PETravel: Personalized e-bike travel recommendation system with unlimited endurance
Publication Type
Conference Proceeding Article
Publication Date
5-2025
Abstract
E-bike tourism has become an increasingly popular and sustainable mode of travel. A significant concern for riders is managing battery range and mitigating range anxiety during extended journeys. Battery swapping has emerged as an innovative solution to these challenges. However, existing e-bike route planning systems fail to account for the need for battery swapping. To bridge this gap, we present PETravel, a personalized e-bike travel recommendation system that integrates battery-swapping strategies directly into route planning. In addition, it enhances the tourism experience by accommodating diverse personalized requirements across various scenarios. Evaluations demonstrate PETravel's effectiveness in providing tailored solutions for personalized and sustainable tourism while supporting a variety of e-bike travel scenarios. A video demonstration of PETravel is available here: https://youtu.be/bu5UO8ArYZg.
Keywords
Route Recommendation, E-bike Tour, Dijkstra’s Algorithm
Discipline
Databases and Information Systems | Theory and Algorithms
Research Areas
Intelligent Systems and Optimization
Publication
WWW '25: Companion Proceedings of the ACM on Web Conference 2025, Sydney, Australia, April 28 - May 2
First Page
2907
Last Page
2910
Identifier
10.1145/3701716.3715191
Publisher
ACM
City or Country
New York
Citation
SHI, Yuduo; LI, Zhao; PAN, Xuming; CHEN, Yaoling; ZHOU, Bo; XU, Haitao; MA, Wenrui; Yuchen LI; and HU, Shichang.
PETravel: Personalized e-bike travel recommendation system with unlimited endurance. (2025). WWW '25: Companion Proceedings of the ACM on Web Conference 2025, Sydney, Australia, April 28 - May 2. 2907-2910.
Available at: https://ink.library.smu.edu.sg/sis_research/10409
Additional URL
https://doi.org/10.1145/3701716.3715191