Identifying Relative Vehicle Positions via Electronic and Visual Signals

The availability of relative location of nearby vehicles is critical in providing safety alerts to the drivers and enhancing driving experience. However, most of wireless localization techniques either fail to provide sufficient accuracy to identify the relative vehicle positioning or require expensive hardware to achieve high accuracy. To resolve this issue, in this paper we propose E-V relative vehicle positioning. To effectively pair electronic and visual signals, the E-V matching algorithm is used, which can maximize the probability of correct pairing between an vehicle's electronic identity and its visual appearance. To evaluate performance of the E-V relative vehicle positioning, a prototype is built on the Raspberry B+ self-driven car. The conducted experiment results show that E-V relative vehicle positioning system is able to achieve a much better vehicle relative positioning accuracy and the matching result is efficient and stable throughout the experiment.