Vehicle automation (even SAE level 1 automated systems) can substantially increase traffic safety, reduce road fatalities/injuries, and improve traffic flow and efficiency. Despite these benefits of automated systems, their acceptance and usage are low among drivers. The current state-of-the-art automated systems such as Adaptive Cruise Control and Lane Keeping Assist follow pre-defined comfort and safety margins for controlling the longitudinal and lateral motion of the vehicle, which are not adequate to distinguish between similar-looking events. In contrast, the driver can recognize and anticipate such upcoming situations and accordingly adapts his behavior. The foremost requirement for enhancing drivers' comfort, trust, and acceptance is to understand situations where automated systems behave differently from human drivers and, subsequently, determine how such behavioral differences can be resolved safely and comfortably. This paper addresses this gap by studying the behavior of Adaptive Cruise Control and Lane Keeping Assist in contrast with the human driver in a real-life highway environment. A four-step design approach is presented for Adaptive Cruise Control and Lane Keeping Assist based on the identified events of interest, facilitating anticipative behavior for them similar to human drivers. The applicability of the design approach is demonstrated using a virtual scenario created using Simcenter Prescan and Matlab Simulink. The scenario showcases the dynamic lane positioning behavior of modified Lane Keeping Assist that can adapt the vehicle lane position within a 1.2% of the human driver in the presence of vehicles in the adjacent lanes.
Towards A Human-centric Design Solution for Automated Systems to Enhance Driver's Comfort and Acceptance
2021-10-07
805638 byte
Conference paper
Electronic Resource
English
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