Integration of Different Mobility Behaviors and Intermodal Trips in MATSim

Johannes Müller,Christian Rudloff,Markus Straub,Gerald Richter

doi:10.3390/su14010428

Johannes Müller, Christian Rudloff + Show 2 more

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https://doi.org/10.3390/su14010428

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Journal: Sustainability	Publication Date: Dec 31, 2021
Citations: 14	License type: CC BY 4.0

Affiliation: Austrian Institute of Technology

Abstract

MATSim is an open-source simulation framework for mesoscopic traffic simulations that has gained popularity in recent years. In this paper, we present a MATSim model for the city of Vienna, with a particular emphasis on the intermodal routing framework used to create agent trips, and the development of a utility function to specify different agents’ mode preferences. To create agent activity chains, we use mobility diaries from the national transportation survey in Austria and disaggregate the available geospatial information to best fit the reported travel times. The novelty of the intermodal framework is the ability to create trips that do not consist of only one mode of transportation, but to also include bicycle, car, and demand-responsive transport (e.g., cab, car sharing) trips in combination with public transportation. To represent the different mobility behaviors of agents, we divide the population into groups and assign them different utility functions for transportation modes according to their socio-demographic characteristics. After presenting the validation of the model, we discuss ways to improve the model.

Highlights

Agent-based simulations have been developed as a popular way of carrying out microscopic simulations
We present the routing framework Ariadne, which is used in performing the population synthesis and running the MATSim scenarios
The value of travel time saving (VTTS) is equal to value of leisure (VoL) minus the direct utility associated with time spent traveling

Summary

Introduction

Agent-based simulations have been developed as a popular way of carrying out microscopic simulations. For the activity-based model, the authors used a hierarchy of logit and nested logit models to determine the purpose, time of day, destination, and mode of the main trip. These trips were used as agent schedules for the MATSim simulation in which the routing of the trips took place. Another well-known example of creating a MATSim model is the open-source model for Berlin by Ziemke et al [4].

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