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首页> 外文期刊>Journal of Field Robotics >Autonomous Driving in Urban Environments: Boss and the Urban Challenge
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Autonomous Driving in Urban Environments: Boss and the Urban Challenge

机译:城市环境中的自动驾驶:老板与城市挑战

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摘要

Boss is an autonomous vehicle that uses on-board sensors (global positioning system, lasers, radars, and cameras) to track other vehicles, detect static obstacles, and localize itself relative to a road model. A three-layer planning system combines mission, behavioral, and motion planning to drive in urban environments. The mission planning layer considers which street to take to achieve a mission goal. The behavioral layer determines when to change lanes and precedence at intersections and performs error recovery maneuvers. The motion planning layer selects actions to avoid obstacles while making progress toward local goals. The system was developed from the ground up to address the requirements of the DARPA Urban Challenge using a spiral system development process with a heavy emphasis on regular, regressive system testing. During the National Qualification Event and the 85-km Urban Challenge Final Event, Boss demonstrated some of its capabilities, qualifying first and winning the challenge.
机译:Boss是一款自动驾驶汽车,它使用车载传感器(全球定位系统,激光器,雷达和摄像机)来跟踪其他车辆,检测静态障碍物并相对于道路模型定位自身。一个三层计划系统将任务,行为和运动计划结合在一起,以在城市环境中行驶。任务计划层考虑要走哪条街道以实现任务目标。行为层确定何时在交叉路口更改车道和优先级,并执行错误恢复操作。运动计划层选择行动,以在实现本地目标的过程中避免障碍。该系统是从头开始开发的,旨在通过螺旋系统开发过程来满足DARPA Urban Challenge的要求,其中特别强调定期进行回归系统测试。在国家资格赛和85公里的城市挑战赛决赛中,Boss展示了其部分能力,首先获得资格并赢得了挑战。

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