Effects of Human Understanding of Automation Abilities on Driver Performance and Acceptance of Lane Change Collision Avoidance Systems

Abstract

Highly sophisticated and reliable driver assistance systems can fail if a driver does not fully understand the functionalities and capabilities of the system. A driving experiment was designed to evaluate how drivers’ understanding of a driving assistance system and its authority impact on safety and performance in critical conditions. Two groups of 24 drivers each had to avoid several impending hazards, while each group received a different type of assistance for avoiding collisions during a lane change: a haptic feedback force through the steering wheel or an automatic steering control. The different assistance systems were applied to different hazards, resulting in significant differences in driver’s reactions and behavior. Collision data showed that both systems were equally efficient when driver’s expectations, system capabilities, and the hazard encountered were in line. More collisions were observed when both systems reached functional limits that were misunderstood by the drivers. However, the impact of these limitations varied, depending on the driver’s ability to retake control and recover the critical situation. The overall driver’s subjective post-hazard assessments were significantly affected by the smoothness of control authority transfer and the types of critical conditions. This indicates the necessity of an adaptive automation that can strike a balance between the processing abilities of the human and the system, and hazardous contexts encountered.