Computational models for safe interactions between automated vehicles and cyclists
Doktorsavhandling, 2025

Cyclists, as vulnerable road users, face significant safety risks in traffic, especially at unsignalized intersections where they must interact with motorized vehicles. This PhD thesis investigated bicycle-vehicle interactions at unsignalized intersections and developed predictive models to improve active safety systems and automated driving. The research integrates naturalistic and simulator data to model the behavior of both cyclists and vehicles at intersections. The models included kinematic factors, non-verbal communication, and glance behavior.
The studies included in this thesis revealed that kinematic factors, such as time to arrival (DTA), along with cyclists' non-verbal cues, like head movements and pedaling, significantly affect yielding behavior at intersections. Both simulator data and naturalistic data confirmed that visibility conditions and DTA played a critical role in cyclists' decision-making while subjective data from questionnaires highlighted the importance of communication and eye contact between cyclists and drivers in reducing the severity of interactions.
Additionally, an analysis of naturalistic data uncovered differences in yielding behavior between professional and non-professional drivers, with professional drivers being less likely to yield to cyclists. Different models, leveraging machine learning and game theory, were developed to predict yielding decisions during these interactions. Lastly, simulator data was used to model drivers’ behavior, incorporating kinematics, demographics, and gaze metrics to predict drivers’ responses to crossing cyclists.
The predictive models developed through this research provide novel insights for the design of threat assessment algorithms for active safety and automated driving, enhancing the machine ability to anticipate cyclist behavior and improve safety.

advanced driving assistance systems

cyclist behavior

automated vehicles safety

active safety systems

automated driving

computational behavioral models

VASA A
Opponent: Narelle Haworth

Författare

Ali Mohammadi

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

Mohammadi, A., Bruneau, A., & Dozza, M. Modelling vehicle-cyclists’ interactions to support automated driving and advanced driving assistance systems. Journal of the International Association of Traffic and Safety Sciences (IATSS). (Submitted)

Mohammadi, A., Kalantari, A., Markkula, G., & Dozza, M. (2024). Cyclists’ interactions with professional and non-professional drivers: Observations and game theoretic models. Journal of Transportation Research Part F: Traffic Psychology and Behavior. (Under review)

Ämneskategorier (SSIF 2025)

Transportteknik och logistik

Farkost och rymdteknik

ISBN

978-91-8103-198-0

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5656

Utgivare

Chalmers

VASA A

Online

Opponent: Narelle Haworth

Mer information

Senast uppdaterat

2025-03-21