A new lateral impact warning system with grey prediction

Vehicle lateral impact is one of the major traffic collision accidents. Usually, this collision accident is caused when the target vehicle appears in the driver's blind spot during lane change or crowded urban travelling and the driver has not carefully observed the approaching vehicle from the rear and side mirrors. Hence, additional sensors need to be installed to measure the relative distance between two closing vehicles for active collision warning purpose. Generally, the lateral distance between two neighbouring vehicles is small compared with longitudinal distance: for crowded city traffic it is less than 1.5 m. It is difficult to estimate accurately or assess the time-to-collision (TTC) based on a single relative distance index between two cars. Here, a novel two-indices TTC decision algorithm is proposed, which can distinguish the safe passing of neighbouring lanes from the essential dangerous lateral collision situation. In addition, the grey prediction theory is introduced to estimate the relative distance of two approaching vehicles one step ahead for TTC estimation to gain additional driver reaction time. The simulation results show that this strategy can create 0.5 s extra time for the driver to take collision avoidance action.