Computer vision approaches for vehicle sideslip angle estimation

Abstract

Vehicle sideslip angle, defined as the angle between the longitudinal axis of a vehicle and its velocity vector, is a crucial parameter in vehicle dynamics. Unfortunately vehicle sideslip angle is very hard to access directly, therefore a variety of estimation methods have been developed so far. Such estimation methods are essentially based on model-based approaches or neural networks. This paper looks at the problem from a fresh angle, by investigating possible solutions to measure vehicle sideslip angle via computer vision techniques, harnessing recent improvements in computer vision algorithms. Preliminary experiments on a radio-controlled scaled vehicle show promising results using the "phase correlation" algorithm.