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论文类型：期刊论文

发表时间：2017-07-01

发表刊物：IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

收录刊物：SCIE、EI、Scopus

卷号：66

期号：7

页面范围：6115-6129

ISSN号：0018-9545

关键字：Channel congestion; cooperative vehicle safety systems (CVSSs); fairness; vehicle tracking; vehicular networking

摘要：Cooperative vehicle safety systems (CVSSs) rely on vehicular networking for broadcasting state information in order to track neighbors' positions and, therefore, to predict potential collisions. In vehicular networking, a large number of vehicles compete for access to the limited channel resource, causing channel congestion. The vehicle tracking accuracy, which is the basis for CVSSs, therefore, can be heavily affected. Moreover, the available channel resources must be shared among vehicles in a fair way in order to maintain accurate tracking accuracy for each vehicle. To realize fair access to channel resources while maintaining an accurate tracking performance under conditions of dynamic vehicle density, in this paper, we present a distributed fair transmission rate control strategy, based on multi-agent model predictive control (MPC). We first propose a dynamic information dissemination rate model to capture the state information dissemination ability under conditions of dynamic vehicle density. Then, we present a multiagent information dissemination model, in which each vehicle is controlled by a control agent that uses MPC and coordinates with its neighboring agents in order to determine its optimal transmission rate actions. We then design an augmented-Lagrangian-based distributed decision-making scheme to find the optimal transmission rate actions and, at the same time, reach an agreement on fair and efficient channel utilization among the vehicles. Simulation results confirm that the distributed transmission rate control strategy can guarantee fair access to channel resources while achieving the optimal vehicle tracking performance under conditions of dynamic vehicle density.