Pairing discrete mode choice models and agent-based transport simulation with MATSim


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Date

2019-01

Publication Type

Conference Paper

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yes

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Abstract

As travellers are faced with an increasing portfolio of transportation options, researchers are similarly faced with increasing complexity of modelling efforts to study people’s choices and behaviour. While discrete-choice models and in particular mode-choice models are widely used to study how people react to specific changes in the system, little published research exist that analyses the possibilities and pitfalls of pairing mode-choice models with the traffic simulation inside of an iterative process. The work presented here describes a structured framework for using discrete choice models along with microsimulation. While the outcomes are based on the MATSim framework, they can be generalised. The obtained results show that the combination of a mode-choice model with MATSim is a promising approach to set up a feedback-enabled transport simulation. Given well-designed constraints on top of the choice model, a good fit with the reference data is achieved. While the modeller loses some of the freedom he or she has within the plan modelling in MATSim, gains in computation time and a reduced effort for calibration are achieved. The authors find that a tour-based model formulation is to be preferred over a trip-based one because by construction more consistent travel decisions are made. While a trip-based model could probably be calibrated to yield a good fit with MATSim, the tour-based model bears the potential of not having to perform a lot of calibration work when setting up the simulation.

Publication status

published

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Book title

2019 TRB Annual Meeting Online

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Pages / Article No.

Publisher

Transportation Research Board

Event

98th Annual Meeting of the Transportation Research Board (TRB 2019)

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Organisational unit

03521 - Axhausen, Kay W. (emeritus) / Axhausen, Kay W. (emeritus) check_circle
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG

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