Technological perception on autonomous vehicles: perspectives of the non-motorists

ABSTRACT

This study investigated a less explored autonomous vehicle (AV) related topic (non-motorists and AVs) through the following two research questions: (1) Does the perception towards AVs differ in non-motorists based on stakeholder nature? and (2) Does prior interaction with AVs alter perception on AVs? The present study examined survey data collected by BikePGH in Pittsburgh, Pennsylvania. This study used multiple correspondence analysis (MCA) to identify the response patterns of participants and sort the responses into several clusters. The results show that perception measures vary among participants based on the nature of the stakeholder. The reception of AVs among the participants was mixed. The results also show that participants with real AV interactions have higher expectations and interest in AVs than the participants with no experience. Additionally, the findings show that participants who see no safety potentials for AVs are also against using Pittsburgh as an AV proving ground. It is anticipated that the results will help in improving the strategic management of AVs to make non-motorist mobility safer.

KEYWORDS:

• Autonomous vehicles
• pedestrians
• bicyclists
• perception
• multiple correspondence analysis

Acknowledgements

The authors like to thank two anonymous reviewers for their thoughtful suggestions. The current version of the paper is much improved due to their excellent feedback.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

Dr Subasish Das is an Associate Transportation Researcher at Texas A&M Transportation Institute (TTI). He received his PhD in Civil Engineering from University of Louisiana at Lafayette in 2015 and holds a Master of Science in Civil Engineering from the same university in 2012. He has more than 10 years of national and international experience associated with transportation safety engineering research projects. His primary fields of research interest are roadway safety, roadway design and operation, mobility, machine learning, deep learning, and natural language processing. Dr Das is the author or co-author of over 80 peer reviewed journal articles and research reports. He is author of CRC Press book ‘Artificial Intelligence in Highway Safety.’

Dr Anandi Dutta is currently working as an Assistant Professor of Practice at the Department of Computer Science in University of Texas at San Antonio. She received her PhD in Computer Engineering from University of Louisiana at Lafayette in 2016 and holds a Master of Science in Computer Engineering from the same university in 2014. She also holds a Master of Science in Electrical Engineering from Louisiana State University in 2011. Her primary fields of research interest are machine learning, deep learning, natural language processing, and computer hardware. Dr Dutta is the author or co-author of over 15 peer reviewed journal articles and conference proceeding papers. She is a member of IEEE.

Dr Kay Fitzpatrick is a Senior Research Engineer at the Texas A&M Transportation Institute. She has both bachelor and master’s degrees from Texas A&M University and a doctor of philosophy degree from Penn State University. She is a registered professional engineer in Texas and Pennsylvania. Her research interest includes the effects of roadway features on traffic operations and safety. She has been the principal investigator for numerous research projects for TxDOT, NCHRP, TCRP, and FHWA. She has authored or co-authored over 100 papers and 100 research reports or guides.