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 …

A review of surrogate safety measures Uses in historical crash investigations

D Nikolaou, A Ziakopoulos, G Yannis - Sustainability, 2023 - mdpi.com
Historical road crash data are the main indicator for measuring road safety outcomes. Over
the past few decades, significant efforts have been made in obtaining and exploiting …

Application of explainable machine learning for real-time safety analysis toward a connected vehicle environment

C Yuan, Y Li, H Huang, S Wang, Z Sun… - Accident Analysis & …, 2022 - Elsevier
Due to the difficulty of obtaining traffic flow data and conflicts simultaneously, conflict-based
analysis using macroscopic traffic features is much less studied. This research aims to …

Application of surrogate safety measures in higher levels of automated vehicles simulation studies: A review of the state of the practice

P Tafidis, A Pirdavani - Traffic injury prevention, 2023 - Taylor & Francis
Abstract Objective Surrogate safety measures (SSMs) are developed and applied as
alternatives or complements of safety analyses mainly due to important road crash data …

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

H Guo, K Xie, 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 …

A multidimensional and multi-period analysis of safety on roads

MA Martins, TV Garcez - Accident Analysis & Prevention, 2021 - Elsevier
This paper proposes a multidimensional and multi-period analysis of safety on roads. It
aggregates different road safety performance indicators observed over different periods for …

Predicting hurricane evacuation behavior synthesizing data from travel surveys and social media

T Bhowmik, N Eluru, S Hasan, A Culotta… - … Research Part C …, 2024 - Elsevier
Evacuation behavior models estimated using post-disaster surveys are not adequate to
predict real-time dynamic population response as a hurricane unfolds. With the emergence …

Spatial predictions of harsh driving events using statistical and machine learning methods

A Ziakopoulos, E Vlahogianni, C Antoniou, G Yannis - Safety science, 2022 - Elsevier
Harsh driving behavior events, such as harsh braking events (HBs) are road safety
surrogate measures showing promising research venues towards crash mitigation, such as …

Proactive safety monitoring: A functional approach to detect safety-related anomalies using unmanned aerial vehicle video data

D Yang, K Ozbay, K Xie, H Yang, F Zuo… - … research part C: emerging …, 2021 - Elsevier
The advent of smart cities has motivated the field of transportation safety to transition
towards a proactive approach that anticipates and mitigates risks before crashes occur. One …

Bayesian spatial correlation, heterogeneity and spillover effect modeling for speed mean and variance on urban road networks

Y Zhou, X Jiang, C Fu, H Liu, G Zhang - Accident Analysis & Prevention, 2022 - Elsevier
Analyzing speed mean and variance is vital to safety management in urban roadway
networks. However, modeling speed mean and variance on structured roads could be …