Study On The Coordination Of Multiple Intelligent Vehicles For The Local Intelligent Transportation Systems

IV The local intelligent transportation system is an important branch of the intelligent transportation systems (ITS), which providing a new solution to the urban transportation. This system uses fully automated intelligent vehicles as transportation tools, and intends to improve the efficiency and safety of the transportation system; therefore the local intelligent transportation system has become a new concept of the future transport technology. The coordination of intelligent vehicles is critical to ensure the efficiency and safety of the local intelligent transportation system. In this thesis, the coordination problems of intelligent vehicles in the local intelligent transportation system, including the design of coordination architecture, the decision-making, and the control problems, have been studied.The coordination architecture is not only the basis of the coordination of multiple intelligent vehicles, but also the framework for integrating control and decision-making of the coordination. By analyzing the multiple intelligent vehicle coordination problems, the parallel coordination architecture based on the multi-agent systems coordination model has been designed by considering the composition and operating characteristics of the local intelligent transportation system. This coordination architecture integrates the behavior coordination and the task coordination, and can meet the requirements of the multiple intelligent vehicle coordination in local transportation system. Refer to the above mentioned coordination architecture, a multiple intelligent vehicle coordination system for the local intelligent transportation has been realized.The operation of the local transportation system must ensure the safety of intelligent vehicles and the en route operating efficiency of the whole system, which are ensured by the en route behavior coordination. The en route behavior coordination concerns both continuous and discrete states of the intelligent vehicles; therefore a hybrid system based behavior coordination method is proposed, in which the state and behavior of a vehicle agent are described by a hybrid system. The hybrid system model based behavior coordination method can describe the state, intention, and decision-making method of an intelligent vehicle completely, and can realize all the coordination behaviors on the straight lane by synthesizing the basic maneuvers of intelligent vehicles. The validity of the proposed behavior coordination method has been verified in both the multiple intelligent vehicle coordination simulation platform and the relative tests.Platoon is a primary behavior coordination mode of the intelligent vehicles, the control problems must be considered for the platoon. The intelligent vehicle following control model has been established by analyzing different vehicle following distance policies. The platoon stability on the condition of following control has been analyzed. From the interconnected system stability theoretical perspective, the platoon stability based optimal following headway and the corresponding determination methods for this headway have been proposed. Test results show that the optimal following headway determined by the proposed method can ensure the safety and stability of the platoon, and can reduce the inter-vehicle distances.Overtaking is another important mode of the intelligent vehicle coordination, safety and celerity must be ensured in this maneuver. In addition, the overtaking concerns both decision-making and control. An overtaking control method based on conflict probability estimation is proposed, which uses conflict probability as the safety indicator. This method adopts model predict control to track a safe conflict probability, and integrates decision-making and control of overtaking into a tracking control problem, then realizes automotive overtaking with safety and celerity. The performance of the proposed overtaking control method has been validated in the comparative experiments with different configurations.Task coordination is another aspect of the intelligent vehicles'coordination in the local transportation system. The transportation tasks of the local intelligent transportation are distributed, dynamic, and random, therefore the intelligent vehicles should complete these tasks by coordination. To resolve the above problem, a task coordination method based on the multi-agent system coordination model has been proposed. This method uses the"pre-planning, negotiation, re-planning"coordination of multiple agents to complete the transportation task assigning and route planning. The vehicle agents carry out pre-plan according to the local transportation tasks, then initiate negotiation and re-plan on the basis of the pre-plan, thus the distributed task coordination can be completed. The comparative test results show that the proposed multi-agent systems coordination based distributed task coordination is able to adapt to the random and dynamic transportation conditions, and reduce both the average waiting time and the total travel time of passengers significantly.