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Complexity and Spatial Networks pp 167–186Cite as

Effects of a Simple Mode Choice Model in a Large-Scale Agent-Based Transport Simulation

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Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

The traditional transportation planning forecasting process is the four-step process, consisting of the following four steps (for example, Ortúzar and Willumsen 1995):1. Trip generation, where sources and sinks of travel are computed 2. Destination choice, where sources and sinks are connected to trips. This results in the so-called origin–destination (OD) matrix 3. Mode choice, where the trips are differentiated by mode 4. Assignment, where routes are found for the trips, taking into account that much-used streets become slower (“congested assignment”).

It has been clear for quite some time now that this approach is at odds with anything that is time dependent. At best, separate runs of the four step process are made for, say, morning peak, mid-day, evening peak, and night. Within the periods, everything is “static” (or steady-state), in the sense flow rates are constant throughout the periods.

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Notes

  1. 1.

    This “consequence” is actually the motivation for the specific mathematical form of the activity performance utility contribution. The reason for this motivation is not relevant to this chapter, but is described in Charypar and Nagel (2005).

  2. 2.

    The algorithm to construct the trip durations of the non-car mode was later modified to take exactly twice as long as the car mode at free speed. This explains differences between this chapter and other publications on the same subject. Eventually, these estimates need to be replaced by real-world data.

  3. 3.

    See http://www.openstreetmap.org.

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Acknowledgments

This work was funded in part by the Volvo Research and Educational Foundations within the research project “Environmentally oriented Road Pricing for Livable Cities”, and funded in part by the German ministry for research and education (BMBF) within the research project “adaptive traffic control” (ADVEST).

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  1. Transport Systems Planning and Transport Telematics, Technical University Berlin, Berlin, Germany

    Dominik Grether, Yu Chen, Marcel Rieser & Kai Nagel

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  1. Dominik Grether
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  1. Dipto. Scienze Economiche, Università di Bologna, Piazza Scaravilli 2, Bologna, 40126, Italy

    Aura Reggiani

  2. Dept. Spatial Economics, Free University, De Boelelaan 1105, Amsterdam, 1081 HV, Netherlands

    Peter Nijkamp

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Grether, D., Chen, Y., Rieser, M., Nagel, K. (2009). Effects of a Simple Mode Choice Model in a Large-Scale Agent-Based Transport Simulation. In: Reggiani, A., Nijkamp, P. (eds) Complexity and Spatial Networks. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01554-0_13

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