Intelligent vehicle lane changing track collaborative planning method based on instantaneous risk assessment

Abstract

The invention discloses an intelligent vehicle lane changing track collaborative planning method based on instantaneous risk assessment. The method comprises the following steps: 1) obtaining trafficbasic data: vehicle motion data, vehicle relative position information, vehicle geometric parameters, road geometric conditions and road surface friction coefficients; 2) collecting motion trails of surrounding vehicles to construct a lane changing sample, and extracting motion characteristics of the surrounding vehicles by using a fuzzy C clustering algorithm; 3) based on the motion characteristics of the surrounding vehicles, predicting the vehicle motion state and the vehicle spacing of the surrounding vehicles at the moment t; 4) establishing a lane change condition safety discrimination model, and deriving a vehicle operation instantaneous risk index by using the parking distance index; 5) taking instantaneous risk minimization as an objective function, and planning transverse and longitudinal movement tracks of the vehicle by utilizing a trapezoidal acceleration method and a genetic algorithm respectively; and 6) realizing a vehicle lane changing track planning function through computer programming. According to the invention, lane changing safety can be recognized in advance, the vehicle lane changing track is planned, and theoretical reference and technical support are provided for a vehicle lane changing track planning system.

Description

technical field [0001] The present invention relates to the technical field of intelligent vehicle lane-changing risk assessment and lane-changing trajectory optimality, in particular to a collaborative planning method for intelligent vehicle lane-changing trajectory based on instantaneous risk assessment. Background technique [0002] Car-following behavior and lane-changing behavior are the two most common driving behaviors when a vehicle is driving on a highway. When the driver intends to perform a lane-changing behavior, the driver needs to consider the distance between the surrounding vehicles, the operating status, the road alignment, and the road usage. A series of traffic environment factors such as traffic conditions and traffic speed limit management, make a reasonable analysis and judgment on whether to execute lane change, when to change lane and how to change lane. Once the driver makes a wrong judgment on the feasibility of safe lane changing, it is very easy t...

AI Technical Summary

Problems solved by technology

After induction, the shortcomings are mainly manifested in: ①Most models only consider the safety of the current traffic environment, and it is difficult to assess the risk of lane change in advance; ②Most models focus on the performance of the lane change trajectory itself, and seldom consider lane change Game relationship between vehicle and surrounding vehicles and their interaction

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