Lane change track optimization and visualization achievement method based on vehicle models and vehicle speeds

Abstract

The invention discloses a lane change track optimization and visualization achievement method based on vehicle models and vehicle speeds. The method includes the following steps of (1) calling whole vehicle models of the four vehicle models in ADAMS software according to the following steps: (1-1) obtaining a whole vehicle structure parameter, and (1-2) obtaining vehicle dynamic characteristics; (2) analyzing tracking errors of an existing lane change track model and extracting lane change track models suitable for different vehicle models and different vehicle speeds; (3) optimizing lane change tracks on the basis of safety and comfort according to the following steps: (3-1) building a driving control DCD file on the basis of a lane change track constraint condition, and (3-2) creating a driver control model and a double-lane three-dimensional road model, creating a driver, road and vehicle simulation system, and obtaining an optimal lane change track after simulation. According to the method, lane change behaviors of a vehicle can be observed dynamically in real time, an intelligent vehicle lane change system is optimized, comfort of drivers is improved, and road driving safety is guaranteed.

Description

technical field [0001] The invention belongs to the field of research and simulation of intelligent transportation, vehicle system dynamics and traffic safety, and in particular relates to a lane-changing track optimization and visualization method based on vehicle types and vehicle speeds. Background technique [0002] Expressways can provide vehicles with a fast, efficient, comfortable and safe driving environment. The traffic flow on the basic road sections is relatively stable, and the traffic capacity and safety service level can generally reach the design level. In the diversion area, the uncertainty of vehicle lane change, speed increase and decrease, and the complex and changeable characteristics of driver behavior complicate the traffic environment in the diversion area and become the bottleneck of expressway speed and safety. According to statistics from the Ministry of Communications, about 30% of high-speed accidents occur in diversion areas and their influence a...

AI Technical Summary

Problems solved by technology

In terms of data acquisition, the principle of close-range photogrammetry is applied, and the ground coordinates can be obtained through linear transformation. This method is easy to operate, and the accuracy of the acquired data is high, but it does not take into account the vehicle type and the dynamic characteristics of the vehicle when changing lanes; In terms of curve fitting, simplified models such as polynomials ignore the curvature changes during vehicle operation, resulting in sudden changes in trajectory curvature that do not match the actual situation

More importantly, it ignores the dynamic characteristics of the vehicle and the comfort and safety of the vehicle when changing lanes, and cannot observe the behavior of vehicles changing lanes in real time.

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