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System and method for real world autonomous vehicle trajectory simulation

机译:真实世界自动驾驶轨迹仿真的系统和方法

摘要

A system and method for real world autonomous vehicle trajectory simulation are disclosed. A particular embodiment includes: receiving training data from a real world data collection system; obtaining ground truth data corresponding to the training data; performing a training phase to train a plurality of trajectory prediction models; and performing a simulation or operational phase to generate a vicinal scenario for each simulated vehicle in an iteration of a simulation, the vicinal scenarios corresponding to different locations, traffic patterns, or environmental conditions being simulated, provide vehicle intention data corresponding to a data representation of various types of simulated vehicle or driver intentions, generate a trajectory corresponding to perception data and the vehicle intention data, execute at least one of the plurality of trained trajectory prediction models to generate a distribution of predicted vehicle trajectories for each of a plurality of simulated vehicles of the simulation based on the vicinal scenario and the vehicle intention data, select at least one vehicle trajectory from the distribution based on pre-defined criteria, and update a state and trajectory of each of the plurality of simulated vehicles based on the selected vehicle trajectory from the distribution.
机译:公开了用于现实世界的自主车辆轨迹仿真的系统和方法。一个特定的实施例包括:从真实世界的数据收集系统接收训练数据;以及获取与训练数据相对应的地面真实数据;执行训练阶段以训练多个轨迹预测模型;并执行模拟或操作阶段以在模拟的迭代中为每个模拟的车辆生成附近场景,与不同位置,交通模式或环境条件相对应的附近场景提供与以下数据表示相对应的车辆意图数据:各种类型的模拟车辆或驾驶员意图,生成与感知数据和车辆意图数据相对应的轨迹,执行多个训练的轨迹预测模型中的至少一个,以为多个模拟车辆中的每一个生成预测的车辆轨迹的分布基于附近场景和车辆意图数据的模拟,基于预定标准从分布中选择至少一条车辆轨迹,并基于所选车辆轨迹来更新多个模拟车辆中的每一个的状态和轨迹从分布。

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