, and with unprecedented quality of information.

An early example of this bi-directional information exchange is a pilot which IBM has been running in conjunction with the

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California Department of Transportation and the University of California, Berkeley.

The Smarter Traveller project is based upon a predictive and analytic traffic tool, helping transportation agencies and city planners proactively design, manage and optimise transportation systems to handle more seamlessly the ever-increasing traffic that results from population growth and increasing urbanisation.

Where and how information gets processed and personalised underlines the need to collaborate across boundaries.

The collaboration can take various forms and crosses multiple elements: different transport modes sharing service information; regulators encouraging integrated operations between transport modes; collaborative planning of infrastructure, for example the design of inter-modal hubs to aid the flow and interchange of passengers; information flow across boundaries via the on-going growth of the Internet of Things and the use of new information to improve use and management of transport and infrastructure assets; cross-industry collaboration. Structural engineers collaborating with IT engineers, city planners and transport providers to improve the design of transport infrastructure, to be adaptive to changes in demand or in environmental conditions; embracing social media such as use of Twitter feeds to alert maintenance engineers to changes in service status, to collect customer satisfaction information, or to generate demand via a personal link to the customer.

Once such data collaboration has been agreed, the next step is to provide a place in which to store and analyse the data, and turn it into something useful. Some call this 'Intelligent Information. This is really tailored and trusted knowledge.

And the crucial consequence is the actions this disseminated and personalised knowledge leads to. For example, trust with users, suppliers and partners will lead to improved customer satisfaction, brand-loyalty and wider adoption of the services. ‘Smartness’ also lies in the analysis of all the available data, and creation of information which drives new business

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insight, and then brings the right parties together to act upon it. Possible outcomes for the service providers include predictive maintenance schedules, improved asset utilisation profiles, and safety vs. cost vs. risk models which may be constantly updated using real-time information. From a citizen viewpoint what is delivered is a new sense of freedom not dependent on a specific mode of transport.

The business paradigm that underpins

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all this needs defining and explaining. To that end IBM has invested in a new Laboratory based in Dublin, and is actively working with academic partners such as the Centre for Smart Infrastructure & Construction to identify how new and old smart-enabled infrastructures can be better designed, used, managed and re-cycled.

For transport providers the ability to seamlessly predict demand and then manage supply accordingly increases

IBM is working with the California Department of Transportation (Caltrans) and California Center for Innovative Transportation (CCIT) to develop an intelligent transportation solution that will help commuters avoid congestion and enable transportation agencies to better understand, predict and manage traffic flow

Data Collection Innovative, intelligent survey design and delivery

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DATA & MODELLING efficiency, improves asset utilisation and can boost customer satisfaction. To benefit society as a whole, we might aim to reduce road congestion by providing travellers with personalised integrated journey planners as an incentive to using public transport. In doing so, this might also increase walking rates, with a corresponding impact upon public health.

A potential investor in such a scheme might therefore be the Department of Health. In such a scenario, data can be transformed into knowledge which may then be used to track benefits accruing to multiple stake-holders. All-in-all, this concept has massive future value to a number of different agencies and interests.

Pinpointing the value of urban activity New – but familiar – urban realm valuation tools could enable highways engineers to better understand the value of quality public realm and support more informed decision-making for local politicians and investors, says Brian Fitzpatrick

Quality and service Measuring a service provider's reputation in this context, with regard to quality of service and value for money, will be based on many factors. Such opinions will shape how providers package and price transport services. A ‘total journey’ offer may become the normal expectation for example and, instead of a car journey from A to B, the option would be offered of a car club from the village to the parkway station, then a train into the city followed by a cab to the destination, all paid for via one ticket, supplied by one provider.

There are some consequential issues to address. From an end-user perspective, the need to share one’s status, preferences, location and intentions could have drawbacks.

Participating organisations must be made aware of what happens to their data and have confidence that the service they receive in return gives them the value they expect. Government legislators will need to provide a robust regulatory and legal framework that will support a fair and equitable use of this information.

In a follow up article I will explore these themes in a little more detail.

I believe that a number of factors are coming together that will create new opportunities and enhanced outcomes, as well as new ways of measuring output, success and satisfaction.

Yet I also foresee many challenges occurring, which if not managed appropriately, will hamper the true potential of the age of smarter transportation and the ‘move to mobility’ which it entails. The prize of harnessing all the information and insight now available is a much more sustainable, efficient and effective transport system.

Chris Cooper is IBM Industry Architect for Travel & Transportation: coopecj@uk.ibm.com Hear him at Modelling World 2012

Traditions of high quality engineering could, it can be argued, be more concerned with function than form. The result, in many cases, is well-engineered infrastructure that often fails to consider the wider implications of how it contributes to the aesthetic environment and the wider public realm.

A recent breakfast briefing at New London Architecture brought together developers and local authority senior officers to debate this issue, particularly in relation to new tools being developed to better articulate the potential value of public realm – be it the quality of its built form, accessibility, security, health and/or impact on surrounding development value – thereby monetising the debate around investment.

This is particularly pertinent given the current financial constraints, which risk a Public realm improvements can generate measurable added value

reversal in the progress made in recent years in the delivery of high quality public realm. Is there an opportunity to establish a more sustainable approach to investing in public realm improvements? And should this approach be based on a central premise that ‘the road is not the customer’ but should instead be viewed as a one element of the public realm that should not absorb all of its resources, or dominate the form of our urban environment?

It’s clear that we need to better understand the relationship between increases in land and amenity value following urban realm investment and development, so that we can provide tools enabling a more focused dialogue between local authorities and potential development partners. To this aim, EC Harris has developed a tool that measures asset deterioration over long periods of time, as well as the ‘value’ of improvement or remedial interventions in a wider context.

This tool is able to support public realm investment decisions or comparisons. We agree that the orthodoxy of roads infrastructure dominating the urban realm in terms of both form and function needs to be challenged, but we want to bring this about in a way that highways engineers are happy with. We call our approach evolution, not revolution.

A useful decision-making tool As an engineer who has also been a senior officer client, a consultant and an elected councillor for local authorities, I have a rounded perspective on the pressures faced by authorities, and on how the public realm is funded. At EC Harris we have been using an asset valuation platform for some time to value the highways estate for strategic roads authorities. To comply with Treasury guidelines, the depreciated replacement value of inter-urban routes has to be calculated and accounted for.

Alongside this, the Whole of Government Accounts (WGA) initiative (which aims to

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approach to valuing the public realm in isolation from TfL, we’re now testing ways of using elements of the TfL toolkit (the categories) together with our platform to develop a key strategic decision support tool for urban realm investment.

Some enlightened local authorities do consider roads in terms of their amenity value to their users. But the value of the public realm for those who live near the road, or who would like to see different types of infrastructure in place, is not accounted for in any efficient way at the moment.

produce a set of consolidated financial accounts for the UK public sector on commercial accounting principles), required that local authorities evaluate the depreciated replacement cost for roads.

From a business perspective, I was aware that our platform would be very useful for local authorities. We could clearly see a relationship between the amenity value of the public realm and the fact that value is derived in part to the fact that it is maintained by highways engineers, who are mainly focused on the road.

At this point, we began to look at a public realm valuation tool being developed by Transport for London (TfL), and organised knowledge-sharing sessions. So, although we developed our

Brian Fitzpatrick is Head of Highways, EC Harris

Measure, map, model and make The challenge for urban design practitioners is to show politicians and investors, along with the transport community, how multi-scale activity rooted in quality of place generates real, economic value, says Tim Stonor Work undertaken at Space Syntax in recent years has identified many strong connections between urban design and property value. We have found strong correlations between the way space is planned and the economic impact that it has, for example on property taxation and rental income. Good urban design increases investment potential. Indeed it is possible to argue that it is only through good urban design that property value can be truly realised. But value, of course, can be

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expressed in social and cultural, as well as economic terms, and successful placemaking is the sum of all these impacts, simultaneously occurring in a natural way.

Our big step forward has been to develop tools that measure this complex matrix of urban design value. These tools reveal the crucial contribution of local movement networks. They show that it is not, and never has been, all about major roads – big infrastructure. But nor is it only about local

streets and squares. Instead, our research indicates that what matters is the way places connect at all scales: macro, meso and micro. It is about how larger-scale movement converts into, and interacts with smaller-scale movement to generate the interactions that lead to social and economic transactions. This balance has been lost in recent decades, usually with too much of an emphasis on the macro as witnessed by extensive road building, but very little place-making.

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DATA & MODELLING The challenge for urban design practitioners should be to show politicians and investors, along with the transport community, how multi-scale activity rooted in quality of place generates real, economic value. But this argument has often been lost either because urban designers have focused too much on local placemaking (and therefore too little on the planning of towns at every scale) or because their analytic methods have been too few and too weak in the face of weighty transport models that have delivered carboniferous road after road.

To make the difference that is needed, urban design methodologies should be just as informed, evidence-based, and scientific as transport models. More so indeed. And creative too. Urban practitioners need to be rigorous and objective about the built environment. But do urban designers have the mindset to measure and, even if they have this, do they have the tools to help them?

Unfortunately, in many projects I look at, a figure-ground plan and a five-minute ‘ped shed’ is about as scientific as it gets. And that is just not good enough when the levels of investment and scales of impact are so great.

Our argument at Space Syntax over many years has been that there is tangible value in urban design. Our goal more recently has been to show exactly how this ‘place value’ can be measured through the analysis of key urban design components such as spatial layout geometry, land use distribution and density – how these factors lead to economic spend, safety and security.

We now have these tools and we are applying them in projects worldwide with positive results. Developers who have difficult choices to make need clear evidence; by building urban design characteristics into real estate financial modelling, we can speak a common language. In the same way, describing design proposals in terms of their implications for safety and conviviality can give neighbourhood groups the confidence to speak up about their own ideas and aspirations.

However, if urban practice is to undergo the step change that I believe it should – to equip itself with models and methods to reverse almost a century of anti-urban roadbuilding, then the techniques that Space Syntax has developed need to be disseminated. In doing so, our aim should be to raise the status of urban design to a higher level. At the moment, discussions about the value of good urban place-making are often in the policy ‘quiet corner’ but they should be centre stage.

It has typically been because of exceptional political leadership and exceptional design leadership that great

places have happened, as in the redesign of Trafalgar Square, Kensington High Street and Ashford. But we can not rely alone on such forces – the importance of good urban design needs to be institutionally recognised and this will only happen, I believe, once value-creating urban design methodologies, such as those developed by Space Syntax, are professionally embedded.

I do sympathise – to a degree – with people who aren’t convinced about Space Syntax’s models because, although the techniques are widely used by us in practice and by researchers all over the world, we haven’t made them available to be easily used by other practitioners. We haven’t yet put our software in the hands of planners, architects, urban designers, transport planners and urban economists, so that they can see the value for themselves. We have published extensively in academic journals, but people in practice don’t often read these. Our approach has often been too technical for a professional audience.

But I have little time for people, usually architects, who say that science has no place in design. Or, that there is no connection between design and behaviour, never mind value. Who are they kidding?

The evidence is too strong. If we care to measure environmental and structural performance, then why should we not also care about something of even greater value: the human factor?

To create the change that I believe is needed to raise the quality of urban planning and design by using rigorous,

Trafalgar Square accessibility before (far left) and after (left and above): the work done by Space Syntax was part of the evidence base providing confidence to go ahead with remodelling the square

science-informed methods, then we need to make Space Syntax’s methods more accessible, affordable and useful.

This means we as an organisation need to disseminate our processes and our learning in ways that we haven’t previously been geared up to do. This is now happening. Our first step has been for the key analytic software to become ‘open source’, making it freely available for anyone to use it and develop it. Our next step will be to openly distribute the knowledge bases that will allow the software to be really well used.

We are now ready to share our technology, the techniques behind the technology and the learning we have embodied over 40 years. In doing so, our aim is to equip urban practitioners with tools and techniques that will strengthen the argument in favour of great towns and cities by demonstrating the social, economic and environmental values that flow from careful urban planning and design.

The transport profession has dominated the making of place for the past 50 years because it has counted and modelled.

Measurement is power. Urban practice has much to learn from the transport industry if its legacy is truly to be one that is great.

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Harnessing CCTV image data for behavioural insight and modelling Since the advent of digital cameras and image capture, a new world of behavioural and identity tracking has opened up, adding to the toolkit for data capture and analysis supporting the understanding and prediction of activity patterns, says Peter Stonham

Cameras are these days watching everywhere: and what they see can increasingly become a major management tool. The subjects ‘under surveillance’ can be human – or mechanical. Early applications have involved vehicle and automatic number plate recognition (ANPR) allowing traffic patterns to be recorded and individual vehicle movements matched in origin and destination surveys and control regimes such as car parking, tolling and congestion charging.

Today, the use of human behaviour modelling and individual activity tracking through facial recognition is becoming a defined area of technical and professional development in its own right – with security, access and border control among the early adoption areas. Some elements are becoming defined in the specialist technology of biometrics – where very precise user-identification through iris recognition has been trialled for passport control, for example.

Where less individual-focused security or monitoring objectives apply, other applications have also been moving ahead.

Queue management and crowd dynamics are two of the most advanced areas, particularly in stressed and capacity

constrained environments like airports, terminals and stadia. One of the companies leading development in the this field, Amor Group, sees the prospect of 100 per cent people tracking in real time by 2020, using the fast-developing Google image network.

As well as video analytics from Blue Eye Video, the current Chroma ACDB system includes Bluetooth tracking from Blip Systems, thermal imaging people counters from Irisys, wireless tensabarrier counters from Qmetrix and ANPR vehicle tracking.

To date, Amor’s ChromaRMS systems include PAXPredict + Forecaster and PAXPlan + HMRS for staff management, which the company expects to integrate within its Chroma Airport Suite sometime during 2012.

It gives its ACDB ‘roadmap’ to full facial tracking as offering a less expensive way to capture passenger faces in real-time at the process start, and matching ‘in process’ faces at their end location. A scheduled release at the end of the year is planned.

Alongside this, Amor is incorporating additional tracking information from smartphone WiFi signals by passive tracking, with no requirement for an ‘app’.

This is being released as an upgrade to BlipTrack, and integrates both WiFi and

“When passenger queues encroach on passenger circulation areas, Blue Eye’s B-Queue system raises a real-time automatic alarm (SMS or email on a smartphone or tablet PC) with video proof, instantly alerting operation managers to a developing situation, with action plans implemented to optimise passenger flow and enhance security”

Bluetooth tracking data. Chroma’s ACDB system also involves thermal imaging path detection to cater for closely packed queues. Based on Irisys Thermal Imaging Technology, it is scheduled for release in the third quarter of 2012.

Applied identity Arguably the leading developer of face recognition systems is NEC. ‘It has been known for some time now that NEC has the most accurate facial recognition algorithms available world-wide,’ says Allevate, a UK-based company specialising in the field of “Applied Identity”. ‘This has been independently demonstrated by the US National Institute of Standards and Technology, and numerous other

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Monitoring aggregated passenger flows and queue lengths using automated face recognition It is becoming increasingly important for organisations such as airlines, airport and terminal operators, venue managers and retailers to monitor queue lengths and the flow of people through their premises. Having a detailed real-time overview of the number of people on premises, as well as collated information on trends and fluctuations in people flow, enables organisations to make quick and informed decisions on the appropriate resource levels to ensure public safety, manage capacity efficiently, and maximise customer experiences.

NEC’s NeoFace Flow solution timestamps when individuals are detected at known camera locations to provide highly accurate information on people flows, such as average queue times. This provides insight on how people move through any environment. No specific people identifying information need be recorded, and data can be purged at regular intervals.

Existing queue monitoring solutions have generally required visitors to have an active tag, such as a Bluetooth device, resulting in very low sample rates for measurement. Face recognition overcomes this problem and NEC’s NeoFace is generally regarded as the most accurate facial recognition identity management algorithm available today, as independently verified by the US National Institute of Standards and Technology (NIST). Its tests also demonstrated that NeoFace provides the fastest matching capability that is the most resistant to variants in angle, age and race.

The system operates by deploying CCTV cameras enabled with biometric technology, that log enrolled individuals with a camera number and time stamp to create data which is automatically aggregated to provide real-time analysis of people flows and movements. The database is automatically purged as required at regular intervals.

The outcomes are aggregated people flow data, average time to move between two or more points and average time staying in a specific area, plus real-time reporting information and historical data comparison over specific time frames, with alerting mechanism (for instance when queues are too long).

According to NEC the benefits include capturing and checking thousands of visitors per hour without any personal details, operating unobtrusively and not requiring special devices, such as Bluetooth phones. Overall, it gives a high sample set and penetration rate.

NEC IT Solutions, the European IT services arm of NEC Corporation, is a provider of intelligent IT solutions designed to enhance business processes and technically empower customers within the public and private sectors.

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independent evaluations.’ NEC has recently released a full suite of solutions incorporating this technology, with NEC Europe’s NeoFace Suite of face recognition solutions.

The solutions are designed to support and optimise surveillance, identification, security operations and people flows by using face recognition, focusing on law enforcement, government, border control and airport passenger environments.

But, say Allevate, there will undoubtedly be further application to numerous other environments as well, such as transport and retail.

NeoFace Match is specifically designed to allow authorities to match captured images against large databases of face photos.

NeoFace Watch and NeoFace Find integrate with existing surveillance processes by extracting faces in real-time from CCTV and large volumes of video footage, and matching against a watchlist of individuals.

NEC’s NeoFace Flow solution ‘timestamps’ individuals detected at camera locations to provide detailed information on people flows, such as average queue times. This provides insight on how passengers move through any environment. ‘No specific people identifying information need be recorded, and data can be purged at regular intervals,’ says the company (see panel).

Video surveillance Serious discussion of the technology and benefits of face recognition by cameras has been taking place at both meetings of the National Institute of Standards and Technology (NIST) and the IEEE Computational Intelligence Society in North America.

At this year’s NIST International Biometric Performance Conference in Gaithersburg, Maryland in March 2012, Dmitry Gorodnichy and Eric Granger of the Canada Border Services Agency explored the state of development of evaluation of real-time face recognition technologies for video surveillance applications.

Working in the Science and Engineering Directorate of the Agency’s Video Surveillance and Biometrics Section, they described the PROVIT project and how it evaluates state-of-the-art commercial technologies and academic systems for face recognition.

As well as public data sets for medium-to

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DATA & MODELLING large-scale evaluation, there are evolving experimental protocols for different still-tovideo and video-to-video surveillance applications, including screening of faces according to their resemblance to a wanted list, matching a face across several video feeds and fusion of face recognition from different cameras while tracking a person.

The Canadian project has looked at performance measures including transaction-based (P-R curve) and subjectbased (biometric menagerie) analysis. This is an area where biometrics meets video surveillance, and evaluation of systems for Face Recognition in Video Surveillance (FRiVS) is looking at both publicly-available datasets and lab mock-ups to develop specialised performance metrics and protocols that integrate face recognition into operational CCTV environments.

Activity monitoring in the airport The most active environment in which the relationship of CCTV and activity monitoring is being explored and applied is the airport.

French Specialist Blue Eye Video SA of Grenoble, which has been working in partnership with Amor, points out that increasing volumes of traffic and security constraints at airports have led to movement becoming increasingly inefficient, with passengers spending more time waiting to buy tickets, check in, at luggage inspection and at passport control.

In this context, managing passenger wait time is crucial to improving the transport system’s performance, enabling visitors to spend more time in the retail areas and preventing costly delayed departures. Blue Eye believes its measurement and monitoring systems can help management anticipate traffic congestion problems and keep passenger traffic flowing as smoothly as possible, reducing wait times, optimising

passenger flow and providing decisionmaking tools for better operator management.

The wider area of understanding passenger flow and behaviour now includes the use of data from counting sensors, people counting software, queue measurement, and wait time and database analysis tools. For image capture, an important step was using a video stream analysis combined with Sony Smart Camera architecture to determine how many people are waiting in queues and patterns of customer behaviour in a shopping, airport or stadium environment.

The provision of real-time data is a key element in ensuring that staff are deployed efficiently, Blue Eye says, enabling managers to make instant decisions and react to rapidly changing situations. The performance of different queues can also be compared and historical data used as an aid to resource planning by hour, day week or month.

Aéroports de Paris has been using Blue Eye Video queue monitoring for the past three years. The company believes that after six months its queue management solutions can dynamically optimise the resource allocation in relation to the number of passengers, enabling users to anticipate wait times beforehand.

Improving retail business revenues Passenger experience is key to improving airport retail business revenues. By displaying the estimated time to reach each gate (taking into account queues at transfer and immigration), passengers can feel less stressed and more comfortable in taking up refreshment and retail offers without constantly watching the flight information display systems. Based on standard video cameras, the company believes four weeks’ observation is enough

time to gain a real-time complete site overview.

When passenger queues encroach on passenger circulation areas, Blue Eye’s BQueue system raises a real-time automatic alarm (SMS or email on a smartphone or tablet PC) with video proof, instantly alerting operation managers to a developing situation, with action plans implemented to optimize passenger flow and enhance security.

Blue Eye video was born out of INRIA, the French national research institution focusing on computer science, control theory and applied mathematics, and has developed new algorithms based on more than 15 years of research on image processing, and a focus on crowd behaviour, including the Muslim Pilgrimage in 2004 in Kingdom of Saudi Arabia for the Hajj.

The technology detects the density of people to stop more than 3 million people rushing during the event. In 2005, with Aéroports de Paris’ help by testing every three months, during three years Blue Eye Video created an innovative queue management solution. It now works at Charles de Gaulle airport, the sixth busiest airport in the world by passenger traffic, and also Dubai Airports with its partner Amor Group. It is also present in several countries with local partners, working with Delta Airlines (Atlanta), Washington Airports, Lisbon airports and also train stations in France (SNCF) and supermarkets in Europe (Carrefour group).

ChromaACDB is currently being applied as the world’s largest Service Delivery Measurement solution being delivered to Dubai Airport. At Oslo Airport, Chroma data aid analytics have been supporting passenger forecasting since 2009 and passenger tracking since 2010, with a terminal operations ‘dashboard’ currently being introduced.

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Microsimulation key to improved road efficiency and capacity Microsimulation modelling has successfully been used by Siemens to improve traffic flow through heavily congested junctions in Banbridge, Northern Ireland, to determine the feasibility of linking them

All three junctions were heavily congested in both peaks and lie on a main commuter route for the area. The locality of a large school and its associated morning drop-off points were major factors contributing to a morning queue regularly extending over half a mile on the worst affected approach. A small gyratory system operating within the middle junction, restricted road width over a bridge, and the presence of heavily used bus stops within the network of junctions all contributed to the difficulty of improving traffic flow through the area.

Network modelling

The sites have various crossing locations and the pedestrian movement in the area has a significant impact on the junction’s operation

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Siemens’ Consultancy Services was commissioned by DRDNI Craigavon to carry out microsimulation modelling. Staff worked together to construct an accurate Paramics model of the three closely associated junctions. The scope of the project aimed to assess the potential impact of applying Microprocessor Optimised Vehicle Actuation (MOVA) control and various junction re-design scenarios at the junctions.

According to Martin Andrews, Head of Consultancy Services, it was clear from the outset of the project that the solution had to be future-proof and offer a real benefit to network users by reducing journey times and providing good progression through the junctions. The site is constrained by the width of the Bann Bridge and the short lengths of the internal junction links.

‘The options tested included a “do minimum” scenario with the introduction of linked MOVA signal control at each of the junctions and a “do something” test including geometric junction changes,’ said Andrews.

For the latter, the proposals included an increase in the geometric capacity for the outbound right turn movement and the upgrade of the signals to MOVA control.

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The implementation of the linked MOVA control system by Siemens was carried out efficiently and has had a very beneficial effect on traffic flows in the area

Data collection For this project, the geography of the area made it cost effective to deploy an automatic number plate recognition (ANPR) survey to collect flow data for the system. For closely associated junctions, collecting the ANPR data gives a robust origin to destination matrix with the entry and exit points defined.

The sites have various crossing locations and the pedestrian movement in the area has a significant impact on the junction’s operation. The crossings were included in the model coded with pedestrian flows from site surveys to give realistic pedestrian demand frequency.

For this small network the validation was performed using stopline counts for each of the signalled stoplines as well as comparison between measured and modelled journey times. An important part of the process was a demonstration of the model running so that the build up and dispersion of traffic could be assessed jointly by Siemens and DRDNI. With both the written evidence for the validation and the statistical comparison the model fitted the validation criteria and was passed as fit for use.

Linking to PC MOVA To assess the network for MOVA linking a comparison of the proportion of traffic making each movement (by origin and destination) was made to look at the difference in distribution for the AM and PM peaks.

It was clear that the main flows were different between the peaks and this analysis allowed the construction of the MOVA linking elements to be specific in design to each of the periods.

An experienced Siemens engineer assessed the scheme merits and prepared

the datasets and linking forms to link the Paramics model to PC MOVA. All of the pre-planning work is vital to setting up a successful MOVA site and a lot of the ‘offline’ work carried out in this stage of the modelling was directly transferable to the on-street implementation.

With the model linked to PC MOVA, the MOVA operation was validated against the modelled traffic flow. This ensured that MOVA was operating most efficiently in the model; all of the validation screens were accessible when using the link so that the engineer could view the messages and amend the validation.

Option testing As well as testing a MOVA scenario some network changes were also evaluated.

These included making changes to the movements allowed from some approach lanes and also changing the central layout of the junction. Both of these changes could be coded in Paramics to provide an immediate comparison between the schemes before any investment in on-site infrastructure.

The PC MOVA tool was again used to place these new layouts under adaptive control so the full benefit of any scheme could be recognised.

Results The Paramics model showed that implementation of MOVA would provide an immediately reactive system giving a more effective response to changing traffic profiles in the peak and achieving better management of the long queues currently building up under existing CLF plans.

The model also demonstrated where me and queue length savings can be made on the most congested arms, but also indicated where giving these

approaches more green time had an effect elsewhere in the network.

Favourable output from the model led to a full design and implementation package and the full upgrade of the junctions with Siemens ELV technology, Puffin crossing facilities and MOVA control.

Roads Service staff coordinated and supervised the civils construction work carried out by Gibson (Banbridge) Ltd and the installation of the traffic signal equipment by Siemens.

The implementation of the linked MOVA control was carried out by Siemens and overseen by Roads Service staff. This was immediately effective in coordinating traffic movements through the junctions.

This effectiveness was in part enabled by the prior construction of the Paramics model. Further minor modifications to the MOVA configuration were made in the days following implementation by Siemens with input from Roads Service.

The effect on traffic flows in Banbridge town centre has been marked, with most approaches being cleared within a single cycle as opposed to the ongoing queues that were evident before the upgrade took place.

Kevin Monaghan, Divisional Roads Manager for Southern Division welcomed the changes saying ‘the implementation of the linked MOVA control system by Siemens was carried out efficiently and has had a very beneficial effect on traffic flows in the area. Gibson (Banbridge) Ltd staff are also to be commended for professional manner in which they carried out the civils construction in a very constrained and busy site.’

Siemens, in association with Gibson (Banbridge) Ltd, worked in Banbridge, Northern Ireland, on behalf of DRDNI Craigavon (Roads Service, Southern Division)

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Opening up opportunities to benefit the individual Open data provides opportunities for exploration and creativity. Such innovation will open new doors in the public sector, and enable new private sector possibilities, says Keith Drew, Halcrow

When the data.gov.uk website launched in January 2010 I did not even notice, to be honest. A failure on my part as a data ‘geek’, I admit.

However, in April 2010, following a more trumpeted arrival (The Guardian’s ‘free our data’ campaign, for example), I was the proverbial kid in a sweet shop ordering as much data as my download facility could handle. ‘Free’ Ordnance Survey data had arrived and they were ‘giving away’ all the data I could ever want for the price of an internet click, not to mention free DVDs to boot.

From memory, I believe this data previously had a value of £0.25m ‘on the street’ for complete UK coverage – so it was a good start! I would have liked OS MasterMap Topography and ITN data as well but you can’t have everything…

With awareness of data.gov.uk now switched to the ‘on’ position, in August 2010 the Department for Transport landed on data.gov.uk, in the form of the publication of the National Public Transport Data Repository (NPTDR) – passenger transport data for all of Great Britain, all free and all available to use without restriction, whereas previously access was through and only for public sector agencies and/or projects.

As a network and accessibility planning specialist, through the OS and DfT open data releases I now had at my disposal all the data I needed to do my work for free (I could even use open source software if needed to).

To gauge use by other transport planners at Halcrow (all of whom have Geographical Information Systems experience), for this article I conducted a quick poll of open data use. The results showed that most (75 per cent) were aware of open data, particularly Ordnance Survey data), with 75 per cent of these people actively using the data in some guise. In the majority of cases most use was attributed to using OS imagery files

“With Ordnance Survey and NPTDR data, my aim has been to build a GIS tool that brings the two together, in the form of a multimodal network analyser tool called Solaris ”

(250,000 and StreetView rasters) as background figures in reports, typically overlaid with outputs from transport models.

My use has been slightly different and the remainder of this article describes what I have done over the last six months.

By way of background, prior to joining Halcrow in 2007 I spent six, formative, years at GMPTE (now Transport for Greater Manchester) observing a steady but rapid rise in the use and management of Geographical Information Systems (GIS) and data. As Ordnance Survey and

Census liaison, part of my role, getting data, was not difficult. Granted, someone in the organisation paid for this somewhere, most of the time, but for me it was still free and available to use.

Picture me as I ran through the green fields of Greater Manchester (maybe best not to, actually) – I could explore and see what was achievable. When I joined the private sector, however, I no longer had access to such data, or at least no one would pay me to explore the green, green grass anymore, but at least I had paid work to do.

Turning back to open data, what opportunities has it given me so far? Well, it has given me the chance to explore once more, at no cost – excluding my time – with no public sector client required. The green fields have returned, although maybe they should be considered more of a brownfield redevelopment due to the current economic climate.

How have I used the data made available? Or, to use one of those annoying phrases, how have I ‘added value’ to produce something more than what is being offered; and done so in a cost efficient manner.

With Ordnance Survey data (background images at many scales, postcode locations, road networks) and NPTDR data, my aim has been to build a GIS tool that brings the two together, in the form of a multi-modal network analyser tool called ‘Solaris’.

In the past I have spent many a day/week/month ‘free-hand’ plotting bus networks in GIS, cross-referencing with timetables for routes, never quite getting my mapped nodes to match up. What I needed was an automated tool that did this for me, for any part of Great Britain, and did so so neatly and quickly, and consistently to the road network – which became the initial successful aim of ‘Solaris’.

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At the cornerstone of ‘Solaris’ is an Excel/GIS tool, utilising Visual Basic and MapBasic programming scripts, that works by firstly manipulating the NPTDR data by arranging it into rows of origindestination rows (public transport node to public transport node). For the bus network, the tool maps the OD pairs against the quickest routes between the two points to create the mapped full network; for non-road modes of public transport a pre-drawn network is required, split by station.

The pertinent point to make here is that this was done with no prior VB/MapBasic programming experience on my part, so open data really was a catalyst to experimenting and this application of open data is possible for anyone to do.

The tool is hardly groundbreaking or a game changer to the transport planner but it does allow a network to be drawn fast and efficiently and, most importantly, gathers intelligence about change scenarios dictated through an Excel interface in a cost-effective manner.

Through the interface, routes can be quickly switched on and off, minimum frequency of service and time-periods set (a facility relevant with many transport authorities juggling subsidies to bus networks in the quest for for efficiency savings). Intelligence is gathered by weaving data in from a third open data

source, the humble postcode centre mapped against Census and deprivation data (was the Census of 2001 the first open data source placed on the internet from central government?).

A further aim of ‘Solaris’ involved the creation of additional GIS tools to understand public transport operators and how they interact temporally and spatially with each other and, potentially of more use and importance for my work, the creation of an accessibility planning application.

The image below is an example output from ‘Solaris’ and shows the bus routes running within the city centre of Manchester and the operators running those routes. The entire bus network for Greater Manchester was created in little under half a day (computer time), with the output shown and associated analysis being relatively instantaneous to complete.

The accessibility planning section of the tool has been developed to support our use of mainstream accessibility tools (AccessionTM for example) for projects, rather than replace them. In ‘Solaris’ the accessibility tool looks at one destination only but has functionality that: Builds pictures of travel times temporally by day; Allows the user to specify perception weightings (to walk and wait time, plus interchange penalties);

“the tool allows a network to be drawn fast and efficiently and, most importantly, gathers intelligence about change scenarios dictated through an Excel interface in a costeffective manner

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An example output from ‘Solaris’, showing the bus routes running within the city centre of Manchester and the operators running those routes. The entire bus network for Greater Manchester was created in little under half a day (computer time), with the output shown and associated analysis being relatively instantaneous to complete

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DATA & MODELLING

By restricting access to only direct journeys, or direct plus one interchange journeys, it gives a more realistic view on accessibility levels. Existing accessibility tools do not restrict levels of interchange. Overall, the accessibility tool within ‘Solaris’ could be considered less of a black box with the above considerations, albeit restricted to one destination. An example of this application is found is seen above: travel times to Leeds city centre in the weekday am peak period (travelling between 8am and 9am)

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Restricts calculated access time to

either direct or direct plus one interchange journeys only and; Creates, in GIS, direct or direct plus one interchange route networks, so that the user has information on how access is possible (including frequency of service).

Temporal accessibility allows the creation of accessibility maps for one destination over a 24-hour period (set at 15 minutes, 30 minutes or hourly timeperiods). The purpose of these maps is to build a picture for a full day (a practical use of this being hospital appointments, which could be set according to when is best to travel for the patient).

By allowing the user to set perception weightings, as per traditional transport models, it allows accessibility to take into consideration impediments to travel (excessive walk distance, wait times and interchange). Further refinement could be made using open data from the UK’s police forces on the perception of crime, for example (disclaimer: the merits of doing this are open to debate, but not one that the author is opening).

By restricting access to only direct journeys, or direct plus one interchange

journeys, it gives a more realistic view on accessibility levels. Existing accessibility tools do not restrict levels of interchange.

Overall, the accessibility tool within ‘Solaris’ could be considered less of a black box with the above considerations, albeit restricted to one destination.

An example of this application is found in the image above, which shows travel times to Leeds city centre in the weekday am peak period (travelling between 8am and 9am).

To conclude, open data has given me the chance to explore and innovate, which will in the future help ‘pay the bills’, hopefully. In the public sector and my core work, open data is not so significant to me as a contractor, as the data has always been there freely through contractor licenses, as project costs to the client will not change.

However, it is hoped that innovation, such as described here, using open data, will open new doors in the public sector.

Furthermore, it allows me now to work more in the private sector, whereas before prohibitive data charges for say postcode, road and background imagery data made my work (GIS and accessibility planning) too expensive, or at least ‘nice to have’, but not essential.

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Informing wider debate in an age of localism

The digital and data revolution is changing the relationship between designers, planners, elected representatives and communities involved in place and movement. Scenario testing tools and ‘games’, 3D visualisation systems, real-time data tracking and collaborative management tools are enabling public debate and discussion to come before, and not after, decision-making. By Peter Warman The digital and data revolution is having a big impact on the wide range of professionals – and communities – involved in place and movement.

Scenario testing tools and 'games', 3D visualisation, Building Information Modelling (BIM) systems, real time data tracking and 4D collaborative management systems are changing the relationship between designers, planners, elected representatives and the public. In a digital world, public debate and discussion can come before, and not after, decision-making.

A new interactive 3D visualisation developed by Parsons Brinckerhoff enables the public to virtually ‘drive’ across the proposed San FranciscoOakland Bay Bridge. Active participation in the form of a car driver simulator with on-screen touch controls for speed, steering (by tilting the screen) and braking is taking ‘public participation’ to a new level. These powerful tools will soon allow the public to actively participate in ‘visioning’ and possibly ‘voting’ on our futures.

Augmented reality (AR) applications are already on the way into our shops, enabling shoppers to ‘try on’ virtual clothes in front of a full-size high resolution TV screen. Viewed on smart phones or tablets, AR imposes an extra

layer of information (sound, video, graphics or GPS data) over an on-screen image of the real world.

When it comes to designing and planning transport projects for our urban and rural environments, interactive visualisation and AR are becoming professional tools that urban and transport planners will be encouraged to work with for both professional and public benefit. Smart transport systems, 3D images on in-car navigation systems, mobile phone ‘way-finding’, walking, cycling and public transport apps are already widely available. Increasingly, we expect a mix of real time information and ‘journey planning’ information combined with 3D images to augment our experience of the real world.

Visual analysis of travel patterns At an afternoon seminar of the ITS (UK) Public Transport Interest Group at the beginning of March, PhD Student Roger Beecham from City University London demonstrated how data and animation are being used to analyse use of the London bicycle hire scheme, linking docking sites and bike distribution at any given time. Transport Control Centres are beginning to use such systems – by capturing information from vehicle

“Interactive visualisation and AR are becoming professional tools that urban and transport planners will be encouraged to work with for both professional and public benefit

”

tracking systems, smartcard data, mobile phones and CCTV – to monitor travel patterns, provide asset management systems and track vehicular movements, creating rich evidence bases to inform future decision-making.

Understanding complexity Data of this kind enables designers to bring together virtual 3D simulation of the built environment with movement and crowd sourcing data. At Imagina (held each February in Monaco), I took the opportunity to see the many ways in which 3D visualisation and simulation technologies can be used. Clay Starr from RTKL explained the benefits of BIM:

(left) St Jean de Cornies: south of France. The images are extracted from the Bionatics interactive 3D model of the Hérault Region (7,000 km²) developed by the urban planning division to study and present scenarios leading to the reduction of urban sprawl around typical villages

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consistency across drawings and schedules, accurate 3D visualisation, enabling designers from various disciplines to work collaboratively in a 3D database, and scenario testing. ‘BIM allows us to express our concepts in three dimensions, giving clients a more accurate depiction of the project’s progression while providing us with a platform for greater integration among disciplines throughout all phases of development.’

Extending 3D to 7D Such approaches are becoming standard practice on a wide range of large construction projects, and the use of BIM will be mandatory on public projects by 2016. The discussion is moving on to envisage projects as 7D processes: the

fourth dimension is ‘time’ so a project can be visualised at each stage of its development; the fifth dimension is ‘cost’, so a bill of quantities and construction labour costs are incorporated; 6D is ‘asset management’ to determine how the building will be maintained when in use; and 7D examines a building’s lifetime sustainability and, possibly, its demolition when the time comes.

‘Technology and the cloud are making it easier to test and simulate virtually how buildings will perform within their environments over their lifetime,’ says Starr. Such approaches will soon be impacting on large scale development and major transport infrastructure investment, as wider applications across the urban development and transport planning sectors take shape.

Virtual models Several cities across Europe maintain an ongoing dialogue with their citizens using a 3D virtual model of their city: past, present and future. In France, national legislation has been passed to encourage the city authorities to provide below ground 3D mapping of main utilities.

A presentation by the City of Bolzano, Italy, explained a 10-year programme to improve communication with the 100,000-strong population using 3D virtual animation.

All ideas are included on the city’s 3D territory virtual model, which is linked with a GIS database, and the public is encouraged to share in city decisiontaking about their city through an online voting system.

As professionals, it is up to us to realise the immense potential available in the smart capture and use of the data that streams across our towns and cities, and to find ways to visualise and communicate data effectively In Bolzano, top left, the city is encouraging public participation in new ideas for future investment in urban development, infrastructure, mobility and tourism through virtual models Bottom left: several cities across Europe, for example Paris, France, maintain an ongoing dialogue with their citizens using a virtual models of their city Below: smart transit systems yield new data sources in Finland

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3D movies: making the case for change A partnership between SKM Colin Buchanan and Wagstaffs Design brings together data collection, quantitative analysis, modelling and visualisation to produce high-resolution 3D movies that support the business case for investment. By Simon Babes and Paul Oesten-Creasey

3D visualisation – as its name suggests – is a type of computer animation used for developing masterplan and concept designs, community consultation displays, presentations to approval authorities, or to accompany sales and marketing presentations.

Communication tool An excellent communication tool, it enables people to more easily understand technical scenarios, can be applied to ‘safety in design’ methodologies, and above all, is a visually exciting, valueadding way to convey information. And by showing attractive and informative visuals to community members, stakeholders, investors and project teams, it also becomes a valuable and costeffective tool in stakeholder engagement.

The technology can be used to bring pedestrian modelling to life in a limitless variety of scenarios, such as at sports stadiums, railway or bus stations, both from the customer’s perspective to represent delays or crowding and from the operator’s perspective to illustrate the impact of day-to -day operations.

About the authors: Simon Babes is Technical Director at SKM Colin Buchanan, and Paul Oesten-Creasey is Associate Director, Wagstaffs Design

DLR network visualisation

The Docklands Light Railway (DLR) opened in August 1987 to serve the burgeoning London Docklands area.The regeneration of Docklands has contributed to the substantial growth of the DLR – carrying more than 85 million passengers in 2011, and awith work and development proposals ongoing.

Conscious of such rapid growth, Wagstaffs Design and SKM Colin Buchanan were commissioned to develop a tool to create a virtual experience of the entire DLR network and the surrounding environment.

This allowed DLR to do a number of things: Identify the quantum and location of planned development within the DLR network catchment area, from an aerial view and a customer’s perspective Provide a possible means of assessing which planned developments may have an impact on the strength of radio signals used by DLR to operate the network and communicate with the vehicles. The ambitious project required vast amounts of data collection and handling. Also it had to be communicated in a way that was clear and engaging, as this was not just a tool to use in training and development, but also to generate support for future investment.

The model incorporates building information that is derived from the client’s land use database, a tool continually updated and improved as a collaborative effort between SKM Colin Buchanan and DLR. Together with DLR, Wagstaffs Design and SKM Colin Buchanan developed a user interface that runs on any standard computer allowing complete control over a virtual journey on the entire DLR network. The software includes a number of novel features that allow users to control the speed of the train while it makes its way around the network, interact with the environment with 360-degree viewing angles and turn surrounding buildings ‘on’ and ‘off’, including proposed buildings based on the GIS data.

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Bond Street: the need for extra capacity Wagstaffs Design and SKM Colin Buchanan were commissioned to develop a computer generated film for Bond Street Underground station (see images below) to highlight the need for the proposed capacity enhancement scheme.

The key objective was to deliver a comprehensive movie that communicated a consistent message to all stakeholders – that the impact of not funding the proposed capacity enhancement project was unacceptable, both from the customer’s perspective to represent delays or crowding, but also from the operator’s perspective, due to the potential negative impact on day to day train operations.

The team commenced the project by using London Underground’s LEGION model, software that simulates and analyses pedestrian movements in the facility.

The outputs, in the form of trajectories for individual customers, were adopted as

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inputs into a series of visualisations, which were then compiled into an easy to understand CG Animation.

LUL awarded full marks to the Wagstaffs Design and SKM Colin Buchanan team for the delivery of the project, confirming their high satisfaction in the work delivered by the team.

Sandra Weddell, Transport Modelling Manager, Transport for London, said that the work took outputs from detailed Legion pedestrian modelling to help accurately portray how increasing passenger numbers lead directly to increased delay and congestion in Bond Street station.

‘What was particularly insightful was the way the 3D outputs were produced into a concise visual narrative that was accessible to a very broad range of stakeholders,’ said Ms Weddell.

‘This enabled the same video to be used when presenting to many different groups about different a range of differing impacts of the project.’

This project was shortlisted at the 2012 London Transport Awards for Excellence in Technology category. As a tool, the marrying of quantitative analysis and 3D visualisation has considerably raised the bar in terms of expectations in the transport market, for clarity of communication when delivering modelling outputs. For non-transport professionals it has proved invaluable in explaining multifaceted data in a visual format, as opposed to complex graphs and charts. London Underground has also used the movie as an exemplar case study both internally and externally at conferences on a national scale.

A five-minute movie recently produced for London Underground Limited (LUL) to illustrate a proposed capacity enhancement scheme for Bond Street Underground Station was instrumental in making the case for the project

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Bluetooth tracking for surveys With traffic surveys remaining a key component of the planning and appraisal process, the introduction of Bluetooth tracking – developed primarily as an alternative to temporary automatic number plate recognition – has had a real impact on cutting costs says Nick O’Neil of Streetwise

How does it work?

The fundamental principle of Bluetooth tracking is straightforward – virtually every mobile phone, hands-free kit, in-car telephone preparation, PDA and laptop, and many Sat Nav and other devices, have a unique MAC (Media Access Control) address that, when enabled, can be detected by a Bluetooth recording device. Bluetooth MAC addresses are detected at the points of interest and then matched between sites to provide origin and destination data, and journey time data.

The sophisticated elements of the survey come in both the field set-up and the data processing to derive and match the required data. Specialist field calibration ensures accurate data capture and complex filtering algorithms analyse the captured MAC addresses to ensure that multiple devices detected simultaneously are treated as one.

This is essential to eliminate any potential bias from say a person or vehicle with several devices. Typically, capture rates are 30 per cent for traffic and 15 per cent for pedestrians, although this is expected to rise over the years in line with increased Bluetooth usage.

Big brother Whilst Bluetooth is certainly tracking of people’s movements, motorised or not, the technology is non-intrusive and anonymous to individuals. It’s a methodology developed to understand how people move around,

but without knowing who they are.

Unlike ANPR, a MAC address is nonpersonal. It’s a unique code used for devices to communicate exclusively between each other, and each MAC address is truncated and encrypted at source, adding further security and anonymity. The technology ticks all the data protection boxes.

Bluetooth and Zigbee are both short range devices using spread spectrum modulation techniques

In austere times, it has been vital to reduce the costs of transportation studies by making more use of existing data sets and developing methodologies that offer added value. However, traffic surveys remain a key component of the planning and appraisal process. Clients want more for their money, and results delivered quicker.

One development which has had a real impact on cutting costs for some types of traffic survey is Bluetooth tracking, developed primarily as an alternative to temporary automatic number plate recognition (ANPR) surveys, which are among the most expensive to deploy.

Deployment and applications A Bluetooth scanner is typically deployed in an elevated position to capture the desired detection area. The power and range of the scanner can be adjusted, so the detection footprint can range from a highway or reduced to focus on an escalator or shop front. Bluetooth scanners are self-contained and the equipment casing is compact and inconspicuous. As Bluetooth captures a sample of the flow, it is normal to have a supporting background count to factor up the Bluetooth data.

Bluetooth tracking is suitable for a wide range of transportation data collection exercises, including origin-destination studies, journey time surveys, and public transport user surveys.

To date, the need for a reliable alternative to ANPR for the collection of origindestination data has aroused most interest in Bluetooth technology. There are a number of reasons that Bluetooth has become a recognised, and in some quarters preferred, alternative to ANPR: timescale and trend analysis; reliability; cost; data accessibility and speed of reporting; health & safety.

The higher specification Bluetooth units report the data back, up to every minute if necessary. This improved granularity of data means that more accurate journey times can be reported in real time.

Significantly, a Bluetooth device may be carried by an individual from start to finish on the same journey, irrespective of transport mode, so Bluetooth technology can bridge the gap between traffic and pedestrian movement, and there are particular benefits for the study of public

transport interchanges. Reporting combined journey times also has applications for events and the retail sector.

Aside from origin-destination recording, Bluetooth tracking is ideally suited to journey time data collection, with careful deployment of monitoring devices serving as a viable alternative to either ANPR or floating vehicle/ moving observer methodologies. The massive benefit that is derived from Bluetooth is the ability to collect literally thousands of journey times per link as opposed to the relatively small number journeys that are commonly collected per survey period with the floating vehicle method.

The technology is also gaining a foothold as a means of recording pedestrian movements and routing, particularly in connection with public transport hub and interchange areas, but also for movements around and within stadia, shopping malls, and public open spaces. This data has traditionally been problematic to record, necessitating both extensive camera coverage and a significant post-survey processing exercise. Streetwise has undertaken a number of pedestrian tracking surveys using GIS (Geographical Information Systems) where surveyors track and spatially record a sample of specific routes taken around the study zone, also recording demographic information. This serves as an exact record of movement and activity, and this compliments the Bluetooth data from strategically located detectors. The spatial interrogation of both data sets in GIS then serves as a comprehensive data set for the

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study of pedestrian movement.

There is also potential for using the technology in tandem with other survey types. A widely recognised limitation to the effectiveness of roadside interview data is the inability to record mainline motorway data. The typical address to this problem is to survey on feeder sites, motorway ramps where possible. However, this is sometimes done ‘blind’ with no real knowledge of what proportion of traffic passing the target site originates from each selected feeder site. A pre-survey using Bluetooth recording would serve as a means by which to identify suitable and valuable survey sites. Given the high cost, directly for the survey and indirectly due to congestion, of roadside interview sites, any scope to reduce the number of sites to ensure that only relevant sites are selected would surely be of interest to the commissioning authority.

Furthermore, being able to ‘bolt on’ other detectors, at a specific location such as a car park, can assist with any specific stated preference aspect of a study. Being able to scale a study in this manner can add great value and partially answers questions normally only achieved by interview or questionnaire.

Suitability and classifications Of course, inevitably, there are pitfalls with the technology, and it will not be suitable for all studies. The major issue for most survey types is the inability to differentiate between different vehicle (or indeed non-vehicle) classifications. The recording unit and associated software has no way to identify whether a MAC code was from a device being carried in a car, van, goods vehicle, or even pedestrians pocket. It is possible, dependent on the route and availability of suitable mounting locations, to be able to time-synch a video camera with the Bluetooth unit to be able to classify MAC codes as the device is detected. However, the post-processing will lead to significant delay and the methodology will only work with relatively quiet, uncongested routes as the spread of the Bluetooth capture zone make it impossible to definitively identify where on the road the vehicle was picked up. In urban environments the class issue should not be so important as journey times will be relatively similar across classes, and setting time parameters can easily exclude pedestrians from the data set, unless the cordon is very small.

Transport Modelling Delivering the right solutions

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Having deployed Bluetooth on major studies in the UK and Ireland, the choice of equipment location and the setup and calibration process is critical to collect and indeed isolate the data of interest.

Significant benefits Whilst we recognise that the technology will not address the needs of every study, Bluetooth matching is here to stay as a technology because it offers some significant advantages over alternative survey types.

Firstly, as outlined in the introduction, Bluetooth matching for O-D surveys is usually cheaper per day of data collected than recording the same information using a number plate survey. The fewer number of units, the ease and safety with which they can be deployed, and the streamlined analysis processes ensure that this is a very cost effective method.

Secondly, this technology is usually far more time efficient than ANPR. Less resource on site typically means lead-in times will be shorter, but primarily the time saving is post-survey. For a long time the A in ANPR has been misunderstood as a process that can be conducted instantly by automatic means. This is almost never the case, as footage typically needs to be run through specialist software to achieve a ‘first pass’ match rate of rarely more than 80% (for a cordon study), with the remaining records being manually in-filled during an ntensive process. This is in stark contrast to a data set that can be scheduled to download immediately after, or even during the survey period, and then run for the required outputs. Whilst it would be unusual to happen in practice, there is the potential for no working time loss with data being presented the morning after the survey.

Thirdly, there is the issue of risk of data loss. Any large scale cordon survey

conducted by ANPR is at the significant risk of loss of footage. Since the replacement of VHS with digital recording by virtually all survey companies, there has been an increase in system failure. Footage loss of 10% has been typical within some recording systems, and though this has improved as more robust digital recording units have been introduced, loss of footage is nonetheless a major concern for a cordon survey where loss of a single site can invalidate an entire study of scores of cameras. This issue is largely avoided with Bluetooth, firstly because the recording units have less to do than a camera/ DVR system and therefore have less that can go wrong, secondly because the data can be checked live for consistency.

This issue of survey duration is another major benefit that is delivered by this technology. As well as being able to collect information on weekend movements and record habitual behaviour during the survey period, recording over multiple days minimises the risk of abortive surveys caused by extraneous factors such as untypical travel patterns caused by weather or accident/ incident within the study area.

There have been instances in the past where surveys in the five figure cost bracket which had to be entirely repeated at the client’s cost due to events causing an abandonment of the study. With a 7-day Bluetooth survey, this data would simply be set to null and ignored, as other days provide additional and data which effectively eliminate this risk.

Viable and robust Bluetooth for transport and pedestrian surveys has emerged as a viable and robust methodology, and has come of age in the past couple of years, and it is likely that it will represent an increasing share of the market for diverse survey requirements. In the field of transportation, Bluetooth is a cost effective evaluation tool for pre and post scheme evaluation. For pedestrian and cyclist tracking, the retail sector, and understanding the dynamics of crowd movement, innovation has enabled new doors to be opened.

It’s a learning curve for everyone, so skilled experience in it’s deployment and use is vital to realistically advise on clients needs and expectations, but more importantly, to advise if Bluetooth is the right tool for the job.

DATA & MODELLING

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A LUTI model with a difference The Leicester and Leicestershire Integrated Transport Model (LLITM) represents the most detailed land-use application that has been built to date by David Simmonds Consultancy in terms of both the number of different land-use types modelled, and the detailed level of zones within the modelled area

Both transport and urban planning require broad ranging consideration in their own right. The interaction of good accessibility provided by transport infrastructure facilitating development and resulting in travel demand and stress on transport networks, is the reason why each cannot be considered in isolation.

Responding to the Eddington and Stern reviews, the DfT has set challenges to tackle climate change, while focusing on those investments that deliver the greatest economic benefits. The need to consider the long-term vision, county-wide, and to plan for a successful future is at a different scale to the detailed impact assessment required to assess the sustainability of individual local developments and of transport schemes.

Planning for future land use and transport infrastructure is multifaceted.

There are tensions between development of strategy, monitoring delivery and the appraisal of individual developments and schemes. The Leicester and Leicestershire Integrated Transport Model (LLITM) was conceived by Leicestershire County Council to address these challenges by providing a consistent means to appraise land use and transport plans from county-wide strategy to individual schemes and developments.

This comprehensive vision is unique in the UK. It provides a framework both to develop the high level strategy and to monitor and shape the delivery while adopting efficiencies through consolidation of the diverse range of models that were previously developed and maintained for individual market towns and for Leicester.

Transport and land-use planning is becoming increasingly complex and, coupled with anticipated pressures on the transport system from proposed significant growth in Leicester and Leicestershire, the authorities foresaw the need for a state-ofthe art analytical tool. Such a tool must be able to provide a wide breadth of evidence necessary making the right investment and land-use choices.

Planning inspectors and Government are demanding more and better analysis of proposals and objections, as appropriate.

Poorly founded proposals are increasingly likely to get rejected. Transport impacts of development are increasingly influential in

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â&#x20AC;&#x153;Through our experience

of dealing with an ecotown proposal, we learned the value of properly integrated models. We chose to invest in the LLITM so that we will be in a strong position to understand the challenges posed by significant growth over the coming yearâ&#x20AC;?

Ian Drummond, Assistant Director of Transportation at Leicestershire County Council

shaping the forward vision for transport in Leicestershire and, in the absence of a regional plan and transport strategy, the Local Development Documents produced by the district councils must allocate land for growth and development.

The now defunct Regional Plan expected Leicestershire and Leicester City to accommodate over 97,000 extra houses over the period up until 2026, together with associated employment and services. The District Councils, as part of their core strategies, are still planning for a substantial level of growth â&#x20AC;&#x201C; which will stifle the county economy if not properly analysed, understood and catered for.

Land use model The LLITM is a fully integrated land use and transport model, drawing together: a detailed public transport assignment model; a detailed highway assignment model;

a tour based demand model, including

parking;

a spatially detailed land use model; and

integrated environmental appraisal.

The key model components and interactions are shown in the figure on page 37.

LLITM features both detailed spatial representation throughout, together with a high degree of segmentation of travel purposes and of travellers. Each of the constituent models has been developed and calibrated to comply with or exceed UK best practice. The rich and comprehensive detail supports the broad range of objectives. The model is suitable for the appraisal of modest developments and associated transport mitigation, as well as assisting the development of countywide land use and transport strategies.

In addition to the detailed spatial representation that is carried through from land use to network models, particular innovative features of LLITM include: integration of the detailed representation of household and person categories in the land use model to develop and forecast demand by income segment in the transport models; the methods to achieve consistency between the tiered network and demand models; and integration of a comprehensive environmental appraisal tool, EASE. The model is based on a rich assembly of data drawn from roadside interviews, public transport surveys, a household survey and planning data. Together these provide a picture of how, when and why travel is made today. This, taken together with a description of the highway and public transport networks, is used to establish travel conditions.

The model has demographic and economic scenarios that are consistent with the NTEM v6.2 forecasts. However the DELTA functionality allows the levels of growth to vary from this forecast depending upon changes in transport and land use policy. The land use model forecasts change in single-year steps. Commencing in the base year of 2008, it calculates the annual change over the period to 2031.The

DATA & MODELLING

transport model is run every five years. In these years information on the distribution of households, car ownership, population and employment is passed from the land use model to the transport model whilst the transport model passes generalised costs to the transport model.

Transport model The transport model was founded on data sourced from some 140 roadside interview sites across the county, public transport boarding surveys undertaken in central Loughborough, and the seven market towns, together with a household survey representative of the Leicestershire population.

Tour-based trip matrices were developed from these data sources, together with national data sources, using best practice to synthesise unobserved movements and walk and cycle travel. Particular care was taken to integrate the household categories represented in the land use model, in addition to considering different trip length distributions, to segment demand by income and car ownership levels. Care was also taken to maintain consistent use of the demand data throughout the demand and supply models. The incorporation of rich segmentation of demand provides the basis both to represent a broad range of price related potential transport interventions, and to appraise the impacts of interventions on different types of traveller.

A detailed 973-zone zoning system was adopted, providing the basis to represent

S upply Model (B as e) 2. Base Networks

1. Base Demand

4. Base Costs

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“It is critical that the

County Council (and Leicester City Council), as highway and transport authorities, are able to offer evidence-based analysis to local planners, inspectors and central Government on where best to locate growth and how transport investment should be directed to support it ”

zones were included to allow for more precise representation of developments.

The transport demand model was developed using EMME software by AECOM, to represent demand choices (frequency, macro-time period, mode, destination, parking location and type (including park & ride).

The model integration system was also implemented by AECOM. This drew upon the DfT national trip end software interface with the DELTA land use forecasts, and with the public transport assignment; and highway assignment models. Providing also an interface in terms of highway congestion on bus speeds.

The performance of the models was demonstrated first through validation against observed data and demand model elasticities. In addition demonstration tests were undertaken assessing the performance of the model against illustrative interventions ranging from demand management to improved highway and improved public transport facilities.

EASE

the highway and public transport networks across the county. The fine granularity allows identification and consideration of specific issues in individual market towns across the county and in Leicester. It also allows for the representation of the impacts of specific development proposals, although a number of ‘development’ or floating

Demand Model

3. Base Assignments

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Direct outputs from the LLITM land use and transport models provide the basis to understand the effects of changes over time and of interventions on business and residential development, and on travel demand, mode shares and intensity of use of specific roads and services.

The EASE tool integrates procedures to estimate vehicular emissions, and links this with forecasts of population density. This

Demand/S upply Interface

13. Future Networks

12. Ref erence Demand

16. Choice Models •Frequency •Mode •Time •Destination •Parking

15. Travel Costs

17. Convergence?

18. Travel Demand

14. Assignments

CUBE Voyager PT model Simplified EMME highway model

L and-Us e Model 5. Accessibility Calculations 6. Floorspace Changes 7. Household Changes 8. Economic/Employment Changes 9. s ee below 10. Employment Status 11. s ee below 9. Car Availability

S upply Model (F uture)

Demand/S upply Iterations

Outputs 19. Scheme Demand 20. Assignment

21. Assigned Networks

11. Productions & Attractions 22. Scheme Costs

23. E AS E- E xternal Apprais al P ackage

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DATA & MODELLING provides direct means to assess the impacts of interventions on greenhouse gas emissions, on air quality and on noise.

Forecasting draws together assumptions about future economic growth and the cost of fuel and fares, together with the envisaged allocation of land for development and proposed transport schemes, to forecast how the patterns of land use and transport demands will evolve over time. In turn, the influences of changing travel conditions (e.g. highway congestion) are represented in the forecasts.

Initial application of the model has started with the assessment of current land use and transport plans to develop an improved understanding of their implications. The initial forecasts are: for population and employment growth respectively of 24% and 12% across the county by 2031; for traffic forecast to increase by 26% over the same period, in part, reflecting DfT assumptions that car costs will reduce over time with increasing vehicle fuel efficiency, although the model forecasts also reflect proposed initiatives to promote more sustainable travel; and since public transport fares are assumed to increase in real terms there is a forecast mode shift to car, particularly from public transport, with public transport trips forecast to increase by 16%, which is lower than the forecast population increase.

The consequences of these forecast increases in demand are for highway speeds to decline, on average across the county and carbon emissions to increase as the forecast growth in traffic exceeds the assumed increase in car fuel efficiency.

Serving planning needs The model was formally launched on 11 May 2011, following completion of its development.

A framework was established of suitably qualified consultants with access to the dedicated computers in the County Council offices to apply the model. Over the past four months the model has been applied for 10 projects ranging from appraising local developments, through considering market town transport strategies to reviewing and refining the county’s spatial development strategy.

Currently the forecasts are being considered and are supporting the development of targets against which the delivery of the local plan can be monitored.

All major transport investment decisions must be made on the basis of an evidencebased understanding of the issues, the likely impact of the investment and its value for money. Central Government, which is usually the arbiter of major transport investment decisions, is increasingly insistent on the use of high quality analytical tools. The LLITM has been developed to be compliant with the Government’s WebTAG guidance.

Since its launch on the 11th of May 2011, demand for the use of the LLITM has exceeded expectations. The model has been used to support our major scheme bid for the Loughborough Town Centre scheme which is an £18.82m scheme designed to boost economic development and reduce congestion.

It has been used successfully to support the Market Harborough Core Strategy process from consultation to successful EIP and is being used for core strategies in nearly all the 7 districts of Leicestershire and a wide range of sustainable urban extensions for housing, employment, education and health.

The LLITM is also being used to provide evidence to support the deliverability of smarter choices interventions to underpin Leicestershire’s bid for the Local Sustainable Transport Fund (LSTF) and by local universities to bid for research funding in the areas of transport and the environment.

(from top) Changes in population density 2008-2026; changes in highway delay 2008-2026, AM peak; changes in highway noise and population ‘annoyed’ by noise 20082026, AM peak

The initial applications have demonstrated the performance of the model system and are evidence that the investment made is justified and will be rewarded through more consistent and better informed planning over the forthcoming years. Given the current financial pressures the ability to plan for best value is particularly important.

Authors: Sonny Tolofari, Leicestershire County Council; Paul Hanson, AECOM; Andy Dobson, David Simmonds Consultancy

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