Urban vehicle platoon using monocular vision: Scale factor estimation

Environment, sustainable development as well as new transportation service emergence in urban areas are major concerns. Consequently, studies are currently intended to automate electric vehicles designed for applications in free access. An additional functionality that appears very attractive is vehicle platooning. In order to avoid oscillations within the fleet when completing this task, a global control strategy, supported by inter-vehicle communications, is investigated. Vehicle absolute localization is then needed and is here derived from monocular vision. These data are however expressed in a virtual vision world, slightly distorted with respect to the actual metric one. It has previously been shown that such a distortion can accurately be corrected on-line in different ways, considering telemetric or odometric data. These strategies have here been refined in order to provide optimal corrections. A comparative study, supported by simulations and full-scale experiments, is reported to exhibit benefits and performances of proposed approaches.