Journal of Advanced Transportation

Surrogate Safety Measures in Traffic Safety Analysis


Publishing date
01 Aug 2021
Status
Closed
Submission deadline
19 Mar 2021

Lead Editor

1Southeast University, Nanjing, China

2McMaster University, Hamilton, Canada

3Tongji University, Shanghai, China

4Wuhan University of Technology, Wuhan, China

This issue is now closed for submissions.
More articles will be published in the near future.

Surrogate Safety Measures in Traffic Safety Analysis

This issue is now closed for submissions.
More articles will be published in the near future.

Description

Traffic safety analysis based on collision data has suffered from the limited availability and relatively poor quality of collision data as well as the long collection period. The use of surrogate safety measures such as the traffic conflict technique (TCT) has been advocated as a proactive and complementary approach to study road safety from a broader perspective than relying on collision-based analysis.

The surrogate safety measures provide a better understanding of collision contributing factors and the failure mechanism that leads to road collisions. In addition, surrogate safety measures are more frequent than road collisions and are of marginal social cost. More importantly, the use of surrogate safety measures in traffic safety analysis avoids the ethical dilemma of waiting for crashes to happen in order to prevent them. This interest is supported by recent advanced technologies such as the use of computer vision, radar, or LiDAR techniques to analyze trajectory data and automatically identify conflicts as well as the use of microsimulation models for estimating surrogate indicators from simulated road user trajectories. Several issues were raised on the use of surrogate safety measures in safety analysis, such as the threshold issue of the surrogate measures, and the validation of the surrogate measures.

This Special Issue aims to present recent research on the use of surrogate safety measures in traffic safety analysis. High quality original research and review articles are welcome. All aspects of statistical analysis, machine learning, traffic simulation, and driving simulator experiments are of interest.

Potential topics include but are not limited to the following:

  • Development of novel surrogate safety measures
  • Application of surrogate safety measures in safety evaluation and analysis
  • Research on safety performance function using surrogate safety measures
  • Before-after safety study using traffic conflicts
  • Surrogate safety measures from traffic simulation
  • Statistical modelling of traffic conflicts
  • Validation of the use of surrogate safety measures for collision prevention
  • Comparison between collision analysis and traffic conflicts analysis
  • Surrogate safety measures of pedestrians and cyclists
  • Application of surrogate safety measures for connected and autonomous vehicles

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 5565343
  • - Research Article

Evaluating the Safety Impact of Connected and Autonomous Vehicles with Lane Management on Freeway Crash Hotspots Using the Surrogate Safety Assessment Model

Hui Zhang | Ninghao Hou | ... | Yan Huang
  • Special Issue
  • - Volume 2021
  • - Article ID 5569143
  • - Research Article

A Dynamic Bayesian Network-Based Real-Time Crash Prediction Model for Urban Elevated Expressway

Xian Liu | Jian Lu | ... | Xiaochi Ma
  • Special Issue
  • - Volume 2021
  • - Article ID 5543114
  • - Research Article

Modeling and Analysis on Minimum Safe Distance for Platooning Vehicles Based on Field Test of Communication Delay

Mengyan Hu | Xiangmo Zhao | ... | Xinrui Zhang
  • Special Issue
  • - Volume 2021
  • - Article ID 5551273
  • - Research Article

Quantification of Rear-End Crash Risk and Analysis of Its Influencing Factors Based on a New Surrogate Safety Measure

Qiangqiang Shangguan | Ting Fu | ... | Shou’en Fang
  • Special Issue
  • - Volume 2021
  • - Article ID 6667688
  • - Research Article

Pedestrian Crash Exposure Analysis Using Alternative Geographically Weighted Regression Models

Seyed Ahmad Almasi | Hamid Reza Behnood | Ramin Arvin
  • Special Issue
  • - Volume 2020
  • - Article ID 6678996
  • - Research Article

Can I Trust You? Estimation Models for e-Bikers Stop-Go Decision before Amber Light at Urban Intersection

Jing Cai | Jianyou Zhao | ... | Jianhua Chen
  • Special Issue
  • - Volume 2020
  • - Article ID 8890351
  • - Research Article

Analysis of Freeway Secondary Crashes in Different Traffic Flow States by Three-Phase Traffic Theory

Bo Yang | Yao Wu | Weihua Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 8824447
  • - Research Article

A Framework for Intersection Traffic Safety Screening with the Implementation of Complex Network Theory

Xueyu Mi | Chunfu Shao | ... | Yan Zheng
Journal of Advanced Transportation
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Acceptance rate36%
Submission to final decision106 days
Acceptance to publication75 days
CiteScore3.400
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.