Understanding the interaction between cyclists and motorized vehicles at unsignalized intersections: Results from a cycling simulator study

Journal article, 2024

cyclists’ behavior to develop behavioral models that can predict the cyclist’s intent. Most conflicts between
cyclists and vehicles happen at crossings where the road users share the path, especially at unsignalized intersections.
However, few studies have investigated and modeled the interaction between cyclists and vehicles at
unsignalized intersections. Method: A bike simulator experiment was conducted to scrutinize cyclists’ response
process as they interacted with a passenger car at an unsignalized intersection. An existing unsignalized intersection
in Gothenburg was simulated for test participants. Two independent variables were varied across trials:
the difference in time to arrival at the intersection (DTA) and intersection visibility (IV). Subjective and quantitative
data were analyzed to model the cyclists’ behavior. Results: When approaching the intersection, cyclists
showed a clear sequence of actions (pedaling, braking, and head turning). The distance from the intersection at
which cyclists started braking was significantly affected by the two independent variables. It was also found that
DTA, looking duration, and pedaling behavior significantly affected cyclists’ decisions to yield. Finally, the
questionnaire outputs show that participants missed eye contact or communication with the motorized vehicle.
Conclusions: The kinematic interaction between cyclists and vehicles, along with the cyclist’s response process
(visual and kinematic), can be utilized to predict cyclists’ yielding decision at intersections. From the infrastructural
perspective, enhancing visibility at intersections has the potential to reduce the severity of interactions
between cyclists and vehicles. The analysis of the questionnaire emphasizes the significance of visual communication
between cyclists and drivers to support the cyclist’s decision-making process when yielding. Practical
applications: The models can be used in threat assessment algorithms so that active safety systems and automated
vehicles can react safely to the presence of cyclists in conflict scenarios.

Marie Skłodowska-Curie Actions; Innovative Training Network (ITN); Project name: SHAPE-IT;Grant number: 860410;Publication date: [2024]; DOI: [10.1016/j.jsr.2024.05.007]