Selected studies on intelligent driver assistance systems

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The alarming worldwide statistics on traffic accidents suggest that human drivers are very much error-prone and are the main culprit to traffic accidents. Intelligent transportation as an umbrella vision and technology advocates that incorporating automation and building intelligent infrastructure increases the capacity and efficiency of highways and roads significantly and reduces the number of accidents. As human drivers are the single most contributing factor in causing traffic accidents, it is sensible to think that redefining the role of the human driver could be part of the final solution. This, of course, implies gradual diminishing of the role of the human from driving the car to supervising the task of driving. However, this imposes a multifaceted approach and solutions that complement each other. In this research proposal, we will focus on selected questions within this wide domain. We will study assisted driver systems, model human drivers, and develop intelligent situation awareness algorithms. In order to evaluate the effectiveness of the control strategies, an existing state-of-the art simulation platform will be used to conduct realistic experiments not on the roads but within the safe confine of a virtual environment. We will also address overriding driving systems for intoxicated drivers. The project duration is estimated to last five years and train three to five highly qualified personnel. Among the project outcomes are novel solutions to assist human drivers that ultimately lead to reducing injuries and loss of life due to traffic accidents. It is envisaged that the outcome of the project benefits Canada and the findings has an international impact.