Manual convoying of automated urban vehicles relying on monocular vision

This paper deals with platooning navigation in the context of innovative solutions for urban transportation systems. More precisely, the case of a manually driven vehicle leading a convoy of automated ones is considered. Vehicle localization relies solely on monocular vision: a 3D map of the environment is built beforehand from reference video sequences, and then used to derive vehicle absolute location from the current camera image. The 3D vision map presents however distortions w.r.t. a metric world, but these latter can be shown to be locally homogeneous. They can then be accurately corrected via a 1-dim. function evaluated with a nonlinear observer relying on odometric data. Next, the platoon reference trajectory is built as a B-Spline curve extended on-line via local optimization from the successive locations of the lead vehicle, and a global decentralized control strategy, supported by inter-vehicle communication, is designed to achieve accurate platooning with no oscillation within the convoy. Experimental results, carried out with two urban vehicles, demonstrate the capabilities of the proposed approach.