Objective and perceived risk in overtaking: The impact of driving context |
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Affiliation: | 1. Dept. Human Factors, Ulm University, Germany;2. Center of Key Competencies, Technical University of Munich, Germany;1. University of Salford, Manchester M5 4WT, UK;2. University of Basrah, Basrah, Iraq;3. University of Salford, UK;1. Indian Institute of Technology Kanpur, Kanpur 208016, India;2. University of Alaska Anchorage, 2900 Spirit Drive, Anchorage, AK 99508, United States |
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Abstract: | The assistance and autonomous performance of overtaking manoeuvres can offer significant safety benefits. The impact of driving context on perceived risk emphasises the benefits of using contextual information to adjust the manoeuvring behaviour. This paper follows a mixed approach, addressing two main objectives: identifying factor combinations related to overtaking crashes (objective risk) and exploring their relationship to perceived risk. Factor combinations were extracted from a multi-year dataset, acquired from the UK in-depth study RAIDS (Road Accident In-depth Studies). Selected factors were used to create motorway overtaking scenarios with different manoeuvring behaviour (pull-out distance, manoeuvre duration, speed) and driving context (day/night, overtaking car/truck), while 237 participants assessed their impact on perceived risk through an online survey. The findings highlight the strong impact of manoeuvre characteristics on perceived risk, mediated or intensified by the driving context. Long pull-out distance and short manoeuvre duration time were preferred; under night conditions, short pull-out distances were perceived as riskier compared to daytime, while the opposite effect appeared for high speed, which was considered safer. The results can inform future research on motorway overtaking safety perception and acceptability, as well as the design of systems that assist or autonomously perform overtaking. Specifically, they can be used as guidelines for incorporating context related information to adjust overtaking behaviour according to user preferences and create a positive passenger experience. |
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Keywords: | Automated driving Overtaking Perceived risk Clustering Crash analysis Situational factors |
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