Cognitive Based Platform for Advanced Driver Assistance Systems

新型地面交通基础设施和智能车辆系统的设计和开发取得重大进展。这是构建下一代智能交通系统的重要组成部分，包括智能道路和高速公路、互联汽车、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，汽车制造商和保险行业对汽车在燃油效率、驾驶安全性、舒适性和环境保护方面的最佳性能提出了额外的严格要求。先进的驾驶辅助技术是实现这些目标最显著的进步之一。预计到2020年，仅这一市场就将增长到2600亿美元，因为该技术不仅在豪华车和行政用车上成为主流，而且在更大批量的产品上也将成为主流。一些国家的交通主管部门已经授权使用这种系统，并为开发下一代高级驾驶员辅助系统（ADAS）分配了大量的研究预算。

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.