A review of surrogate safety measures and their applications in connected and automated vehicles safety modeling

C Wang, Y **e, H Huang, P Liu - Accident Analysis & Prevention, 2021 - Elsevier
Abstract Surrogate Safety Measures (SSM) are important for safety performance evaluation,
since crashes are rare events and historical crash data does not capture near crashes that …

Modeling traffic conflicts for use in road safety analysis: A review of analytic methods and future directions

L Zheng, T Sayed, F Mannering - Analytic methods in accident research, 2021 - Elsevier
Limitations of crash data and crash-based methods have given rise to the study of alternate
measures of safety that are not predicated on the occurrence of a crash such as traffic …

Anticipated Collision Time (ACT): A two-dimensional surrogate safety indicator for trajectory-based proactive safety assessment

SP Venthuruthiyil, M Chunchu - Transportation research part C: emerging …, 2022 - Elsevier
Abstract Surrogate Safety Measures (SSMs) are widely used to assess potential crash risk
proactively. Notably, most of the existing safety indicators are fundamentally designed to …

How many are enough?: Investigating the effectiveness of multiple conflict indicators for crash frequency-by-severity estimation by automated traffic conflict analysis

A Arun, MM Haque, S Washington, T Sayed… - … research part C …, 2022 - Elsevier
Traffic conflict techniques are a viable alternative to crash-based safety assessments and
are particularly well suited to evaluating emerging technologies such as connected and …

Data-driven approaches for road safety: A comprehensive systematic literature review

A Sohail, MA Cheema, ME Ali, AN Toosi, HA Rakha - Safety science, 2023 - Elsevier
Road crashes cost over a million lives each year. Consequently, researchers and transport
engineers continue their efforts to improve road safety and minimize road crashes. With the …

Stability analysis and connected vehicles management for mixed traffic flow with platoons of connected automated vehicles

Y Qin, Q Luo, H Wang - Transportation Research Part C: Emerging …, 2023 - Elsevier
Recently, the market has witnessed the emergence of intelligent vehicles equipped with
diverse functionalities. Among these are connected automated vehicles (CAVs) boasting a …

Vehicle trajectory prediction and cut-in collision warning model in a connected vehicle environment

N Lyu, J Wen, Z Duan, C Wu - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Side collisions caused by sudden vehicle cut-ins comprise a significant proportion of traffic
accidents. Due to the complex and dynamic nature of traffic environments, the warning …

Modeling driver's evasive behavior during safety–critical lane changes: Two-dimensional time-to-collision and deep reinforcement learning

H Guo, K **e, M Keyvan-Ekbatani - Accident Analysis & Prevention, 2023 - Elsevier
Lane changes are complex driving behaviors and frequently involve safety–critical
situations. This study aims to develop a lane-change-related evasive behavior model, which …

Lane change detection and prediction using real-world connected vehicle data

H Guo, M Keyvan-Ekbatani, K **e - Transportation research part C …, 2022 - Elsevier
Prediction of lane changes (LCs) provides critical information to enhance traffic safety and
efficiency in a connected and automated driving environment. It is essential to precisely …

Fusing crash data and surrogate safety measures for safety assessment: Development of a structural equation model with conditional autoregressive spatial effect and …

D Yang, K **e, K Ozbay, H Yang - Accident Analysis & Prevention, 2021 - Elsevier
Most existing efforts to assess safety performance require sufficient crash data, which
generally takes a few years to collect and suffers from certain limitations (such as long data …