Calibrating the Wiedemann 99 Car-Following Model for Bicycle Traffic

Heather Kaths, Andreas Keler and Klaus Bogenberger
Additional contact information
Heather Kaths: Chair of Traffic Engineering and Control, TUM Department of Civil, Geo and Environmental Engineering, Technical University of Munich (TUM), 80333 Munich, Germany
Andreas Keler: Chair of Traffic Engineering and Control, TUM Department of Civil, Geo and Environmental Engineering, Technical University of Munich (TUM), 80333 Munich, Germany
Klaus Bogenberger: Chair of Traffic Engineering and Control, TUM Department of Civil, Geo and Environmental Engineering, Technical University of Munich (TUM), 80333 Munich, Germany

Sustainability, 2021, vol. 13, issue 6, 1-12

Abstract: Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic simulations by adjusting and calibrating behavior models developed for motor vehicle traffic. However, very little work has been carried out to examine the following behavior of bicyclists, calibrate following models to fit this observed behavior, and determine the validity of these calibrated models. In this paper, microscopic trajectory data collected in a bicycle simulator study are used to estimate the following parameters of the psycho-physical Wiedemann 99 car-following model implemented in PTV Vissim. The Wiedemann 99 model is selected due to the larger number of assessable parameters and the greater possibility to calibrate the model to fit observed behavior. The calibrated model is validated using the indicator average queue dissipation time at a traffic light on the facilities ranging in width between 1.5 m to 2.5 m. Results show that the parameter set derived from the microscopic trajectory data creates more realistic simulated bicycle traffic than a suggested parameter set. However, it was not possible to achieve the large variation in average queue dissipation times that was observed in the field with either of the tested parameter sets.

Keywords: microscopic simulation; bicycle traffic; bicycle simulator; car-following model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/6/3487/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/6/3487/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:6:p:3487-:d:521589

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().