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Trajectory Planning in Traffic Scenarios Using Support Vector Machines

机译:支持向量机在交通场景中的轨迹规划

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摘要

Finding safe and collision free trajectories in an environment with moving obstacles is central for autonomous vehicles but at the same time a complex task. A reason is that the search space in space-time domain is very complex. This paper proposes a two-step approach where in first step, the search space for trajectory planning is simplified by solving a convex optimization problem formulated as a Support Vector Machine resulting in an obstacle free corridor that is suitable for a trajectory planner. Then, in a second step, a basic A* search strategy is used in the obstacle free search space. Due to the physical model used, the comfort and safety criteria are applied while searching the trajectory. The vehicle rollover prevention is used as a safety criterion and the acceleration, jerk and steering angle limits are used as comfort criteria. For simulations, urban environments with intersections and vehicles as moving obstacles are constructed. The properties of the approach are examined by the simulation results.
机译:在有移动障碍物的环境中寻找安全且无碰撞的轨迹对于自动驾驶汽车至关重要,但同时也是一项复杂的任务。原因是时空域中的搜索空间非常复杂。本文提出了一种两步方法,其中第一步是通过解决凸面优化问题简化为轨迹规划的搜索空间,该凸优化问题被公式化为支持向量机,从而形成了适合轨迹规划者的无障碍走廊。然后,在第二步中,在无障碍搜索空间中使用基本的A *搜索策略。由于使用了物理模型,因此在搜索轨迹时会应用舒适性和安全性标准。防止车辆侧翻被用作安全标准,而加速度,加速度和转向角限制被用作舒适度标准。为了进行模拟,构建了以交叉路口和车辆为移动障碍物的城市环境。仿真结果检查了该方法的特性。

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