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

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...

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Main Authors: Xu Qu, Mofeng Yang, Junyi Ji, Linheng Li, Bin Ran
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2021/8823292
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author Xu Qu
Mofeng Yang
Junyi Ji
Linheng Li
Bin Ran
author_facet Xu Qu
Mofeng Yang
Junyi Ji
Linheng Li
Bin Ran
author_sort Xu Qu
collection DOAJ
description 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.
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spelling doaj-art-dca75097aea24848bb64508fbce7cf0f2025-08-20T03:23:55ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/88232928823292Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big DataXu Qu0Mofeng Yang1Junyi Ji2Linheng Li3Bin Ran4School of Transportation, Southeast University, Nanjing, ChinaDepartment of Civil and Environmental Engineering, University of Maryland-College Park, College Park, MD 20742, USASchool of Transportation, Southeast University, Nanjing, ChinaSchool of Transportation, Southeast University, Nanjing, ChinaSchool of Transportation, Southeast University, Nanjing, ChinaVariable 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.http://dx.doi.org/10.1155/2021/8823292
spellingShingle Xu Qu
Mofeng Yang
Junyi Ji
Linheng Li
Bin Ran
Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data
Journal of Advanced Transportation
title Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data
title_full Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data
title_fullStr Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data
title_full_unstemmed Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data
title_short Analyzing the Safety Impacts of Variable Speed Limit Control on Aggregated Driving Behavior Based on Traffic Big Data
title_sort analyzing the safety impacts of variable speed limit control on aggregated driving behavior based on traffic big data
url http://dx.doi.org/10.1155/2021/8823292
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