Preferences Regarding Parking and Sharing Use for Privately Owned Autonomous Vehicles Based on a Virtual-Actual Experience
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Autonomous vehicles are capable of automatically cruising and parking, presenting an opportunity for these vehicles to be shared with others during idle periods. This study conducted a face to face stated preference survey on parking and shared use of privately owned autonomous vehicles based on a virtual-actual experience in Beijing. Utilizing 232 valid samples, a nested Logit model was established to analyse the hierarchical choice behaviour regarding parking modes, parking locations and shared use of autonomous vehicles. The research results show that travellers with a favourable initial understanding of autonomous vehicles and a significantly improved perception of them after the travel experience are more likely to choose the parking mode of ‘Platform agency (parking + paid sharing)’. Travellers tend to prefer remote parking places that offer lower parking fees and higher reliability in vehicle retrieval when needed. Additionally, travellers are more inclined to share their autonomous vehicles when the vehicle-sharing service platform offers lower agency fees and higher sharing earnings and allows temporary vehicle retrieval. Increasing public sharing attitude and perception of autonomous vehicles through travel experiences and advertising can encourage more people to accept car sharing. These findings offer key insights into the factors that affect the market penetration of private vehicle-sharing services in future.
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Haboucha CJ, Ishaq R, Shiftan Y. User preferences regarding autonomous vehicles. Transportation Research Part C: Emerging Technologies. 2017;78: 37-49. DOI: 10.1016/j.trc.2017.01.010
Fagnant DJ, Kockelman K. Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transportation Research Part A: Policy and Practice. 2015;77:167-181. DOI: 10.1016/j.tra.2015.04.003
Levin MW, Wong E, Nault-Maurer B, Khani A. Parking infrastructure design for repositioning autonomous vehicles. Transportation Research Part C: Emerging Technologies. 2020;120:102838. DOI: 10.1016/j.trc.2020.102838
González-González E, Nogués S, Stead D. Parking futures: Preparing European cities for the advent of automated vehicles. Land Use Policy. 2020;91:104010. DOI: 10.1016/j.landusepol.2019.05.029
Bahrami S, Roorda M. Autonomous vehicle parking policies: A case study of the City of Toronto. Transportation Research Part A: Policy and Practice. 2022;155:283-296. DOI: 10.1016/j.tra.2021.11.003
Tian Z, et al. Where to park an autonomous vehicle? Results of a stated choice experiment. Transportation Research Part A: Policy and Practice. 2023;175:103763. DOI: 10.1016/j.tra.2023.103763
Zhang X, Liu W, Waller ST. A network traffic assignment model for autonomous vehicles with parking choices. Computer‐Aided Civil and Infrastructure Engineering, 2019;34(12): 1100-1118. DOI: 10.1111/mice.12486
Si H, Duan X, Cheng L, De Vos J. Adoption of shared autonomous vehicles: Combined effects of the external environment and personal attributes. Travel Behaviour and Society. 2024;34:100688. DOI: 10.1016/j.tbs.2023.100688
Etminani-Ghasrodashti R, Kermanshachi S, Rosenberger JM, Foss A. Exploring motivating factors and constraints of using and adoption of shared autonomous vehicles (SAVs). Transportation Research Interdisciplinary Perspectives. 2023;18:100794. DOI: 10.1016/j.trip.2023.100794
Ye X, et al. Research on parking choice behavior of shared autonomous vehicle services by measuring users’ intention of usage. Transportation Research Part F: Traffic Psychology and Behaviour. 2022;88:81-98. DOI: 10.1016/j.trf.2022.05.012
Khayati Y, Kang JE, Karwan M, Murray C. Household use of autonomous vehicles with ride sourcing. Transportation Research Part C: Emerging Technologies, 2021;125:102998. DOI: 10.1016/j.trc.2021.102998
Wiseman Y. Remote parking for autonomous vehicles. International Journal of Hybrid Information Technology. 2017;10(1):313-24. DOI: 10.14257/ijhit.2017.10.1.27
Pimenta A, Kamruzzaman M, Currie G. Exploring gaps in residential and parking location choice models for autonomous vehicles: a proposed evaluation framework. Transport Reviews. 2025;45(1):94-118. DOI: 10.1080/01441647.2024.2417718
Bischoff J, Maciejewski M, Schlenther T, Nagel K. Autonomous vehicles and their impact on parking search. IEEE Intelligent Transportation Systems Magazine. 2018;11(4):19-27. DOI: 10.1109/MITS.2018.2876566
Parmar J, Das P, Dave SM. Study on demand and characteristics of parking system in urban areas: A review. Journal of Traffic and Transportation Engineering, 2020;7(1):111-124. DOI: 10.1016/j.jtte.2019.09.003
Yu R, Yun M, Yang X. Study on driver's parking location choice behavior considering drivers' information acquisition. Second International Conference on Intelligent Computation Technology and Automation. IEEE. 2009;3:764-770. DOI: 10.1109/ICICTA.2009.650
Ibeas A, Dell’Olio L, Bordagaray M, de Ortúzar J. Modelling parking choices considering user heterogeneity. Transportation Research Part A: Policy and Practice. 2014;70:41-49. DOI: 10.1016/j.tra.2014.10.001
Chen M, Hu C, Chang T. The research on optimal parking space choice model in parking lots. 3rd International Conference on Computer Research and Development. IEEE. 2011;2:93-97. DOI: 10.1109/ICCRD.2011.5764091
Li XD, et al. Parking choice behavior of urban village residents considering parking risk: An integrated modeling approach. Case Studies on Transport Policy. 2024;15:101145. DOI: 10.1016/j.cstp.2023.101145
Hassine SB, Mraihi R, Lachiheb A, Kooli E. Modelling parking type choice behavior. International Journal of Transportation Science and Technology. 2022;11(3):653-664. DOI: 10.1016/j.ijtst.2021.09.002
Nourinejad M, Bahrami S, Roorda MJ. Designing parking facilities for autonomous vehicles. Transportation Research Part B: Methodological. 2018;109:110-127. DOI: 10.1016/j.trb.2017.12.017
Zhang W, Guhathakurta S. Parking spaces in the age of shared autonomous vehicles: How much parking will we need and where?. Transportation Research Record. 2017;2651(1):80-91. DOI: 10.3141/2651-09
Millard-Ball A. The autonomous vehicle parking problem. Transport Policy. 2019;75:99-108. DOI: 10.1016/j.tranpol.2019.01.003
Dias FF, et al. A behavioral choice model of the use of car-sharing and ride-sourcing services. Transportation. 2017;44:1307-1323. DOI: 10.1007/s11116-017-9797-8
Paundra J, Rook L, van Dalen J, Ketter W. Preferences for car sharing services: Effects of instrumental attributes and psychological ownership. Journal of Environmental Psychology. 2017;53:121-130. DOI: 10.1016/j.jenvp.2017.07.003
Tao Z, Nie Q, Zhang W. Research on travel behavior with car sharing under smart city conditions. Journal of Advanced Transportation. 2021;(1):8879908. DOI: 10.1155/2021/8879908
Etzioni S, Daziano RA, Ben-Elia E, Shiftan Y. Preferences for shared automated vehicles: A hybrid latent class modeling approach. Transportation Research Part C: Emerging Technologies. 2021;125:103013. DOI: 10.1016/j.trc.2021.103013
Lv F, et al. Research on the influencing factors of using behavior intention of automated car-sharing system. IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE). IEEE. 2022;320-325. DOI: 10.1109/ICITE56321.2022.10101410
Shirley T, et al. Exploring the potential of using privately-owned, self-driving autonomous vehicles for evacuation assistance. Journal of Advanced Transportation. 2021;(1):2156964. DOI: 10.1155/2021/2156964
Khayati Y, Kang JE, Karwan M, Murray C. Household activity pattern problem with autonomous vehicles. Networks and Spatial Economics. 2021;21(3):609-637. DOI: 10.1007/s11067-021-09537-6
Kock N, Hadaya P. Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal. 2018;28(1):227-261. DOI: 10.1111/isj.12131
Green S B. How many subjects does it take to do a regression analysis. Multivariate Behavioral Research. 1991;26(3):499-510. DOI: 10.1207/s15327906mbr2603_7
Maxwell S E. Sample size and multiple regression analysis. Psychological Methods. 2000;5(4): 434. DOI: 10.1037/1082-989X.5.4.434
Manski CF, McFadden D. Alternative estimators and sample designs for discrete choice analysis. Structural Analysis of Discrete Data with Econometric Applications. 1981;2:2-50. https://www.scholars.northwestern.edu/en/publications/alternative-estimators-and-sample-designs-for-discrete-choice-ana [Accessed 1st November 2024]
Zhao X, Yan X, Yu A, Van Hentenryck P. Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models. Travel Behaviour and Society. 2020;20:22-35. DOI: 10.1016/j.tbs.2020.02.003
McFadden, D. Conditional logit analysis of qualitative choice behaviour. In: Zarembka, P. (Ed.), Frontiers in Econometrics. Academic Press New York, New York, NY. 1973;105-142. https://escholarship.org/uc/item/61s3q2xr [Accessed 1st November 2024].
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