Control method for merging and changing lanes of intelligent networked vehicles on expressway ramps under mixed traffic conditions

Abstract

The invention discloses a control method for intelligent network-connected vehicles merging and changing lanes on expressway ramps under mixed traffic conditions. The method includes the following steps: collecting road traffic driving information; The safe distance is used to determine whether a lane change decision is made; the vehicle acceleration is adjusted in real time based on the path function of the driving lane change trajectory to achieve a safe lane change. The present invention is based on the realization of related technologies such as intelligent network connection, vehicle-road coordination, etc., according to the environment, traffic and other information of the surrounding roads of a preset range obtained in the communication area, to make decision and judgment of lane change, so as to avoid the occurrence between vehicles when driving the intelligent network connection. Rear-end collision can effectively improve the safety and reliability of automatic driving during lane changing.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a control method for lane change of intelligent network-connected vehicles on expressway ramps under mixed traffic conditions. Background technique [0002] The intelligent networked vehicle uses the on-board system and the road test system to perceive and recognize the surrounding environment of the driving vehicle, analyze and process the acquired information such as vehicle position, traffic signal, road and obstacles, and control the speed and steering of the vehicle to realize the vehicle. Smart driving. The realization of intelligent and connected vehicle technology mainly relies on the integration of multiple assisted driving technologies. A single assisted driving technology can only assist the driver in driving, and the integration of multiple assisted driving technologies can adapt to more scenarios and even all scenarios. of unmanned driving. Accor...

AI Technical Summary

Problems solved by technology

[0007] However, roadside facilities are not comprehensive at this stage, and intelligent networked vehicles have not yet been popularized

In this case, artificial vehicles on the road can only judge the driving state, and cannot obtain specific dynamic driving data

In addition, the time required for conventional lane changes is relatively long, and traffic jams are prone to occur on expressway ramps, especially in mixed traffic conditions. The existing vehicle lane change methods cannot judge the driving behavior of the manual vehicle owner in the target lane. It is impossible to judge the influence of mixed vehicles on vehicle lane change under different driving modes, which may easily lead to wrong decision-making of vehicle lane change

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