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An Adaptive Route Planning Method of Connected Vehicles for Improving the Transport Efficiency

Bibliographic Data

ID22033709
AuthorsBaoju Liu (0000-0003-1151-4309, Central South University), Jun Long (0009-0008-6097-0646, Central South University), Min Deng (0000-0001-7041-4418, Central South University), Xuexi Yang (0000-0001-5531-5841, Central South University, corresponding author), Yan Shi (0000-0003-0320-3244, Central South University)
Year2022
Volume11
Issue1
Pages39
Publication date2022-01-06
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi11010039
OpenAlexW4206291403
LanguageEN
References cited32

In recent years, the route-planning problem has gained increased interest due to the development of intelligent transportation systems (ITSs) and increasing traffic congestion especially in urban areas. An independent route-planning strategy for each in-vehicle terminal improves its individual travel efficiency. However, individual optimal routes pursue the maximization of individual benefit and may contradict the global benefit, thereby reducing the overall transport efficiency of the road network. To improve traffic efficiency while considering the travel time of individual vehicles, we propose a new dynamic route-planning method by innovatively introducing a bidding mechanism in the connected vehicle scenario for the first time. First, a novel bidding-based dynamic route planning is proposed to formulate vehicle routing schemes for vehicles affected by congestion via the bidding process. Correspondingly, a bidding price incorporating individual and global travel times was designed to balance the travel benefits of both objectives. Then, in the bidding process, a new local search algorithm was designed to select the winning routing scheme set with the minimum bidding price. Finally, the proposed method was tested and validated through case studies of simulated and actual driving scenarios to demonstrate that the bidding mechanism would be conducive to improving the transport efficiency of road networks in large-scale traffic flow scenarios. This study positively contributes to the research and development of traffic management in ITSs

Bidding · Business · Computer network · Operations research · Traffic congestion · Transport engineering · Computer Science · Engineering · Traffic control and management · Transportation and Mobility Innovations · Transportation Planning and Optimization

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