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This paper proposes a driver assistance system with a collaborative control framework between the human driver and a Collision Avoidance System (CAS) for vehicles on the road while considering the driver drowsiness status. Driver drowsiness detection is performed with two inputs: driver's facial data from a camera mounted in front of the driver and steering wheel data from the car controller system...
This paper considers the problem of controlling an autonomous vehicle that must share the road with human-driven cars.We present proactive collision avoidance algorithms that take into account the expressed intent of human driven cars and minimize the need for sudden braking or other purely reactive sudden actions. The presented algorithm utilizes multi-stage Gaussian Processes (GPs) in order to learn...
This paper proposes the development of a driver assistance framework that allows switching between manual and autonomous driving on a simulated testbed. This testbed is a driving simulator which can create realistic environments and driving experience while enabling both autonomous and manual driving capabilities. The switching between manual and autonomous driving is triggered by the driver drowsiness...
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