Microsimulation of travel flows aims to assess the effect of decisions taken by travelers based on personal preferences, time-of-day, properties of the infrastructure and expected or perceived travel flows. Route choice represents a particular class of such decisions. Route choice prediction is an essential component of microsimulators. Specification of choice models and estimation of the corresponding parameters based on observations are required in the preparatory stage. Route choice sets need to be established for sampling in the simulation stage. This paper is part of a research project aiming to investigate how route complexity can be integrated in the choice process modeling. In particular routes for bikers collected by GPS tracking in the Dutch FietsTelWeek project in 2016 are analyzed. The data exploration stage and the research project outline are covered. Properties of the publicly available fietstelweek2016 dataset used for model training are investigated in order to assess their effect on prediction results. In order to achieve the project goal, the research project structure is briefly discussed. It is based on the observation that the number of routes recorded for each OD-pair is too small to observe a frequency distribution for complexity. Hence, complexity data are collected for sub-networks that are similar with respect to particular graph properties.

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Procedia Computer Science
Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands

Knapen, L, Koch, T. H. A, & Dugundji, E.R. (2019). Bicyclist route choice: Data exploration and research project outline. In 10th International Conference on Ambient Systems, Networks and Technologies (pp. 401–408). doi:10.1016/j.procs.2019.04.055