SBIR Phase I: Risk-Aware Motion Planning for Autonomous Vehicles

SBIR 第一阶段：自动驾驶车辆的风险感知运动规划

• 批准号: 1819302
• 负责人: Peter Howard
• 金额: $ 22.5万
• 依托单位: Realtime Robotics Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-15 至 2018-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1819302&HistoricalAwards=false
• 关键词: SBIR; Phase; Risk; Aware; Motion

The broader impact/commercial potential of this project is to enable autonomous vehicles to make risk-aware decisions at high-speed, by reasoning about the uncertain movements of the people and cars around them to anticipate risks and react defensively. This technology will make new technical approaches to safety and risk viable for the first time. It will enable autonomous cars to drive at regular speeds in dense, highly populated urban environments while reducing the likelihood of accidents - thereby resulting in faster, safer urban autonomous driving. This will increase public trust in autonomous cars and accelerate the development of a new industry which could reshape transportation, freeing people from the need to drive their own cars and increasing their free time and productivity.This Small Business Innovation Research (SBIR) Phase I project aims to develop a specialized processor for risk-aware motion planning for autonomous vehicles. Motion planning is a critical problem for autonomous cars, which must decide how to move through space to reach a designated goal without colliding with a static obstacle, another vehicle, or a pedestrian. Existing approaches can only construct a few plans per second, and assume that the other road-users will continue on their current trajectories. This is acceptable for highways but not for urban driving, where distances are short and other road-users can change behavior suddenly. This project aims to develop a prototype of a specialized motion planning processor that plans in milliseconds, enabling it to consider all likely future movements of other road-users to anticipate risks and react defensively. This proposal aims to evaluate the feasibility of the processor by designing a prototype, demonstrating that it results in safer driving at normal speeds in urban environments, and quantifying its performance improvements over existing solutions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的更广泛的影响/商业潜力是使自动驾驶汽车能够通过推理周围人和汽车的不确定运动来预测风险和防御性反应，以高速进行风险意识。这项技术将首次为安全和风险提供新的技术方法。这将使自动驾驶汽车能够以密集，人口稠密的城市环境的定期速度驾驶，同时减少事故的可能性，从而导致更快，更安全的城市自动驾驶。这将提高公众对自动驾驶汽车的信任，并加速新的行业的发展，该行业可以重塑运输，使人们摆脱需要开车并提高其空闲时间和生产力的需求。这一小型企业创新研究（SBIR）I阶段项目旨在为自动驾驶汽车提供专业的处理器，以开发专业的处理器。运动计划是自动驾驶汽车的关键问题，该汽车必须决定如何在太空中移动以达到指定目标，而不会与静态障碍物，另一个车辆或行人相撞。现有的方法每秒只能构建一些计划，并假设其他公路用户将继续其目前的轨迹。这对于高速公路来说是可以接受的，但对于城市驾驶，距离很短，其他公路用户可以突然改变行为。该项目旨在开发一个专业运动计划处理器的原型，该计划的计划以毫秒为单位，使其能够考虑其他可能的公路用户将来所有可能的运动，以预测风险并做出防御性。该建议旨在通过设计原型来评估处理器的可行性，表明它在城市环境中以正常速度的速度驾驶，并量化其对现有解决方案的绩效改进。该奖项反映了NSF的法定任务，并通过使用该基金会的知识优点和广泛影响来评估NSF的法定任务，并被认为是值得的支持。