Drivers’ Lane-Keeping Ability in Heavy Rain: Preliminary Investigation Using SHRP 2 Naturalistic Driving Study Data

Abstract

There is a lack of studies that have examined the impact of weather conditions on drivers’ lane-keeping performance. Many driver behavior studies have been conducted in simulated environments. However, no studies have examined the impact of heavy rain on lane-keeping ability in naturalistic settings. A study used data from the SHRP 2 Naturalistic Driving Study to provide better insights into driver behavior and performance in clear and rainy weather conditions. In particular, a lane-keeping model was developed using logistic regression to better understand factors affecting drivers’ lane-keeping ability in different weather conditions. One interesting finding of this research is that heavy rain can significantly increase the standard deviation of lane position, which is a widely used method for analyzing lane-keeping ability. More specifically, drivers in heavy rain are 3.8 times more likely to show a higher standard deviation of lane position than in clear weather condition. An additional interesting finding is that drivers have better lane-keeping abilities in roadways with higher posted speed. Results from this study could provide a better understanding of the complex effects of weather conditions on drivers’ lane-keeping ability and how drivers perceive and react in different weather conditions. Results from this study may also provide insights into automating the activation and deactivation of lane departure warning systems.