Drivers overtaking cyclists and pedestrians: Modeling road-user behavior for traffic safety
Doctoral thesis, 2023

In a world aiming to shift to more sustainable modes of transportation, vulnerable road users (VRUs) like cyclists and pedestrians are still confronted with significant barriers to safety, particularly on rural roads where overtaking maneuvers represent a frequent and dangerous interaction with motorized traffic. If drivers misjudge their kinematics, even near-crashes without physical contact can harm the perceived safety of the VRU, which may decrease the willingness to continue cycling or walking on these roads. Crash risks when overtaking VRUs exist in different overtaking phases: when approaching the VRU, steering out, passing, and eventually returning. To make overtaking VRUs safer, improvements to policymaking, infrastructure, and vehicles are needed. However, these improvements need models that can describe or predict road-user behavior in overtaking, which was the objective of this thesis. Based on data sets obtained from a test-track experiment, field-test studies, and naturalistic studies, this thesis developed behavioral models for both objective and perceived safety of drivers and VRUs in different overtaking phases. The results indicate that drivers’ and VRUs’ behavior is mainly influenced by their highest crash or injury risk. The descriptive models showed that a close oncoming vehicle could reduce a driver’s safety margins to the VRU in all phases. Furthermore, the VRU behavior may affect the driver’s behavior; for instance, through lane positioning and, for pedestrians, walking direction. Infrastructure design and policymaking should focus on preventing overtaking in areas where oncoming vehicles are hard to estimate and enforcing sufficient clearances to the cyclist, stratified by speed. The predictive models can help vehicle safety systems adapt to drivers to become more acceptable, for instance, when assisting drivers in the decision to overtake or not. They may further help optimize road networks’ objective and perceived safety.

traffic safety

behavioral models

perceived safety

driver behavior

advanced driving assistance systems

Overtaking

vulnerable road users

Omega-salen, Hörselgången 5, Chalmers
Opponent: Professor Christopher Cherry, University of Tennessee, Knoxville (TN), US

Author

Alexander Rasch

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

How do drivers overtake pedestrians? Evidence from field test and naturalistic driving data

Accident Analysis and Prevention,;Vol. 139(2020)

Journal article

How do oncoming traffic and cyclist lane position influence cyclist overtaking by drivers?

Accident Analysis and Prevention,;Vol. 142(2020)

Journal article

Drivers’ and cyclists’ safety perceptions in overtaking maneuvers

Transportation Research Part F: Traffic Psychology and Behaviour,;Vol. 84(2022)p. 165-176

Journal article

Modeling Drivers’ Strategy When Overtaking Cyclists in the Presence of Oncoming Traffic

IEEE Transactions on Intelligent Transportation Systems,;Vol. 23(2022)p. 2180-2189

Journal article

When is it Safe to Complete an Overtaking Maneuver? Modeling Drivers' Decision to Return After Passing a Cyclist

IEEE Transactions on Intelligent Transportation Systems,;Vol. In Press(2024)

Journal article

Getting hit by a motorized vehicle is one of the major causes of injury or death for vulnerable road users (VRUs), particularly cyclists and pedestrians. Such crashes are most severe on rural roads where vehicles travel at high speeds and cycle paths or sidewalks are missing. Where VRUs and motorized vehicles need to share the same lane, overtaking maneuvers are a frequent challenge for drivers who need to avoid collisions with the VRU and oncoming traffic. Countermeasures exist; however, they need a detailed understanding of human behavior to become most effective. This thesis addressed the overtaking of cyclists and pedestrians by conducting a series of studies that collected data from overtaking maneuvers and modeled human behavior. While the data were collected in different environments, their story is similar: when drivers face a larger threat, such as oncoming traffic, they might compromise the VRU’s safety. This thesis showed that not only the risk of crashing increases in such situations but also the comfort of both driver and VRU is at stake. This thesis further developed computational models that can be used to improve transport and vehicle safety systems. Traffic regulations should ensure passing distances and speeds are accepted by VRUs, and roads must be designed to allow such distances and speeds. Safety systems and automated driving may benefit from the models by having a human reference for overtaking.

Modellering av Interaktion mellan Cyklister och Fordon 2- MICA2

VINNOVA (d-nr2019-03082), 2019-11-01 -- 2022-12-31.

MICA - Modelling Interaction between Cyclists and Automobiles

VINNOVA (2017-05522), 2018-03-09 -- 2019-12-31.

DIV - Driver Interaction with Vulnerable Road Users

Toyota Motor Europe, 2015-09-01 -- 2020-08-31.

Autoliv AB, 2015-09-01 -- 2020-08-31.

Areas of Advance

Transport

Subject Categories

Transport Systems and Logistics

Infrastructure Engineering

Applied Psychology

Vehicle Engineering

ISBN

978-91-7905-796-1

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5262

Publisher

Chalmers

Omega-salen, Hörselgången 5, Chalmers

Online

Opponent: Professor Christopher Cherry, University of Tennessee, Knoxville (TN), US

More information

Latest update

10/16/2024