Abstract
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.
Highlights
Intelligent transportation systems (ITSs) are an important part of the urban geoinformation framework, and road traffic congestion has become an extensive problem in urban areas that hinders the operational efficiency of urban traffic systems and the intelligent application of urban geo-informatics
In the proposed method, only the driving route of vehicles that will be affected by congestion are dynamically replanned in advance; vehicles on unobstructed road segments would continue with their originally planned routing scheme to achieve a balance between the computational burden and transport efficiency of the road network
Compared with the individual optimal routes obtained by vehicles independently, this local negotiation method significantly improves the overall traffic efficiency of the road network, reducing the travel time by 32.71% on average
Summary
Intelligent transportation systems (ITSs) are an important part of the urban geoinformation framework, and road traffic congestion has become an extensive problem in urban areas that hinders the operational efficiency of urban traffic systems and the intelligent application of urban geo-informatics. To reduce the overall travel time and alleviate traffic congestion, we propose a new bidding-mechanism-based route-planning method, which is introduced to plan vehicle routing schemes by coordinating with multiple road segment agents. (1) To the best of our knowledge, we innovatively introduce for the first time a bidding mechanism to dynamically coordinate plan routing schemes for vehicles affected by congestion based on the road intersection planning center model In this mechanism, the independent route-planning schemes of control centers in a centralized framework are transformed into a route-negotiation process of multiple CVs and road segment agents, resulting in a traffic efficiency improvement in the road network. (3) A novel priority-set-based local search algorithm is proposed to address the combination assignment problem between large-scale traffic flow and road segments in the bidding-based route-replanning process This algorithm improved the efficiency of route replanning by selecting a combination of winning schemes rather than a single one.
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