01628169

Component

https://doi.org/10.3141/2663-13

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.

01653375

17-06048

English

pp 99–108

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309442060

Digital/other

References (42) ; Tables (8)

Automatic data collection systems; Driver performance; Lane changing; Lane occupancy; Rain; Weather conditions

Highways; Safety and Human Factors

TRIS, TRB, ATRI

Dec 8 2016 12:26PM

• Age-Based Simulation of Merging Behavior at Freeway Merging Ramps
• Analyzing and Modeling Drivers’ Deceleration Behavior from Normal Driving
• Automatic Driver Head State Estimation in Challenging Naturalistic Driving Videos
• Comparative Analysis of Toll Plaza Safety Features in Puerto Rico and Massachusetts with a Driving Simulator
• Crash Heterogeneity: Implications for Naturalistic Driving Studies and for Understanding Crash Risks
• Effects of a Change in Environment on the Minimum Time to Situation Awareness in Transfer of Control Scenarios
• Effects of Alert Cue Specificity on Situation Awareness in Transfer of Control in Level 3 Automation
• Examining Potential Confounds in Use of the Detection Response Task for In-Vehicle System Evaluation
• How to Drive Drivers Nuts: Effect of Auditory, Vibrotactile, and Multimodal Warnings on Perceived Urgency, Annoyance, and Acceptability
• Investigating Driver Behavior at Minor-Street Stop-Controlled Intersections in Qatar
• Linking the Detection Response Task and the AttenD Algorithm Through Assessment of Human–Machine Interface Workload
• Modeling Effects of Forward Glance Durations on Latent Hazard Detection
• Modeling of Vehicles Merging Movement at Unsignalized Intersections Considering Drivers’ Risk Perception
• On-Road Visual Sign Salience, Driver Attention Allocation, and Target Detection Accuracy
• Simulator Study of Involuntary Driver Distraction Under Different Perceptual Loads
• Strategies to Assist Drivers in Remaining Attentive While Under Partially Automated Driving: Verification of Human–Machine Interface Concepts