Driverless vehicle local path planning method with time consistency

Abstract

The invention discloses a driverless vehicle local path planning method with time consistency. The method comprises the steps: firstly, vehicle motion differential constraints are increased for a planning path curve, so that a vehicle can track a generated trajectory accurately; secondly, model parameters of a path planning trajectory curve model are promoted, a greater degree of freedom is increased for the planning path, and a curvature constraint problem is conveniently transformed into a mathematical solving optimization problem; and finally, results of periodic optimization before and after the local path method is obtained through periodic optimization solving have large difference, and the problem of jitter of the vehicle during real-time path tracking is caused. A local path planning section is divided into two parts, namely a weak planning section and a strong planning section; the weak planning section is obtained by a strong planning result of a last planning period; throughplanned segmentation, the time consistency of the planning results can be guaranteed, and the local path planning can also have high obstacle avoidance ability.

Description

technical field [0001] The invention belongs to the research field related to local path planning of intelligent vehicles, and relates to a method for local path planning of unmanned vehicles with time consistency. technical background [0002] According to statistics, in 2016, my country's domestic car sales reached 28.028 million, an increase of 13.7% compared to 2015, ranking first in global sales for eight consecutive years. By the end of 2015, the total mileage across the country had reached 4,577,300 kilometers, an increase of 145,000 kilometers year-on-year. The increase in car ownership and the total mileage of roads has led to frequent traffic accidents and serious traffic congestion. Analysis of urban traffic data by experts shows that human factors are the main cause of urban traffic accidents. In view of this, countries all over the world have paid full attention to the Intelligent Transportation System and invested a lot of manpower and material resources in i...

AI Technical Summary

Problems solved by technology

[0006] For the current local path planning methods based on path generation and path selection for unmanned vehicles, the planned curves lack vehicle kinematics constraints, cannot guarantee the accuracy and safety of vehicle path tracking, and rely on optimization solutions to obtain The poor cycle consistency of the local planning path method can easily lead to a step in the planning result that affects the safe driving of the vehicle. A time-consistent local path planning method for unmanned vehicles is proposed.

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