Stated Preference Analysis Toward Autonomous Vehicles and Other Emerging Mobility Technologies Using Bayesian Networks

Date
2022
Authors
Imanishimwe, Delphine
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Abstract

The penetration and utilization of mobility technologies (e.g., Autonomous vehicles (AVs) and micromobility) have been extensively studied, but little is known about their interaction and association between various age groups and vulnerable road users. Furthermore, studies have focused on whether respondents would want AVs based on their age rather than whether they would use them. Therefore, this study evaluated the association between different mobility options for various age groups using Text Network Analysis (TNA) and Bayesian Networks (BNs). The BN results based on a survey conducted in Gilbert, Arizona revealed that micromobility devices and electric vehicles are associated with higher likelihood of wanting AVs and using AVs across all age groups. Regarding gender, young and middle-aged adult males were more likely to want AVs than their female counterparts. Additionally, young, and older adult males were more likely to use AVs than females. In addition, BN results based on a survey conducted in Pittsburgh, Pennsylvania revealed that familiarity with the technology behind AVs, feeling safe while sharing the road with AVs, and using Pittsburgh's public streets as a proving ground for AVs were associated with higher likelihood of AVs' safety potential to reduce traffic injuries and fatalities. Furthermore, the BN model predicted that the experience of sharing the road with AVs while riding a bicycle or walking, familiarity with the technology behind AVs, and using Pittsburgh's public streets as a proving ground for AVs were associated with higher likelihood of feeling safe sharing the road with AVs. Emerging mobility society will have a better understanding of how mobility options are perceived by different age groups and vulnerable road users.

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Keywords
Autonomous Vehicles, Bayesian Network, Micromobility, Text Network
Citation
Department
Civil and Environmental Engineering