论文标题
使用驱动程序模型在交叉场景中自动驾驶的轨迹计划
Trajectory Planning for Automated Driving in Intersection Scenarios using Driver Models
论文作者
论文摘要
城市交叉点的有效轨迹计划目前是自动驾驶汽车（AV）最具挑战性的任务之一。对其他交通参与者，AV的舒适性及其在环境中的发展是决定轨迹计划算法的性能的关键方面。为了捕捉这些方面，我们提出了一个新颖的轨迹计划框架，以确保社会合规性并同时优化AV的舒适度受运动限制。该框架结合了局部连续优化方法和有效的驱动程序模型，以确保快速行为预测，操纵性生成和决策在长距离上。在不同的情况下评估了所提出的框架，以证明其能力从所得的轨迹和运行时来证明。
Efficient trajectory planning for urban intersections is currently one of the most challenging tasks for an Autonomous Vehicle (AV). Courteous behavior towards other traffic participants, the AV's comfort and its progression in the environment are the key aspects that determine the performance of trajectory planning algorithms. To capture these aspects, we propose a novel trajectory planning framework that ensures social compliance and simultaneously optimizes the AV's comfort subject to kinematic constraints. The framework combines a local continuous optimization approach and an efficient driver model to ensure fast behavior prediction, maneuver generation and decision making over long horizons. The proposed framework is evaluated in different scenarios to demonstrate its capabilities in terms of the resulting trajectories and runtime.
