论文标题
时空钥匙帧对交通模拟的控制，使用粗到限制优化
Spatio-temporal Keyframe Control of Traffic Simulation using Coarse-to-Fine Optimization
论文作者
论文摘要
我们提出了一种新型的交通轨迹编辑方法，该方法使用时空钥匙帧在模拟过程中控制车辆以产生所需的交通轨迹。通过考虑自我激励，遵循和避免碰撞的路径，提出的基于力的交通模拟框架更新了Frenet坐标和笛卡尔坐标中车辆的动作。使用用户的路点，可以通过参考路径计划生成车道级导航。使用给定的键框，提出了粗到五的优化，以有效地生成可满足时空约束的合理轨迹。首先，沿参考路径构建的有向状态图用于通过将键框映射为目标来搜索粗粒轨迹。然后，使用从粗轨迹作为初始化提取的信息，基于基于伴随的优化来生成基于我们基于力的仿真的平滑运动的较好轨迹。我们通过广泛的实验来验证我们的方法。
We present a novel traffic trajectory editing method which uses spatio-temporal keyframes to control vehicles during the simulation to generate desired traffic trajectories. By taking self-motivation, path following and collision avoidance into account, the proposed force-based traffic simulation framework updates vehicle's motions in both the Frenet coordinates and the Cartesian coordinates. With the way-points from users, lane-level navigation can be generated by reference path planning. With a given keyframe, the coarse-to-fine optimization is proposed to efficiently generate the plausible trajectory which can satisfy the spatio-temporal constraints. At first, a directed state-time graph constructed along the reference path is used to search for a coarse-grained trajectory by mapping the keyframe as the goal. Then, using the information extracted from the coarse trajectory as initialization, adjoint-based optimization is applied to generate a finer trajectory with smooth motions based on our force-based simulation. We validate our method with extensive experiments.
