Automatic driving optimization system and method based on V2V

Abstract

The invention discloses an automatic driving optimization system and method based on V2V, and belongs to the field of intelligent driving. The method comprises the steps: enabling a vehicle to carry out V2V data exchange under a condition that the vehicle is accompanied, and building a distribution map of the accompanied vehicle at a periphery through the information of a lane line where the vehicle is located and the license plate number of the vehicle in front of the lane; receiving the transverse acceleration, the longitudinal acceleration and the deflection angular velocity corresponding to the surrounding vehicles one by one for N seconds, and adjusting a following braking time point and the deceleration of the vehicle according to the longitudinal acceleration of the vehicle in frontof the lane and the transverse acceleration of the vehicle in front of the adjacent lane in an accompanying straight running state so that the following of the vehicle in front is more comfortable; under the condition that lane changing is needed during accompanying, enabling the vehicle to adjust a lane changing triggering condition through the longitudinal acceleration habit of the rear vehicleof the adjacent lane so that lane changing of the vehicle is safer; and under the condition of not being limited by network conditions, matching automatic driving of different styles according to different accompanying vehicles, and updating a real-time automatic driving strategy in a personalized mode.

Description

technical field [0001] The invention belongs to the field of intelligent driving, and more specifically relates to a V2V-based automatic driving optimization system and method. Background technique [0002] The Highway Assist (HWA) / Highway Pilot (HWP) system can automatically control the longitudinal direction and keep the lateral lane on the high-speed road. If there is no risk of collision at the current position and speed, then the HWA / HWP system of the vehicle can support the vehicle to change lanes automatically. [0003] For longitudinal control in HWA, the driver first sets the following distance preference in Adaptive Cruise Control (ACC): far, medium, and close. Then, according to the collision time (Time to Collision, TTC) with the vehicle in front and the road speed limit, the vehicle selects acceleration and deceleration & acceleration and deceleration rate of change according to the parameters calibrated by the OEM to control the acceleration and deceleration o...

AI Technical Summary

Problems solved by technology

[0005] However, the above method has a fixed coefficient and cannot be adapted to surrounding drivers with different driving styles (aggressive or conservative) in the accompanying situation.

For example, the acceleration and deceleration of the vehicle in front is too high each time, and the acceleration change rate is high. If the following distance is set uniformly according to a certain TTC threshold, it will easily lead to excessive braking of the vehicle following the vehicle in the same working condition. The car is close, the TTC is lower than the threshold, and the lane change is delayed or fails due to the sudden acceleration of the car behind

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