New routes around urban congestion Traffic congestion is a daily experience for many people, which often leads to high levels of pollution in urban centres. Researchers in the MAGnUM project are developing multimodal traffic models, which could underpin more effective and environmentally-friendly transport management strategies, as Professor Ludovic Leclercq explains. Many cities face
significant challenges around traffic congestion, and policy-makers are grappling with the task of ensuring that large numbers of people can get in and out of urban centres as quickly and efficiently as possible, while also minimising pollution. As the Principal Investigator of the MAGnUM project, Professor Ludovic Leclercq aims to make a significant contribution in this respect. “We are trying to improve the functioning of urban transportation systems,” he outlines. This is primarily about the management of existing mobility, with researchers taking different modes of transport into account to develop traffic models. “We initially aimed to develop models related to the management of journeys, rather than looking at each mode of transport specifically or trying to manage the flow,” explains Professor Leclercq. “That means you have to consider all the means of transport at once, and the connections between those means of transport. Such models require a deep integration of mathematical, computer and behavioural sciences.”
Simulation game A commuter making their way into a city for work typically has a choice between the car or relying on public transport for example. One key priority in the project is to better understand how people make these types of decisions around urban transport. “You have at least three main decisions to make when you travel – you have to choose your mode of transportation, your route through the city, and your departure time,” says Professor Leclercq. Researchers have designed a simulation game to gain deeper insights into how these decisions are made. “The simulation environment is essentially the city of Lyon in France. People play a game at the same time on different computers, where they see a map of the city and receive assignments where they have to make journeys across the city, from a point of origin to a specific destination,” continues Professor Leclercq. “The players in the game have to choose the route they are going to take and when they want to start travelling.”
These journeys vary widely in terms of distance as well as in other factors, such as proximity to the ring road and the availability of public transport. Participants in the simulation can choose their means of travel, whether it be car or public transport, which will affect the level of congestion on the transport network. “As in real life, the choices of other users will affect the rest of the transportation network. So if you decide to take the car you will see more congestion and the travel time will increase,” points out Professor Leclercq. This kind of information is commonly available to travellers on the move, which is reflected in Professor Leclercq’s simulation. “People can change their decision based on the traffic information that we broadcast to them,” he says. “Travel time information is an important influence on people’s transport decisions, but we have found it’s not the only consideration – some people may choose a less direct route to avoid traffic signals for example.”
Simulation Game interfaces and outputs for a route choice experiment.
Reversoir-based large-scale dynamic traffic simulation – Lyon Metropolis.
Mobility patterns at city scale This is an important insight in terms of the management of transport networks, where the right balance needs to be struck between user equilibrium and the system optimum. In the vast majority of European cities individual people are free to make their own choices on what form of transport to use, and so tend to prioritise their own interests when making decisions on transport. “The main factor when making this decision is usually the travel time,” says Professor Leclercq. While information on the fastest route for a given journey is often freely available, if sufficiently
The choices of other users will affect the rest of the transportation network. So if you decide to take the car you will see more congestion and the travel time will increase. large numbers of people choose to use that route then this will inevitably affect the overall functioning of the system. “If a lot of people go on the same route at the same time then the travel time will increase and then you will see that some people start to use alternatives,” explains Professor Leclercq. “This is not the most efficient way to manage the transportation system.” The ideal scenario in terms of the overall functioning of a transport system would be to achieve a collective optimum, which would involve identifying travellers that, by using
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alternatives routes at busy times with maybe longer journeys, would significantly improve the global transportation system. If some people can be persuaded to avoid the most congested routes then this will help the system function effectively, an important dimension of Professor Leclercq’s research. “The question is, can we identify the 10 or 20 percent of trips that are really having the biggest impact on the system overall?” he asks. Researchers are developing methods to identify these groups of people from within the wider population. “Everyone needs to travel and we’re not trying to force people to change their plans. What we
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want to see is who among the population, by maybe changing their journey in some way, would help the system overall,” continues Professor Leclercq. A parallel can be drawn here with medicine. In the same way as medical researchers aim to develop treatments that target the source of a problem rather than the whole body, Professor Leclercq and his colleagues are developing targeted techniques to improve network efficiency and mitigate pollution. “From that point we can then look to notify those users and so improve the overall
management of a system. However, at this stage we are focussing more on developing the methods, using the advanced modelling frameworks we set up during the early years of the project,” he says.
Traffic management strategies This research could both inform the development of traffic management strategies and provide a basis to evaluate their effectiveness. Traffic signals at intersections to reduce or slow the traffic that enters a particular region are a central part of largescale management strategies based on cordon control. “This approach helps to maintain a certain level of service,” explains Professor Leclercq. This is known to work effectively in terms of improving traffic flow. Now Professor Leclercq and his colleagues in the project are looking to apply it to buses, as dedicated bus lanes do not always represent an efficient use of space. “If you don’t have a very high flow of buses then this part of the road may not be used at full capacity,” he points out. “Our idea is to have a cordon of signalled intersections along major bus routes, and essentially to limit the inflow into a region. This guarantees high commercial speed for buses while being more flexible for other vehicles.” A similar principle is being applied in the project’s work on dynamic perimeter control strategies to protecting a given area like the central business district (CBD). The static and economic counterpart of such a strategy is already applied for example in London and
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MAGnUM A Multiscale and Multimodal Traffic Modelling Approach for Sustainable Management of Urban Mobility
Project Objectives
T he MAGnUM project aims to: (i) create a consistent set of interrelated dynamic and multimodal traffic models able to capture driver behaviours at the different urban scales. (ii) apply this variety of models to design efficient and green traffic management strategies.
Project Funding
This study has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 646592 – MAGnUM project)
Contact Details
Project Coordinator, Professor Ludovic Leclercq Université de Lyon, IFSTTAR / ENTPE, LICIT T: +33(0) 04 72 04 77 16 E: ludovic.leclercq@ifsttar.fr W: http://magnum.ifsttar.fr W: https://www.sciencesquared.eu/ network/researcher/ludovic.leclercq Professor Ludovic Leclercq
Professor Ludovic Leclercq is deputy director of the LICIT laboratory at IFSTTAR (The French Institute of Science and Technology devoted to Transport, Planning and Networks), where he works as the head of a research group focused on traffic modeling and analysis. His main research interests are multiscale and multimodal dynamic traffic modeling and the related environmental externalities. IFSTTAR will become University Gustave Eiffel on 1st January, 2020.
Network travel time improvements by banning movements at intersections for certain demand levels - Lyon 6th network.
well-known as congestion charge. The idea here is that a defined area is protected in order to improve traffic congestion and reduce emissions. However, classical implementations mainly focus on the area only leading the vehicles and the pollution being shifted elsewhere in the suburbs. “We see that this works very effectively inside the region, but essentially all the emissions may be moved elsewhere,” explains Professor Leclercq. This is a large part of the motivation behind Professor Leclercq’s work in designing a new traffic management scheme. “We are trying to balance the total emissions in a region by controlling entry into the CBD in a way that is good for both that area as well as the areas outside it,” he says. A number of other strategies to improve the efficiency of urban transport systems and reduce emissions have been proposed, such as encouraging ride-sharing. “Some studies have suggested that encouraging ride-sharing will lead to a dramatic reduction in the number of cars in a city, and a much better and more efficient transport system,” outlines Professor Leclercq. However, the project’s models suggest that while this may lead to a reduction in the number of vehicles on the road, this will not necessarily have a big impact on congestion. “There will be less cars parked in the city but there will be almost no gain in terms of congestion, and if you have
no gain in terms of congestion you will have no gain in terms of emissions,” points out Professor Leclercq. The project’s analysis of mobility patterns and their work in developing methods to identify the biggest contributors to overall congestion will also inform the design of new traffic management strategies as innovative technologies enter the transport sector. With autonomous vehicles set to come onto the roads at some point, Professor Leclercq believes that in future urban routing could be more prescriptive, based on centralized or decentralized guidance provided to vehicles by road operators. “This could help us to better distribute traffic over a city’s network,” he says. “Another option is to modify mobility demand patterns by changing departure times or mode of transportation, using pricing or incentive schemes.” The wider aim in this research is to design new tools and traffic management strategies, which could eventually be applied in cities to alleviate congestion problems. Beyond the term of the MAGnUM project, Professor Leclercq plans to work actively with transport authorities to conduct field experiments, although at this stage the priority is developing the models. “In terms of the models we are quite well advanced, and now we starting to focus more on the development of innovative traffic management strategies,” he says.
Results of perimeter control of region 3 in total network travel time - Lyon North network.
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