Forward Collision Warning Systems: Validating Driving Simulator Results with Field Data

TL;DR

This study evaluates a forward collision warning system in a driving simulator and validates the findings with real-world field data, demonstrating significant speed reduction and identifying key variables affecting driver response.

Contribution

It introduces a connected vehicle FCW system in a simulator and validates its effectiveness using actual field data, bridging simulation and real-world testing.

Findings

Significant mean speed reduction of 15.07 mph post-FCW

Random forest identified key variables influencing driver response

Field data confirmed simulator results

Abstract

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.