Modelling discomfort: How do drivers feel when cyclists cross their path?
Journal article, 2020
Method: This study investigated the degree of discomfort experienced by drivers when cyclists crossed their travel path. Participants were instructed to drive through an intersection in a fixed-base simulator or on a test track, following the same experimental protocol. The effects of demographic variables (age, gender, driving frequency, and yearly mileage), controlled variables (car speed, bicycle speed, and bicycle-car configuration), and a visual cue (car’s time-to-arrival at the intersection when the bicycle appears; TTAvis) on self-reported discomfort were analysed using cumulative link mixed models (CLMM).
Results: Results showed that demographic variables had a significant effect on the discomfort felt by drivers—and could explain the variability observed between drivers. Across both experimental environments, the controlled variables were shown to significantly influence discomfort. TTAvis was shown to have a significant effect on discomfort as well; the closer to zero TTAvis was (i.e., the more critical the situation), the more likely the driver red great discomfort. The prediction accuracies of the CLMM with controlled variables and the CLMM with the visual cue were similar, with an average accuracy between 40 and 50%. Surprise trials in the simulator experiment, in which the bicycle appeared unexpectedly, improved the prediction accuracy of the models, more notably the CLMM including TTAvis.
Conclusions: The results suggest that the discomfort was mainly driven by the visual cue rather than the deceleration cues. Thus, it is suggested that an algorithm that estimates driver discomfort be included in active safety systems and autonomous driving systems. The CLMM including TTAvis was presented as a potential candidate to serve this purpose.
Safety systems
Cycling safety
Driver behaviour model
Test track
Comfort
Driving simulator
Author
Christian-Nils Åkerberg Boda
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety
Marco Dozza
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety
Pablo Puente Guillen
Toyota Motor Europe
Prateek Thalya
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety
Veoneer
Leila Jaber
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety
Nils Lübbe
Autoliv AB
Accident Analysis and Prevention
0001-4575 (ISSN)
Vol. 146 105550DIV - 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
Other Engineering and Technologies
DOI
10.1016/j.aap.2020.105550