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Two-Phase Scheduling for Efficient Vehicle Sharing
- Source :
- IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Intelligent Transportation Systems, 2022, 23 (1), pp.457-470. ⟨10.1109/TITS.2020.3011952⟩, IEEE Transactions on Intelligent Transportation Systems, IEEE, In press, pp.1-14. ⟨10.1109/TITS.2020.3011952⟩
- Publication Year :
- 2022
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2022.
-
Abstract
- International audience; Cooperative Intelligent Transport Systems (C-ITS) is a promising technology to make transportation safer and more efficient. Ridesharing for long-distance is becoming a key means of transportation in C-ITS. In this paper, we focus on private long-distance ridesharing, which reduces the total cost of vehicle utilization for long-distance journeys. In this context, we investigate journey scheduling problem with shared vehicles to reduce the total cost of vehicle utilization. Most of the existing works directly schedule journeys to vehicles with long scheduling time and only consider the cost of driving travellers instead of the total cost. In contrast, to reduce the total cost and scheduling time, we propose a comprehensive cost model and a two-phase journey scheduling approach, which includes path generation and path scheduling. On this basis, we propose two path generation methods: a simple near optimal method and a reset near optimal method as well as a greedy based path scheduling method. Finally, we present an experimental evaluation with different path generation and path scheduling methods with synthetic data generated based on real-world data. The results reveal that the proposed scheduling approach significantly outperforms baseline methods in terms of total cost (up to 69.8%) and scheduling time (up to 84.0%) and the scheduling time is reasonable (up to 0.16s). The results also show that our approach has higher efficiency (up to 141.7%) than baseline methods.
- Subjects :
- Optimization
Mathematical optimization
Schedule
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]
Job shop scheduling
Scheduling
Total cost
Computer science
Mechanical Engineering
Scheduling (production processes)
Context (language use)
7. Clean energy
Computer Science Applications
Path planning problem
SAFER
11. Sustainability
Automotive Engineering
Path (graph theory)
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Intelligent transportation system
Vehicle sharing
Subjects
Details
- ISSN :
- 15580016 and 15249050
- Volume :
- 23
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Intelligent Transportation Systems
- Accession number :
- edsair.doi.dedup.....e8c333cfd28077153f3aca91d6fa3e12
- Full Text :
- https://doi.org/10.1109/tits.2020.3011952