Grant: Strategic Projects - Group

Inclusion of new embedded technologies in vehicular applications is precluded by several constraints and requirements among which optimizing solutions and finding trade-offs between 1) safety, 2) low-cost, 3) manufacturability, 4) environment friendliness 5) and standard policies and regulations. In the proposed project we intend to put emphasis on the safety aspects of the requirements while keeping in mind the other issues. One of the major concerns related to the introduction of new technologies in vehicular applications is safety. Apart from HMIs (Human Machine Interfaces) and driver's distraction issues, safety is directly related to the level of reliability and robustness of the sensors and systems involved. In fact, one of the major challenges in industry is to achieve and guarantee a very high level of reliability and robustness of on-board equipments to insure sufficient safety at a cost low enough to enable large deployment and mass production in the automotive industry. One of the main objectives of this proposal is to determine how we can improve those reliability and robustness aspects of the embedded systems and sensors which are becoming ubiquitous, more numerous and more complex over time. As the number of sensors and systems increases, the challenge of insuring sufficient reliability and thus a high level of safety is becoming overwhelming. In addition, vehicular environment is highly dynamic and thus requires a high level of connectivity , which in turn requires reliability and robustness as well. Robustness is linked to the capability of the systems to adapt and adjust their performance/behaviour according to the situation and environment at hand. These adaptation and learning capabilities are directly related to safety as well. We have in mind to explore and develop intelligent signal and information processing tools to take advantage of the presence of multiple vehicles and inter-vehicles communications capabilities to gather information from multiple sources, validate individual data pieces, assess their level of uncertainty and exploit potential redundancies in order to mitigate risk of unexpected failures and optimize reliability and robustness.