Safety Effectiveness of Variable Speed Limit System in Adverse Weather Conditions on Challenging Roadway Geometry

2015 ◽  
Vol 2521 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Promothes Saha ◽  
Mohamed M. Ahmed ◽  
Rhonda Kae Young
Keyword(s):  
Quantitative Measure ◽  
Weather Conditions ◽  
Speed Limit ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Explanatory Variables ◽  
Safety Performance Function ◽  
Distinct Variable ◽  
Adverse Weather Conditions ◽  
Adverse Weather

This paper examined the interaction between roadway geometric characteristics and adverse weather conditions and their impact on crash occurrence on rural variable speed limit freeway corridors through mountainous terrain. As a quantitative measure of the effect of geometrics in adverse weather conditions, a crash frequency safety performance function that used generalized linear regression was developed with explanatory variables including snow, ice, frost, wind, horizontal curvature, and steep grades. This research concluded that the interaction between grades and horizontal curves with weather variables had a significant impact on crash occurrence. The research suggested that distinct variable speed limit strategies should be implemented on segments with challenging roadway geometry.

Impact of Variable Speed Limit in a Connected Vehicle Environment on Truck Driver Behavior under Adverse Weather Conditions: Driving Simulator Study

2019 ◽  
Vol 2673 (7) ◽  
pp. 132-142 ◽  
Author(s):  
Guangchuan Yang ◽  
Mohamed M. Ahmed ◽  
Sherif Gaweesh
Keyword(s):  
Driving Simulator ◽  
Weather Conditions ◽  
Truck Drivers ◽  
Connected Vehicle ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Advisory Speed ◽  
The Impact

In 2015, the U.S. Department of Transportation (U.S. DOT) selected Wyoming as one of three sites to develop, test, and deploy a suite of connected vehicle (CV) applications on a 402-mi Interstate 80 corridor. One of the Wyoming’s key CV applications is the variable speed limit (VSL) warning, which aimed to provide commercial truck drivers with real-time regulatory and advisory speed limits to help in better managing speeds under adverse weather conditions, and reducing potential speed variances that may cause traffic collisions. This paper developed a driving simulator testbed to assess the impact of the Wyoming’s CV-based VSL (CV-VSL) application on truck drivers’ behavior under adverse weather conditions. A total of 18 professional truck drivers were recruited to participate in the driving simulator experiment. Participants’ instantaneous speeds at various locations were collected to reveal the impact of the CV-VSL warnings on their driving behavior. Simulation results showed that when the advisory speed limits were lower than 55 mph, participants generally followed the VSLs displayed on the CV human–machine interface (HMI). In addition, traffic flows utilizing CV-VSL technology tend to exhibit lower average speeds and speed variances compared with baseline scenarios. These effects of CV-VSL warnings can bring potential safety benefits, as reduction in average speeds and speed variances are effective surrogate measures of safety, that is, lower risk of crashes, under adverse weather conditions.

scholarly journals Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xu Qu ◽  
Mofeng Yang ◽  
Junyi Ji ◽  
Linheng Li ◽  
Bin Ran
Keyword(s):  
Big Data ◽  
Traffic Safety ◽  
Weather Conditions ◽  
Driving Behavior ◽  
Speed Limit ◽  
Variable Speed ◽  
Small Space ◽  
Real World Data ◽  
Variable Speed Limit ◽  
Speed Difference

Variable speed limit (VSL) control dynamically adjusts the displayed speed limit to harmonize traffic speed, prevent congestions, and reduce crash risks based on prevailing traffic stream and weather conditions. Previous research studies examine the impacts of VSL control on reducing corridor-level crash risks and improving bottleneck throughput. However, less attention focuses on utilizing real-world data to see how compliant the drivers are under different VSL values and how the aggregated driving behavior changes. This study aims to fill the gap. With the high-resolution lane-by-lane traffic big data collected from a European motorway, this study performs statistical analysis to measure the difference in driving behavior under different VSL values and analyze the safety impacts of VSL controls on aggregate driving behaviors (mean speed, average speed difference, and the percentage of small space headway). The data analytics show that VSL control can effectively decrease the mean speed, the speed difference, and the percentage of small space headways. The safety impacts of VSL control on aggregated driving behavior are also discussed. The aggregated driving behavior variables follow a trend of first decreasing and then increasing with the continuous decrease in VSL values, indicating that potential traffic safety benefits can be achieved by adopting suitable VSL values that match with prevailing traffic conditions.

Parametric Ordinal Logistic Regression and Non-Parametric Decision Tree Approaches for Assessing the Impact of Weather Conditions on Driver Speed Selection Using Naturalistic Driving Data

2018 ◽  
Vol 2672 (12) ◽  
pp. 137-147 ◽  
Author(s):  
Ali Ghasemzadeh ◽  
Britton E. Hammit ◽  
Mohamed M. Ahmed ◽  
Rhonda Kae Young
Keyword(s):  
Logistic Regression ◽  
Weather Conditions ◽  
Ordinal Logistic Regression ◽  
Speed Limit ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Speed Selection ◽  
Naturalistic Driving ◽  
The Impact ◽  
Non Parametric

The impact of adverse weather conditions on transportation operation and safety is the focus of many studies; however, comprehensive research detailing the differences in driving behavior and performance during adverse conditions is limited. Many previous studies utilized aggregate traffic and weather data (e.g., average speed, headway, and global weather information) to formulate conclusions about the impact of weather on network operation and safety; however, research into specific factors associated with driver performance and behavior are notably absent. A novel approach, presented in this paper, fills this gap by considering disaggregate trajectory-level data available through the SHRP2 Naturalistic Driving Study and Roadway Information Database. Parametric ordinal logistic regression and non-parametric classification tree modeling were utilized to better understand speed selection behavior in adverse weather conditions. The results indicate that the most important factors impacting driver speed selection are weather conditions, traffic conditions, and the posted speed limit. Moreover, it was found that drivers are more likely to significantly reduce their speed in snowy weather conditions, as compared with other adverse weather conditions (such as rain and fog). The purpose of this study was to gather insights into driver speed preferences in different weather conditions, such that efficient logic can be introduced for a realistic variable speed limit system—aimed at maximizing speed compliance and reducing speed variations. This study provides valuable information related to drivers’ interaction with real-time changes in roadway and weather conditions, leading to a better understanding of the effectiveness of operational countermeasures.

Cycle-based variable speed limit methodology for improved freeway merging

2017 ◽  
Vol 11 (10) ◽  
pp. 632-640 ◽  
Author(s):  
Li Zhang ◽  
Lei Zhang ◽  
David K. Hale ◽  
Jia Hu ◽  
Zhitong Huang
Keyword(s):  
Speed Limit ◽  
Variable Speed ◽  
Variable Speed Limit
Sign in / Sign up

Export Citation Format

Share Document