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This paper presents a computer vision-based approach to tracking surrounding vehicles and estimating their trajectories, in order to detect potentially dangerous situations. Images are acquired using a camera mounted in the egovehicle. Estimations of the distance, velocity and orientation of other vehicles on the road are obtained by detecting their lights and shadow. Because 3D information is not...
This paper presents a model-based algorithm that estimates how the driver of a vehicle can either steer, brake, or accelerate to avoid colliding with an arbitrary object. In this algorithm, the motion of the vehicle is described by a linear bicycle model, and the perimeter of the vehicle is represented by a rectangle. The estimated perimeter of the object is described by a polygon that is allowed...
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