A Study on the Scheduling Problem of Car Sharing with User Participation Under Dynamic Incentives
Authors
Jie Wang1, Meijie Jia1, *, Yunpeng Xie1
1Engineering School for Transportation, Dalian Maritime University, Dalian, China
*Corresponding author.
Email: jiaxibei_101@163.com
Corresponding Author
Meijie Jia
Available Online 26 July 2023.
- DOI
- 10.2991/978-94-6463-200-2_78How to use a DOI?
- Keywords
- Car sharing scheduling; staff relocation; user relocation
- Abstract
Car sharing is growing rapidly worldwide, and the development of car sharing is constrained by factors such as unbalanced user travel demand and high enterprise operating costs. This paper considers the influence of multiple factors on user travel behavior, uses a multinomial logit model to encourage user participation in car-sharing dispatch, and develops a model for joint employee and user dispatch with the goal of minimizing enterprise costs. The model is validated using Qingdao city as an example, and the results show that user participation in dispatching can reduce enterprise operating costs.
- Copyright
- © 2023 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.
Cite this article
TY - CONF AU - Jie Wang AU - Meijie Jia AU - Yunpeng Xie PY - 2023 DA - 2023/07/26 TI - A Study on the Scheduling Problem of Car Sharing with User Participation Under Dynamic Incentives BT - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023) PB - Atlantis Press SP - 761 EP - 767 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-200-2_78 DO - 10.2991/978-94-6463-200-2_78 ID - Wang2023 ER -