Unmanned vehicle guiding method and system based on cooperative vehicle infrastructure technology

Abstract

The invention provides an unmanned vehicle guiding method and system based on a cooperative vehicle infrastructure technology, and the method comprises the following steps: S1, obtaining road network abstraction according to structured map data; s2, acquiring passing time of each lane; s3, acquiring connection time between adjacent lanes of the same road section; s4, constructing a directed graph which takes lane numbers as nodes, traffic time as edge weights and connection time as inter-node connection edge weights; s5, acquiring longitude and latitude information of a starting point of the vehicle and longitude and latitude information of a target terminal point, and acquiring a vehicle path planning starting node and a target node; s6, acquiring an optimal path of the vehicle; and S7, controlling the unmanned vehicle to execute the vehicle speed of the optimal path and the path guiding strategy. According to the unmanned vehicle guiding method based on the vehicle-road cooperation technology provided by the invention, the vehicle is controlled through the road, and a guiding method for efficient driving on the premise of ensuring safety is provided for the unmanned vehicle.

Description

technical field [0001] The invention relates to the technical field of intelligent driving, in particular to a method and system for guiding an unmanned vehicle based on a vehicle-road coordination technology. Background technique [0002] With the continuous development of unmanned technology, unmanned vehicles have been able to achieve a high degree of automatic driving, that is, the unmanned system can continuously perform all dynamic driving tasks and automatically execute the minimum risk strategy under its designed operating conditions. However, However, its driving trajectory needs to be collected in advance and cannot be planned autonomously. And when the running trajectories of multiple unmanned vehicles conflict, the vehicles cannot obtain each other's driving information, and they cannot determine the driving intention of other vehicles. For driving safety, the unmanned vehicles will stop at a safe distance from each other. , a deadlock phenomenon will occur. Th...

AI Technical Summary

Problems solved by technology

In recent years, lane-level dynamic path planning for vehicle path guidance has also achieved certain results. Most of the research is based on vehicle positioning technology and vehicle navigation systems, using the shortest path algorithm, and designing different models for different optimal criteria. , to plan the optimal path to assist manual driving, but only stay in the "cloud-car" interaction, and there is no specific point on how to use the planned path to guide the unmanned vehicle, and there is a time delay in the "cloud-car" interaction , can not meet the performance requirements of real-time safe and accurate guidance

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