Cooperative Control in Expressway Weaving Areas via Internet of Vehicles
The weaving area of expressways undertakes the task of vehicle diversion and merging, often causing congestion as a bottleneck in traffic. Thanks to the explosive evolution of 6G technology, the data transmission reliability and service quality of Internet of Vehicles (IoV) have been enhanced, making it possible for intelligent transportation systems to become more autonomous, intelligent, and efficient. Intelligent transportation systems are showing promise as a means to improve traffic efficiency and alleviate congestion issues. Due to different strategic purposes, exiting vehicles and merging vehicles weave, interlace, and frequently change lanes in the weaving area. Given this premise, we consider separating the tasks of vehicle diversion and merging in space and propose a distributed dynamic transferable utility game-based lane-changing strategy. We have designed a three-player game framework based on a five-step transferable utility model to assist exiting vehicles in fairly and efficiently completing lane changes in advance to avoid conflicts with merging vehicles in the weaving area. Simulation results indicate that the dynamic transferable utility game-based lane-changing strategy can accommodate higher lane change demands and generally benefit all participating vehicles in most scenarios. Furthermore, in mixed traffic flow scenarios of exiting and merging vehicles, this lane-changing strategy effectively enhances road capacity, reduces vehicle delay time, and improves network operational efficiency.
Authors
- Xinglong Wu (ORCID: https://orcid.org/0009-0007-5860-5941)
- Hua Hu (ORCID: https://orcid.org/0000-0003-2370-429X)
- Tingting Fu (ORCID: https://orcid.org/0000-0002-6629-8976)
Institutions
- Hangzhou Normal University (CN)
- Hangzhou Dianzi University (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1109/jiot.2024.3481317
- Citations
- 2
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 0.66
Funders
- National Natural Science Foundation of China