Motorcade intersection obstacle avoidance control method based on multi-level leader pigeon flock theory

Abstract

The invention discloses a motorcade intersection obstacle avoidance control method based on a multi-level leader pigeon flock theory. The method comprises the following steps: 1, establishing a motorcade leader number switching principle; 2, defining the ranges of a risk sensing area and a risk sensing area; 3, determining set division of traffic flow vehicles; 4, calculating a risk coefficient [mu]i of the intelligent vehicle i in the motorcade; 5, determining a secondary leader according to the risk coefficient [mu]i; 6, establishing emergency obstacle avoidance control of the secondary leader; 7, judging whether the secondary leader successfully completes avoidance or not: if so, executing the step 8; 8, establishing navigation control of a secondary leader; 9, establishing avoidance following control of a vehicle behind the secondary leader; 10, enabling the motorcade to pass through the intersection and performing grade returning and switching. According to the invention, the passing efficiency of the intelligent motorcade intersection is improved, the avoidance success rate of the motorcade for intersection emergencies is improved, and the problem that the intelligent motorcade has many dangers when passing through the intersection is solved.

Description

technical field [0001] The invention belongs to the technical field of vehicle network intelligent fleet coordination and emergency obstacle avoidance, and in particular relates to an obstacle avoidance control method for fleet intersections based on the multi-level leader pigeon group theory. Background technique [0002] In order to meet the requirements of safe, efficient, and intelligent transportation development, the multi-vehicle cooperative obstacle avoidance strategy of intelligent networked vehicles has become a hot direction of development and research in recent years. As a typical scene of the urban traffic environment, the intersection is the "throat" of urban traffic, where traffic accidents are extremely prone to occur due to the mixture of people and vehicles and the complex interaction and influence between traffic subjects. The uncertainty and risk of the team's obstacle avoidance at intersections and curves are higher than those in the driving environment ...

AI Technical Summary

Problems solved by technology

But in the complex traffic scene at the intersection, there are various emergencies. When the leader leads the team to turn in the pilot-follow mode, the turning vehicle in the side lane is close to our team or the pedestrians at the intersection are gradually approaching us when passing the intersection. In the case of the square convoy, the convoy will have a greater potential safety hazard and should take different degrees of avoidance behaviors according to the size of the risk factor at the moment. , approaching vehicles and approaching pedestrians cannot pose a threat to the leader, so the original first-level leader cannot take evasive measures

If the approaching vehicle or pedestrians approach the subordinate vehicle in the convoy further, the subordinate vehicle will perform emergency avoidance and have a large heading angle deflection. When the deflection angle exceeds the threshold, the vehicle in front will be lost in the formation, resulting in Loss of formation position, disrupting the entire formation and creating a great risk to following vehicles

[0006] Therefore, when mixed traffic flows such as pedestrians, passing vehicles, and crossing lines in a complex intersection environment pose a greater threat to the fleet, when there is a risk of collision, it is obviously not possible to consider only a single leader's fleet coordination. Ensuring the safe passage of convoys through intersections

Images