What influences vulnerable road users’ perceptions of autonomous vehicles? A comparative analysis of the 2017 and 2019 Pittsburgh surveys

Yingying Xing, Huiyu Zhou, Xiao Han, Meng Zhang and Jian Lu

Technological Forecasting and Social Change, 2022, vol. 176, issue C

Abstract: Autonomous vehicles (AVs) are expected to eliminate many driver errors to save thousands of lives. As vulnerable road users, pedestrians and bicyclists are more likely to be injured or killed in accidents involving cars. Therefore, understanding the perceptions of vulnerable road users is crucial for developing and deploying AVs and solving public concerns because the acceptance of AVs relies on both AV users and other road users, such as vulnerable road users. This paper analyzed two surveys collected in 2017 and 2019 by BikePGH in Pittsburgh to understand vulnerable road users’ perceptions of AVs in different years. The analysis showed that vulnerable road users’ interactive experiences with AVs increased from 2017 to 2019 in Pittsburgh, and the interactive experiences with AVs positively affected vulnerable road users’ perceived safety and receptivity toward AVs in 2017 and 2019. Specifically, vulnerable road users’ perceived safety of AVs significantly increased from 2017 to 2019, while their receptivity toward AVs did not change significantly during that period. Additionally, autonomous driving accidents negatively affected vulnerable road users’ perceptions of AVs. Therefore, we recommend that policymakers provide opportunities for the public to interact with AVs and guarantee vulnerable road users’ safety and benefits in AV testing.

Keywords: Autonomous vehicle; Public perception; Vulnerable road user; Interactive experience; Perceived safety, Receptivity (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162521008891

DOI: 10.1016/j.techfore.2021.121454

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