Cognitive Based Platform for Advanced Driver Assistance Systems

高级驾驶辅助系统的认知平台

• 批准号: RGPIN-2015-05313
• 负责人: Karray, Fakhreddine
• 金额: $ 3.42万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689445
• 关键词: Cognitive; Based; Platform; Advanced; Driver

Major advances are made in the design and development of novel ground transportation infrastructure and intelligent vehicles systems. This is an integral part for building the next generation of intelligent transportation systems involving smart roads and highways, connected vehicles, intelligent sensors and actuators, advanced communication systems and autonomous vehicles equipped with the latest smart mechatronic devices and knowledge based software. At the same time, additional stringent requirements are made by the car manufacturers and insurance industries for achieving best possible performance in terms of fuel efficiency, driving safety, comfort and environment protection. Advanced driver assistance technologies are among the most notable advancements made towards these goals. This market alone is expected to grow to $260 billion by 2020, as the technologies become mainstream not only for luxury and executive vehicles, but also for higher volume product. Transportation authorities in several countries have already mandated such systems and large research budgets have been allocated for the development of next generation advanced driver assistance systems (ADAS).******The proposed research program will investigate and build novel functionalities for a cognitive based ADAS. The system's proposed capabilities should substantially help enhancing the safety and the comfort of the car's occupants, while continuously monitoring the driver's current state, the vehicle's dynamic characteristics and the surrounding environment. To this end, we will develop a context aware based multi-agent system, which accounts for static and dynamic context information involving all types of sensory information coming from the inside and the outside of the car, along with a continuous update on the driver status and the driving environment. To achieve the highest levels of reliability and to infer the most accurate decision-making process, the system must be able to store a wide variety of information, including knowledge from past situations and should possess capabilities for adaptation and driver behavioral learning. Given the various types of sensory signals involved, which need to be interpreted and analysed in real time, an advanced novel approach for multi-modal data and information fusion will be developed as well. ******The proposed program will tackle a number of challenges in the areas of cognitive design, context awareness and data/information fusion. It should lead to real opportunities for the advancement of knowledge pertaining to the design of next generation ADAS and the training of highly qualified personnel, who will advance these technologies through their own research programs, while contributing to the strategically important Canadian automotive and transportation sectors.**

在新型地面交通基础设施和智能车辆系统的设计和开发方面取得了重大进展。这是构建下一代智能交通系统的一个组成部分，涉及智能道路和高速公路，联网车辆，智能传感器和执行器，先进的通信系统以及配备最新智能机电设备和基于知识的软件的自动驾驶汽车。与此同时，汽车制造商和保险业对汽车提出了更严格的要求，以在燃油效率、驾驶安全性、舒适性和环保方面实现最佳性能。先进的驾驶辅助技术是实现这些目标的最显着进步之一。预计到2020年，仅这一市场就将增长到2600亿美元，因为该技术不仅成为豪华和行政车辆的主流，而且也成为更大批量产品的主流。一些国家的交通部门已经强制要求使用这种系统，并为开发下一代高级驾驶员辅助系统（ADAS）分配了大量研究预算。拟议的研究计划将调查和建立基于认知的ADAS的新功能。该系统的拟议功能应大大有助于提高汽车乘员的安全性和舒适性，同时持续监测驾驶员的当前状态，车辆的动态特性和周围环境。为此，我们将开发一个基于上下文感知的多智能体系统，该系统负责静态和动态上下文信息，涉及来自汽车内部和外部的所有类型的感官信息，沿着驾驶员状态和驾驶环境的不断更新。为了实现最高水平的可靠性并推断最准确的决策过程，系统必须能够存储各种信息，包括过去情况的知识，并应具有适应和驾驶员行为学习的能力。考虑到所涉及的各种类型的感觉信号，需要在真实的时间内进行解释和分析，还将开发一种先进的多模态数据和信息融合的新方法。** 拟议的计划将解决认知设计，上下文感知和数据/信息融合领域的一些挑战。它应该为下一代ADAS设计知识的进步和高素质人才的培训带来真实的机会，这些人才将通过自己的研究计划推进这些技术，同时为具有战略重要性的加拿大汽车和运输部门做出贡献。