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SIMULATION-BASED METHOD TO EVALUATE PERCEPTION REQUIREMENT FOR AUTONOMOUS DRIVING VEHICLES

机译:基于模拟的自动驾驶汽车知觉要求评估方法

摘要

A system (400) is designed to determine the requirement of a perception range for a particular type of vehicles and a particular planning and control technology. A shadow filter (411) is used to connect a scenario based simulator (413) and a PnC module (412), and tuning the parameters (e.g. decreasing the filter range, tuning the probability of obstacles to be observed among frames) of shadow filter (411) to mimic the real world perceptions with a limited range and reliabilities. Based on the simulation results (e.g., a failure rate, smoothness, etc.), the system is able to determine the required perception distance for the current PnC module (412). A PnC module (412) represents a particular autonomous driving planning and control technology for a particular type of autonomous driving vehicles. Notice that the PnC module (412) is replaceable so that this system is suitable for different PnC algorithms representing different autonomous driving technologies.
机译:系统(400)被设计为确定针对特定类型的车辆以及特定的计划和控制技术的感知范围的要求。阴影过滤器(411)用于连接基于场景的模拟器(413)和PnC模块(412),并调整阴影过滤器的参数(例如,减小过滤器范围,调整要在帧之间观察到障碍物的概率) (411)模仿有限范围和可靠性的现实世界的看法。基于仿真结果(例如,故障率,平滑度等),系统能够确定当前PnC模块所需的感知距离(412)。 PnC模块(412)代表用于特定类型的自动驾驶车辆的特定的自动驾驶计划和控制技术。注意,PnC模块(412)是可替换的,使得该系统适合于代表不同的自动驾驶技术的不同的PnC算法。

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