Improved Situation Awareness with User Intention-Based Lane Change Assistant

Lane change assistance systems increase safety by providing warnings and other stability assistance to drivers to avert traffic dangers. In this contribution, lane change intention recognition was performed and applied to generate warnings for drivers to increase situation awareness and avoid imminent collision. The focus is to evaluate whether utilizing predictions of driver's lane change intentions to provide warnings in the event of imminent collision will result in decreased risk of accidents. It integrates an online Fuzzy-Random Forest (fuzzy-RF) approach with which collision warnings were generated. A total of 44 drivers (39 males and 5 females) among whom 22 experienced the lane change assistance system with intention recognition and corresponding warnings. The experimental and control groups were compared to determine if the intention-based warnings improve driving performance. The results indicate reduced risk of collision and enhanced performance in some lane change scenarios but no significant difference for lane keeping. In addition, the augmented reality head-up display imagery using familiar color schemes and a minimalist layout enable drivers to identify the direction or location of the potential danger without taking their eyes of the road.