Model-Based Synthesis and Safety Assurance of Intelligent Controllers for Autonomous Vehicles

自动驾驶能力有限的汽车已经投放市场，一些汽车制造商承诺，2020年将推出能够在城市环境下自动驾驶的产品。自动驾驶汽车最终将彻底改变汽车行业，以机器人出租车等基于服务的产品取代私家车。大规模自动驾驶车队的部署将减少撞车次数和撞车严重程度，减少排放，让通勤者更有效地利用时间，并释放停放的汽车占用的空间。虽然目前的自动驾驶技术近年来有了很大的进步，但一个主要的挑战是确保自动驾驶汽车在所有交通情况和所有路况下安全和适当地运行。需要新的设计方法和工具来应对这一挑战。*发现基金将资助一个尖端研究计划，为开发安全和智能的基于计算机的自动驾驶汽车控制创造新的方法和工具。预期结果包括(1)控制器设计和相关的机器学习方法，以使控制器能够智能决策和具有类似人类的驾驶技能，以及(2)依赖机器学习的系统的安全保证方法。该项目将使用滑铁卢自动驾驶测试床，这是一种带有集成传感器套件的线控林肯MKZ，并利用安大略省新的自动车辆试点计划在公共道路上演示和评估这项新技术。*自动驾驶汽车将在未来几十年对我们的社会和经济产生重大影响。预计自动驾驶汽车可以将事故率降低高达80%。在加拿大，这将挽救每年1600人的生命，以及超过550亿美元的医疗成本和生产力损失。高盛(Goldman Sachs)预测，无人驾驶技术市场最早将于2025年达到960亿美元。拟议的研究计划针对目前更广泛采用自动驾驶汽车的主要障碍：(1)将无人驾驶汽车和人类驾驶汽车与骑自行车和行人等其他参与者混合在一起的交通智能决策，以及(2)此类系统的安全保证。该计划将产生无人驾驶技术的尖端研究成果，建立一个开放的测试和模拟基准，以刺激科技进步，创造可商业化的技术，并在未来五年内培训13名自动驾驶系统和软件工程方面的HQP。在自动驾驶汽车上的实践经验将使这些HQP在就业市场上获得显着的竞争优势。汽车行业是加拿大制造业GDP的最大贡献者。加拿大在无人驾驶技术方面的创新和HQP培训将有助于保持加拿大在汽车领域的世界领先地位。

Vehicles with limited self-driving capabilities are already on the market and some car makers have promised products capable of autonomous driving in an urban setting in 2020. Self-driving cars will eventually completely transform the automotive industry, replacing private car ownership by service-based products such as robotic cabs. The deployment of large-scale self-driving vehicle fleets will reduce the number of crashes and crash severity, reduce emissions, allow commuters to use their time more effectively, and free up spaces occupied by parked cars. While current self-driving technologies have improved immensely in recent years, a major challenge is assuring safe and appropriate operation of an autonomous vehicle in all traffic situations and all road conditions. New design methods and tools are needed to address this challenge.******This Discovery grant will fund a cutting-edge research program to create new methods and tools for the development of safe and intelligent computer-based controls for self-driving cars. The expected results include (1) a controller design and associated machine-learning methods to enable controllers capable of intelligent decision making and human-like driving skills and (2) methods for safety assurance of systems that rely on machine learning. The program will use the Waterloo Autonomous Driving Testbed, a drive-by-wire Lincoln MKZ with an integrated sensor suite, and take advantage of Ontario's new Automated Vehicle Pilot Program to demonstrate and evaluate the new technology on public roads. ******Self-driving cars will have a major impact on our society and economy over the coming decades. It is expected that self-driving cars can reduce accident rates by as much as 80%. In Canada, this would save 1,600 lives a year and over $55 billion in health costs and lost productivity. Goldman Sachs predicts a driverless technology market of $96 billion as early as 2025. The proposed research program targets current major roadblocks to a wider adoption of self-driving cars: (1) intelligent decision making in traffic that mixes driverless and human-driven cars with other participants such as cyclists and pedestrians and (2) safety assurance of such systems. The program will generate cutting-edge research results in driverless technology, establish an open test and simulation benchmark to stimulate scientific and technological progress, create commercializable technology, and train thirteen HQP in systems and software engineering for autonomous driving over the next five years. Hands-on experience on a self-driving car will give these HQP a significant competitive advantage on the job market. The automotive sector is the single biggest contributor to Canada's manufacturing GDP. Canadian innovation and HQP training in driverless technology will contribute to maintaining Canada's role as a world leader in the automotive sector.