We present our approach, Collision Avoidance Detour (CAD), which won the 3rd place award in the 2023 Waymo Open Dataset Challenge - Sim Agents, held at the 2023 CVPR Workshop on Autonomous Driving. To satisfy the motion prediction factorization requirement, we partition all the valid objects into three mutually exclusive sets: Autonomous Driving Vehicle (ADV), World-tracks-to-predict, and World-others. We use different motion models to forecast their future trajectories independently. Furthermore, we also apply collision avoidance detour resampling, additive Gaussian noise, and velocity-based heading estimation to improve the realism of our simulation result.

翻译：我们提出碰撞规避绕行（CAD）方法，该方法在2023年CVPR自动驾驶研讨会上举办的2023年Waymo开放数据集挑战赛（模拟智能体）中获得了第三名。为满足运动预测分解要求，我们将所有有效对象划分为三个互不相交的集合：自动驾驶车辆（ADV）、待预测世界轨迹及其他世界实体。我们使用不同的运动模型独立预测其未来轨迹。此外，我们还应用碰撞规避绕行重采样、加性高斯噪声和基于速度的航向估计来提升仿真结果的真实性。