Simulating cyclist behaviour

Simulating cyclist behaviour: An examination of what we know about this subject and how we should go further

Veraart, Marijn (TU Delft Architecture and the Built Environment)

Annema, J.A. (mentor)
Farah, H. (mentor)

Delft University of Technology
Wageningen University & Research
Amsterdam Institute for Advanced Metropolitan Solutions (AMS)

Metropolitan Analysis, Design and Engineering (MADE)

2024-02-16

Cycling as a mode of transport is getting increasingly more attention from academics and governments around the world. It improves the physical and mental well being of citizens, it is efficient in terms of space and it provides economic benefits. However, traffic engineers and urban planners of these cities currently lack the means to quantitatively test their bicycle infrastructure designs. Simulation models have become an important tool for the transport planner as it is cheap and effective. But simulation models of cyclist behaviour are an understudied subject.

This is not only an issue for cities that attempt to transform there mobility landscape to a more bicycle-friendly one, but also for established cycling cities that face new challenges because of the introduction of new vehicle types (e.g., e-bike, e-step) and new mobility business models (e.g., shared mobility, flash delivery). The academic world is also affected by the fact that cyclist simulation is understudied. The literature review of this thesis reveals that the academic landscape on this subject is foggy and unclear. The most popular model in academia is the Social Force Model (SFM). However, just the SFM leads to unsatisfactory behaviour, as is confirmed in the case study of this thesis. Thus, the academics propose a hybrid model. Herein, the SFM is constrained by additional rules, regimes or decision making processes. However, these propositions are tailored to cycling in a specific context and they are created in unmentioned software, using unmentioned programming languages. This hampers the possibility to replicate and verify their study.

The primary conclusion is that academics and simulation software developers should work towards a standardised behavioural model for cyclists, similar to the SFM for pedestrians and the car-following model for motorised traffic. An example of a leading principle for cycling behaviour could be a model where cyclists move along predetermined trajectories rather than being led by a force. This seems to solve the challenges researchers face regarding the operational behaviour of the cyclists.
It is also advised in future research to discuss the semantics of cyclist behaviour simulation. Literature that used this principle of predetermined trajectories still referred to their model as a model based on the SFM. This understates the fundamental criticism of these researchers on the SFM.

Lastly, commercial software companies are advised to actively partake in this process of creating a standardised model for cyclist simulation. With pro-cycling policy becoming more popular in cities all over the world, it is expected that municipalities and research institutes will show interest in a standardised model for cyclist behaviour when offered by a simulation software company. Moreover, such a standardised model incorporated in an applied simulation software should improve the verifiability and replicability of academic research. As a properly calibrated model for cyclist behaviour, would mean that less academics are inclined to create their own custom model for their research.

If these proposed developments come to fruition, other research subjects and applications become possible or more accessible. It should allow peer reviewers to test a researcher’s simulation model more easily. It enables urban planners and traffic engineers of local governments to quantitatively test their infrastructure designs and it enables academics to study the rapidly changing urban mobility landscape. For instance, it provides a possibility to experiment with infrastructure designs, aiming to tackle the contemporary challenges of established cycling cities.

Traffic Simulation
Social Force Model
Cycling
PTV Vissim
Cycling behaviour

http://resolver.tudelft.nl/uuid:07fdf942-bf4c-4e19-9937-cd62be5f415e

Student theses

master thesis

© 2024 Marijn Veraart