Journal of South China University of Technology(Natural Science Edition)

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Study on the Effect of Complex Horizontal Alignment Combination Design on the Trajectory Offset of Autonomous Vehicles Based on PreScan

WANG Xiaofei1  HUANG Shiqi1  YAO Jiangbei2  ZENG Qiang1   

  1. 1. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, Guangdong, China;

    2. Guangdong Communication Planning& Design Institute Group Co., Ltd, Guangzhou 510635, Guangdong, China

  • Published:2025-03-07

Abstract:

The penetration of automated vehicles (AVs) will gradually increase in the future, and the consequent method of adding Dedicated lanes for AVs to existing roads has become an effective countermeasure to improve roadway efficiency and driving safety. Although the horizontal and vertical alignment are not easy to change due to the constraints of manned vehicles, the width of Dedicated lanes for AVs can be redesigned and optimized. However, there is a lack of standards and calculation basis for the design of self-driving lanes. Autonomous vehicle trajectory offset is an important basis for the design of the width of lanes dedicated to AVs. This study conducts corresponding research on the complex horizontal alignment combination design, which significantly affects the driving trajectory. The typical lateral motion control algorithm and the longitudinal motion control algorithm of AVs, as applied to the PreScan-Simulink simulation platform, are used to consider three complex horizontal alignment combination designs: the oval curve, the convex curve, and the C-shape curve. The objective was to construct simulation vehicle models of car and truck models and road scenarios, and to obtain a characterization of the influence law of horizontal alignment combination design on AV trajectory offset. Additionally, trajectory offset models of car and truck were constructed. This study shows that the feature point with the largest offset for the AV is HY1 on the oval curve and the C-shape curve, but on the convex curve the feature point with the largest offset is HH. The design speed is significantly correlated with the trajectory offsets of AV on each horizontal alignment combination design: the offsets of the feature points with the largest offsets on each design are about [9cm, 16cm] for AV at 60-130 km·h-1; the magnitude of the trajectory offsets varies greatly with the change in design speed, and the offsets of the feature points with the largest offsets on each horizontal alignment combination design are about [13cm, 23cm] for AV at 140-150 km·h-1. The correlation model between design speed and trajectory offset is a quadratic polynomial regression model, and the R2 of the model is greater than 0.95, so the model fit meets the prediction requirements. The research method and research results of this thesis can provide a reference basis for the calculation of dedicated lane width.

Key words: road engineering, dedicated lanes for autonomous vehicle, simulation experiment, trajectory offset