Empirical research on residents’ acceptance of reserved parking

DOI

10.2991/978-94-6463-578-2_9How to use a DOI?

Keywords

Intelligent transportation; reserved parking; acceptance of residents; questionnaire survey

Abstract

Recently, the rapid development of new technologies such as artificial intelligence, cloud computing, big data, etc. has profoundly affected the complex and open urban transport system. Many new modes of traveling represented by reserved parking have been spawned under the impetus of new technologies. At present, in the field of reserved parking, scholars have carried out in-depth research on the construction of the reserved parking system and the formulation of parking space allocation strategies. However, fewer scholars have paid attention to the fairness of reserved parking. Therefore, this paper conducts an empirical study on the acceptance of residents of reserved parking using the questionnaire survey and data analysis method, analyses the decision-making process of residents’ travel modes and the factors influencing the acceptance of reserved parking, researches the acceptance of residents’ overall reserved parking mode, and explores the acceptance of residents’ reserved parking with different personal attributes. The study found that the overall resident acceptance of reserved parking is 71.61%. Among residents with cars, the acceptance of reserved parking is higher for those groups of residents who are aged 60 or above, have a college/vocational-technical college degree, have a monthly income between RMB 7,000–11,000, and are in retirement or working in the private sector. In contrast, residents in other classifications may face more considerations in accepting parking by reservation, such as flexibility in scheduling, financial costs, special needs of their work, long-established personal parking habits, and awareness of the emerging concept that leads to a conservative attitude towards reserved parking.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Rong Chen
AU  - Yue Liu
AU  - Ge Gao
AU  - Fahui Pan
AU  - Xinbo Mao
AU  - Shuo Liu
AU  - Shiying Yan
PY  - 2024
DA  - 2024/12/01
TI  - Empirical research on residents’ acceptance of reserved parking
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Digital Management (ICAIDM 2024)
PB  - Atlantis Press
SP  - 63
EP  - 71
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-578-2_9
DO  - 10.2991/978-94-6463-578-2_9
ID  - Chen2024
ER  -