Intelligent networked vehicle state vector calculation method based on vehicle-road information coupling

Abstract

The invention provides an intelligent networked vehicle state vector calculation method based on vehicle-road information coupling. According to the method, a V2X-based multi-lane road segment scene is built, and a vehicle multi-lane space-time trajectory optimization method based on the V2X-based multi-lane road segment scene is designed based on the scene. According to the method, the V2X-basedvehicle space-time trajectory is generated by combining the current state information of the vehicle, the environment information near the vehicle, the signal timing information of the downstream of the road section and the like. According to the method, the space-time track of the passing vehicles in the road section can be optimized and generated in real time according to different road environments and traffic states; the mutual cooperation capability between vehicles is improved, the safety of passing through a road section and the vehicle passing efficiency of an intersection are improved, the energy consumption level of the vehicles is reduced, and a novel solution and a theoretical basis are provided for ensuring the road traffic safety and improving the travel efficiency.

Description

technical field [0001] The invention belongs to the technical field of vehicle-road coordination / arterial traffic flow control, and specifically relates to a method for calculating state vectors of intelligent networked vehicles based on vehicle-road information coupling, which is applicable to any signalized intersection section in an urban road traffic network. Background technique [0002] For the urban traffic road network, the current urban traffic road system controls the traffic flow at the intersection, except for a small number of suburban intersections with small traffic volumes that adopt the self-organizing control method without signals. The intersection is the main node connecting each road section, and the reasonable planning of traffic flow in each road section is also an important part of improving the traffic efficiency of the intersection. The driving behavior of the vehicle during the driving process of the road section can be divided into lane keeping be...

AI Technical Summary

Problems solved by technology

Compared with the single-lane space-time trajectory optimization problem, the multi-lane space-time trajectory optimization problem has higher complexity, and it is difficult to directly solve the multi-lane space-time trajectory optimization problem through the existing lane changing rules

[0013] 2. Traditional routing methods have limited information acquisition capabilities, often rely on fixed traffic detectors, and lack real-time, efficient, and accurate vehicle driving information a

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