Safety risk assessment for intersection rear-end conflicts based on collision risk force indicator

This study introduces a novel method for assessing the risk of rear-end conflicts based on collision risk force indicator. Drawing on the theory of road user safety fields, we construct a collision risk force indicator tailored for rear-end conflict scenarios. By analyzing the impact of driver attributes and vehicle features on risk force, as well as key road environmental factors influencing rear-end accidents, we propose a specific calibration method for the collision risk force indicator. This is further refined using historical accident data for parameter calibration. We then employ the Peak-Over-Threshold (POT) model and utilize the collision risk force values as input indicator to predict the annual average accident frequency. As a case study, we select intersections in Guilin City and extract vehicle trajectory information. The calibrated collision risk force method is applied to obtain accident prediction values for the intersections. The results demonstrate that the predicted annual frequency of rear-end accidents, based on the collision risk force indicator, aligns with the 95% Poisson confidence interval of actual accidents, validating the accuracy of our research method. The calibrated collision risk force indicator serves as a non-accident indicator for evaluating the safety risks of rear-end conflicts at intersections.

Authors

Institutions

Publication Details

Journal
International Journal of Injury Control and Safety Promotion
Published
2025-06-13
DOI
https://doi.org/10.1080/17457300.2025.2512487
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Safety risk assessment for intersection rear-end conflicts based on collision risk force indicator

Shiyi Chen, Chen Wang, Jun Chen, Tao Wang et al.
International Journal of Injury Control and Safety Promotion
Traffic and Road Safety
article

Safety risk assessment for intersection rear-end conflicts based on collision risk force indicator

Shiyi Chen, Chen Wang, Jun Chen, Tao Wang, Chengkun Liu
article en

Abstract

This study introduces a novel method for assessing the risk of rear-end conflicts based on collision risk force indicator. Drawing on the theory of road user safety fields, we construct a collision risk force indicator tailored for rear-end conflict scenarios. By analyzing the impact of driver attributes and vehicle features on risk force, as well as key road environmental factors influencing rear-end accidents, we propose a specific calibration method for the collision risk force indicator. This is further refined using historical accident data for parameter calibration. We then employ the Peak-Over-Threshold (POT) model and utilize the collision risk force values as input indicator to predict the annual average accident frequency. As a case study, we select intersections in Guilin City and extract vehicle trajectory information. The calibrated collision risk force method is applied to obtain accident prediction values for the intersections. The results demonstrate that the predicted annual frequency of rear-end accidents, based on the collision risk force indicator, aligns with the 95% Poisson confidence interval of actual accidents, validating the accuracy of our research method. The calibrated collision risk force indicator serves as a non-accident indicator for evaluating the safety risks of rear-end conflicts at intersections.

International Journal of Injury Control and Safety PromotionVol. 32(3)
Southeast University (BD), Guilin University of Electronic Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 84%
Traffic and Road Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Safety risk assessment for intersection rear-end conflicts based on collision risk force indicator — Shiyi Chen, Chen Wang, et al. · International Journal of Injury Control and Safety Promotion (2025) | TGRS Research Map | TGRS