Modeling commercial vehicle drivers’ acceptance of advanced driving assistance system (ADAS)

Purpose Advanced driving assistance system (ADAS) has been applied in commercial vehicles. This paper aims to evaluate the influence factors of vehicle drivers’ acceptance on ADAS and explore characteristics each key factors. Two most widely used functions, forward collision warning (FCW) lane departure (LDW), were considered this paper. Design/methodology/approach A random forests algorithm was acceptance. data 24 vehicles recorded from 1 November 21 December 2018, Jiangsu province. Respond or not set as dependent variables, while six considered. Findings The rate for FCW LDW systems 69.52% 38.76%, respectively. accuracy model is 0.816 0.820, For system, speed, duration time hour are three Drivers prefer respond a short during daytime low speed. While time, speed driver age Older drivers have higher probability under longer than system. Originality/value Few research studies focused attitudes drivers, though accidents proved be more severe passenger results study can help researchers better understand behavior make corresponding recommendations