2021/12/17 by Snehanshu Banerjee, Banerjee, Snehanshu, Mansoureh Jeihani +1
Engineering · #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #Robotics (cs.RO) #Traffic Prediction and Management Techniques #Traffic and Road Safety
paper · pdf · doi:10.48550/arxiv.2112.13645
openalex publication_date 2021/12/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With the advent of Advanced Driver Assistance Systems (ADAS), there is an increasing need to evaluate driver behavior while using such technology. In this unique study, a forward collision warning (FCW) system using connected vehicle technology, was introduced in a driving simulator environment, to evaluate driver braking behavior and then the results are validated using data from field tests. A total of 93 participants were recruited for this study, for which a virtual network of South Baltimore was created. A one sample t-test was conducted, and it was found that the mean reduction in speed of 15.07 mph post FCW, is statistically significant. A random forest, machine learning algorithm was found to be the best fit for ranking the most important variables in the dataset by order of importance. Field data obtained from the University of Michigan Transportation Research Institute (UMTRI), substantiated the FCW findings from this driving simulator study.