Study in Jiangsu Province, China Evaluated Commercial Vehicle Drivers’ Acceptance on ADAS Features Using Naturalistic Driving ADAS Data from 12 Buses and 12 Trucks.
Nanjing, China
Modeling commercial vehicle drivers' acceptance of advanced driving assistance system (ADAS)
Summary Information
Advanced Driving Assistance Systems (ADAS) have been widely used in commercial vehicles in recent years to enhance road safety. This study evaluated the influence factors of commercial vehicle drivers’ acceptance on ADAS and explored the characteristics of each of the key factors. Two most widely used ADAS features, namely Forward Collision Warning (FCW) (with 1,706 records) and Lane Departure Warning (LDW) (with 43,221 records) were considered in this study, using data collected in 2018 in Jiangsu Province, China.
METHODOLOGY
In this study, the researchers applied a machine learning algorithm to evaluate the influence factors of commercial drivers’ acceptance. Naturalistic driving ADAS data of 24 commercial vehicles, 12 buses and 12 trucks, were collected from November 1 to December 21, 2018, in Jiangsu province of China. ‘Response’ or ‘No Response’ of the drivers to each of the FCW and LDW features were set as dependent binary variables, while six influence factors related to driver characteristics, vehicle status and road environment, were considered. Specifically, for FCW, the six influence factors included vehicle speed, warning hour, warning duration, road type, driver age group and vehicle type. For LDW, the six influence factors included vehicle speed, warning hour, warning duration, road type, driver age group and weather condition.
FINDINGS
- For FCW, a total of 1,186 driver ‘response’ cases were found among 1,706 total records, translating into a driver acceptance rate of 69.52 percent.
- For LDW, a total of 16,793 driver ‘response’ cases were found among 43,221 total valid records, translating into a driver acceptance rate of 38.76 percent. The researchers attributed this lower acceptance rating compared to the one for FCW to the fact that FCW was being used in more urgent situations.
- Among all six influence factors for FCW, ‘vehicle speed’ was found to be the most important variable. Among all six influence factors for LDW, ‘warning duration’ and ‘vehicle speed’ were found to be the two most important variables.
