Cooperative vehicle formation driving method and system

Abstract

The invention belongs to the field of networking automatic driving of vehicles, and discloses a cooperative vehicle formation driving method and a cooperative vehicle formation driving system. Sensinginformation of vehicles and absolute position information of the vehicles are captured for sensing fusion, path planning and decision-making control, and road environment information of the vehiclesis integrated to implement formation converging, following, quitting, parking and cooperative lane changing co-driving strategies for the vehicles. According to the method and the system, connection of all modules and direct communication between the modules are implemented in a 5G (5th-generation) manner, meanwhile, low-cost vehicle-mounted sensors such as a visual sensor and a millimeter wave radar are additionally arranged, sensing fusion, path planning and decision-making control are integrated into the same software architecture, the road environment information of the vehicles is integrated, and a reliable vehicle formation driving function is realized by a high-accuracy controller. The system is consistent with the development trend of networking vehicle formation driving, high in modulation degree and easy to functionally extend, and by a decentralized following strategy, the influence of uncertainties of network communication can be reduced.

Description

technical field [0001] The invention belongs to the field of vehicle network-connected automatic driving, and in particular relates to a vehicle cooperative formation driving method and system. Background technique [0002] Intelligent networked vehicles refer to equipped with advanced on-board sensors, controllers, actuators and other devices, and integrate modern communication and network technologies to realize the exchange and sharing of intelligent information between vehicles and X (people, vehicles, roads, clouds, etc.), with complex Functions such as environmental perception, intelligent decision-making, and collaborative control can realize "safe, efficient, comfortable, and energy-saving" driving, and finally realize a new generation of vehicles that can replace humans to operate. Vehicle intelligence can be divided into five levels: driver assistance (DA), partially automated driving (PA), conditional automated driving (CA), highly automated driving (HA), and full...

AI Technical Summary

Problems solved by technology

[0006] The current network-connected vehicle formation algorithm can only be used on structured roads with high-precision maps, and the leading vehicle (lead vehicle) is the center, and the car-following strategy is selected according to the status information sent by it. The robustness of the formation model is not strong ; Not combined with a method based on control stability theory to provide a decentralized self-driving multi-vehicle cooperative formation driving

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