Age-Based Preference Analysis between Autonomous Vehicles and Other Mobility Technologies
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 11
Abstract
As new mobility technologies become more widely used, they can transform the way that people travel. Among these technologies are autonomous vehicles (AVs) and micromobility such as bike-sharing and scooters. While the penetration and utilization of these mobility technologies have been extensively studied, little is known about their interaction and association between various age groups. Further, studies have focused on whether respondents would want AVs based upon their age rather than whether they would actually use them. The widespread adoption and use of self-driving vehicles is contingent upon user acceptance and utilization. Therefore, this study evaluated the association between different mobility options for various age groups using text network analysis (TNA) and Bayesian networks (BNs). This study used a data set collected from a survey conducted in Gilbert, Arizona, in 2019. The TNA results facilitated the extraction of additional features that could not be retrieved from the traditional data. The BN results revealed that micromobility devices are associated with higher likelihoods of wanting AVs and using AVs across all age groups, except for young adults who want dockless bikes and older adults who will use docked bikes. Furthermore, for all age groups, electric vehicles are associated with higher likelihoods of wanting AVs and using AVs. Regarding gender, young and middle-aged adult males were more likely to want AVs than their female counterparts. In addition, young and older adult males were more likely to use AVs than females. After combining the variables, the maximum probabilities of wanting AVs and using AVs in the city were 87% and 100% for young adults, 95% and 97% for middle-aged adults, and 59% and 93% for older adults, respectively. Emerging mobility society will have a better understanding of how mobility options are perceived by different age groups.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
Acknowledgments
I would like to acknowledge Gilbert city for the open-source 2019 transportation survey data that has been used in this study.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 150 • Issue 11 • November 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Nov 15, 2022
Accepted: Apr 10, 2024
Published online: Aug 26, 2024
Published in print: Nov 1, 2024
Discussion open until: Jan 26, 2025
ASCE Technical Topics:
- Analysis (by type)
- Bayesian analysis
- Bicycles
- Data collection
- Engineering fundamentals
- Equipment and machinery
- Highway transportation
- Infrastructure
- Mathematics
- Methodology (by type)
- Network analysis
- Probability
- Research methods (by type)
- Statistical analysis (by type)
- Transportation engineering
- Uncrewed vehicles
- Vehicles
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