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Poster Paper Proc. of Int. Conf. on Recent Trends in Transportation, Environmental and Civil Engineering 2011

Estimation of Transit Travel Demand in Delhi Metro: A comparison of the travel trips in 2006 and 2021 Nikita Rathi1 and Kartik Goel2 1

Department of Civil Engineering, IIT, Delhi, India Email: nikitarathi@gmail.com 2 Department of Civil Engineering, IIT, Delhi, India Email: kartikgoel.iitd@gmail.com that trip generation is thought of as a function of the social and economic attributes of households. Trip distribution, also called destination choice or zonal interchange analysis, is the second component in the four-step transportation forecasting model. This step matches trip maker’s origins and destinations to develop a “trip table” a matrix that displays the number of trips going from each origin to each destination (O-D Matrix). Historically, this component has been the least developed component of the transportation planning model. Mode choice analysis is the third step in the fourstep transportation forecasting model. Trip distribution’s zonal interchange analysis yields a set of origin destination tables which tells where the trips will be made. Mode choice analysis allows the modeler to determine what mode of transport will be used, and what modal share results and computes the proportion of trips between each origin and destination that use a particular transportation mode. Finally step is the trip assignment which is the process of allocating given set of trip interchanges to the specified transportation system is usually referred to as traffic assignment. The fundamental aim of the traffic assignment process is to reproduce on the transportation system, the pattern of vehicular movements which would be observed when the travel demand represented by the trip matrix, or matrices, to be assigned is satisfied. Assignment is done on the basis of minimum generalized cost of travel between each pair of zones. This generalized cost is a linear combination of the link journey time and the link distance + fixed costs such as parking or tolls etc. Transportation demand modelling is a data-intensive process. It requires a huge amount of information on traffic network data, land use data; population density data to estimate traffic demand and implement the four-step model. Traffic demand software, like EMME/3, has a powerful ability to automate the four-step model for traffic analysis. An algorithm is formed for transit passenger OD estimation. The user equilibrium assignment is based on Wardrop’s first principle, which states that no driver can unilaterally reduce his/her travel costs by shifting to another route. If it is assumed that drivers have perfect knowledge about travel costs on a network and choose the best route according to Wardrop’s first principle, this behavioural assumption leads to deterministic user equilibrium. EMME/3 uses the user equilibrium model to estimate the trip distribution i.e the standard transit assignment offered in EMME/2, which is based on optimal strategies, does not consider congestion effects due to limited vehicle capacity. Estimation of travel trips using EMME/3 Transportation Planning Software

Abstract - Travel forecasting is the process of estimating the number of vehicles or travellers that will use a specific transportation facility in the future. This paper aims to forecast the total transit trips in the Delhi Metro for the year 2021 and to compare them with the travel trips in the year 2006. Firstly a network of the Delhi city was created on EMME/ 3 Transportation Planning Software and then the travel trips for 2006 and 2021 were calculated. The number of trips for various continuation modes like walk-metro, bus-rickshawmetro, walk-bus-metro, rickshaw-metro and car/2_wheelermetro for all the 8 lines of the Delhi Metro was separately found. Finally the mode distribution access and egress trips for 2006 and 2021 were compared for analysis. Keywords Travel-forecasting of Delhi metro, mode distribution of access and egress trips, EMME/3 transportation modelling software, seating probability in Delhi metro, transit assignment.

I. INTRODUCTION A travel forecast estimates, for instance, the number of vehicles on a planned freeway or bridge, the ridership on a railway line, the number of passengers patronizing an airport, or the number of ships calling on a seaport. It begins with the collection of data on current traffic and together with data on population, employment, trip rates, travels costs, etc., traffic data are used to develop a traffic demand model. Feeding data on future population, employment, etc. into the model results in output for future traffic, typically estimated for each segment of the transportation infrastructure in question, e.g., each roadway segment or each railway station. This project includes the detailed study of transport forecasting and it describes how the standard version of the EMME/3 Transportation Planning Software can be used to solve the assignment model and thus estimate the travel trips for the year 2021 so as to suggest the steps that should be undertaken by the government to manage and control the scenario in 2021. Also the above mentioned comparison of the trips between 2006 and 2021 has been done for each type of mode distribution so as to identify the most important areas of improvement. II. LITERATURE REVIEW Transportation forecasting is done by the conventional 4-step model which is explained as follows. Trip generation is the first step in the conventional four-step transportation forecasting process. It predicts the number of trips originating in or destined for a particular traffic analysis zone. In the main trip generation analysis is focused on residences, and © 2011 ACEE DOI: 02.TECE.2011.01.16

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