未来自动驾驶车辆（AV）的渗透率将逐渐增加，随之而来的在已有道路上增设自动驾驶专用车道成为提高道路通行效率和行车安全的有效对策。平纵线形受有人驾驶车辆的约束不易调整，但AV专用车道的宽度需重新设计，而自动驾驶专用车道设计方面尚缺乏行业标准和计算依据。车辆轨迹偏移量是车道宽度取值的重要依据，针对显著影响行驶轨迹的复杂平曲线组合设计开展相应研究，基于PreScan-Simulink仿真平台，应用典型的AV横、纵向运动控制算法，考虑卵形、凸形和C形3种复杂的平面线形组合，构建不同车型的仿真车辆模型和道路场景，得到了这3种复杂的平面线形组合对AV轨迹偏移的影响规律特征，并构建不同车型的轨迹偏移模型。研究结果表明：AV除了在凸形曲线上偏移最大的特征点是缓缓点（HH点）之外，在卵形曲线和C形曲线上偏移量最大的特征点均是第1个缓圆点（HY1点）。在这3种平面线形组合上设计速度与AV的轨迹偏移量的大小显著相关，AV车速在60~130 km/h时，各平面线形组合最大特征点的偏移量约为9~16 cm；AV车速在140~150 km/h时，轨迹偏移量随设计速度变化幅度较大，各平面线形组合最大特征点的偏移量约为13~23 cm。最后建立的设计速度与轨迹偏移量之间的关联模型为二次多项式回归模型，回归模型决定系数R²均大于0.95，拟合度基本满足预测要求。本研究方法和研究成果可为专用车道宽度的计算提供参考依据。

The penetration of automated vehicles (AVs) is expected to gradually increase in the future. Consequently, adding dedicated lanes for AVs to existing roads has become an effective countermeasure to improve traffic efficiency and driving safety. Although the horizontal and vertical alignment are constrained by human-driven vehicles and difficult to adjust, the width of Dedicated lanes for AVs can be redesigned and optimized. However, there is currently a lack of industry standards and calculation basis for designing such lanes. Vehicle trajectory deviation is a crucial factor in determining lane width. This study focuses on complex horizontal curve combinations that significantly affect driving trajectories. Using the PreScan-Simulink simulation platform, it applied typical AV lateral and longitudinal motion control algorithms and considered three types of complex horizontal curve combinations: oval, convex, and C-shaped. It constructed simulation vehicle models and road scenarios for different vehicle types and analyzed the impact of these complex curve combinations on AV trajectory deviation, ultimately developing trajectory deviation models for various vehicle types. This study shows that, unlike in convex curves where the maximum trajectory deviation occurs at the gentle transition point (HH point), in oval and C-shaped curves, the maximum deviation occurs at the first transition curve point (HY1 point). 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 9~16 cm for AV at 60~130 km/h; 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 13~23 cm for AV at 140~150 km/h. Finally, a polynomial regression model was established to describe the relationship between design speed and trajectory deviation. 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.