Recognition on trigger condition of autonomous emergency braking system

• Published in: Journal of safety research 2020-02, Vol.72, p.239-247
• Main Authors: Mimura, Yasuhiro, Ando, Ryosuke, Higuchi, Keiichi, Yang, Jia
• Format: Article
• Language: English
• Subjects: Age; Automobiles; Autonomous emergency braking system; Braking; Braking systems; Drivers; Driving ability; Gender; Motor vehicles; Multiple regression models; Multivariate analysis; Multivariate analysis model; Occupational safety; Public relations; Recognition; Regression analysis; Traffic accidents; Traffic accidents & safety; Traffic safety
• ISSN: 0022-4375; 1879-1247
• DOI: 10.1016/j.jsr.2019.12.018

•Female and 65 or older were lower recognition on many of AEBS TCs.•Two multiple regression models were constructed according to the AEBS TCs.•Gender, age, confidence in driving skill are significant variables in both models.•The recognition of the conditions of the AEBS work accidentally was influenced by the interest of cars. Introduction: Automobiles carrying an autonomous emergency braking system (AEBS) are currently prevailing. While the reduction of traffic accidents is expected because of the widespread use of the system, concerns as regards many drivers using the system without proper understanding of the trigger conditions (TCs) have arisen. This research aims to grasp the degree of recognition of the AEBS TCs by a driver with a vehicle equipped with the system. Method: Using a web research company, we sent a survey sheet for screening to 9999 monitors randomly selected by gender and age group and confirmed own vehicle with an autonomous braking system ownership status. The number of answer targets was 200 for each of the four groups divided by age and gender. In this research, we developed a multivariate analysis model with the degree of understanding the AEBS TCs as the objective variable. The explanatory variables of this model were “Driver characteristics” and “Contact opportunities of information on the AEBS.” Results: Using PCA’s main component scores as the objective variable, two types of multiple regression models were constructed according to the AEBS TCs (do not work properly and work accidentally). The model analysis showed that gender, age, confidence in driving skill, and experience of the AEBS before purchasing are significant variables in both models. The recognition of the conditions of the “AEBS does not work properly” was influenced by the information-gathering ability and the degree of reference to various information. In contrast, the recognition of the conditions of the “AEBS work accidentally” was influenced by the interest of automobiles, such as the importance of automobile for self-expression and explanation taken up in a car magazine. Conclusions: This study clarified the driver characteristics and contact opportunities of information that have problems in recognizing the AEBS TCs. Practical Applications: Considering measures, such as public relations, utilizing this result will be meaningful in terms of road safety in the current stage, which is the transitional period of the AEBS.