Safety Assessment of the Interaction Between an Automated Vehicle and a Cyclist

A Controlled Field Test

Journal Article (2023)
Author(s)

M.I. Oskina (Royal HaskoningDHV)

Haneen Farah (TU Delft - Transport and Planning)

Peter Morsink (Royal HaskoningDHV)

R. Happee (TU Delft - Intelligent Vehicles)

B Arem (TU Delft - Transport and Planning)

Transport and Planning
Copyright
© 2023 M.I. Oskina, H. Farah, Peter Morsink, R. Happee, B. van Arem
DOI related publication
https://doi.org/10.1177/03611981221112423
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 M.I. Oskina, H. Farah, Peter Morsink, R. Happee, B. van Arem
Transport and Planning
Issue number
2
Volume number
2677
Pages (from-to)
1138-1149
Reuse Rights

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Abstract

The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a controlled field experiment consisting of interaction scenarios in which a vehicle approached the cyclist from behind. Four interaction scenarios were included: manual and automated following and manual and automated overtaking of the cyclist. The vehicle operated in all scenarios in a manual mode for safety reasons. However, before each ride, participants received information about the vehicle’s operation mode (automated or manual). The following attributes were considered: overtaking speed, overtaking lateral distance, following distance, and roadside objects. The objective and the subjective risks were evaluated in each scenario. The objective risk was assessed using the probabilistic driving risk field, and the subjective risk was assessed based on the cyclists’ selfreported risk values, cycling behavior, and their trust in AVs. The results show that automated and manual following have similar objective and subjective risks, while automated overtaking has a higher level of objective and subjective risks than manual overtaking. The results also show that a longer interaction time leads to an increase in cycling speed and a decrease in the lateral distance of the cyclist to the curb. Thus, we conclude that automated following is a safer option for short traveling distances, while for longer traveling distances, manual overtaking is preferred. Additionally, a short lateral distance from the cyclist when overtaking increases the subjective and objective risks.

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