Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data

Abstract With the raise of implementation of both signalized and ITS intersections at many municipalities around the world, countries such as Germany, USA, Canada and others still use the stop-control (non-signalized) intersections in their traffic network systems. The safety of these non-signalized intersections has been a major concern for researchers and city planners. Therefore, this study aims to investigate the safety in terms of exploring the rear-end conflicts of non-signalized intersections in a Two-way stop intersection in Germany. The Intersection Drone Dataset from an intersection in the city of Aachen in Germany is used to measure traffic conflicts between car-following (leading and following vehicles) when approaching the intersection, then the microscopic variables leading to these conflicts are explored using the random parameter logit model with heterogeneity in means and variances. The results show that there is a concerning number of conflicts over a short period of time at the non-signalized intersection and variables such as the standard deviation velocity of the leading vehicle, the average acceleration of the leading vehicle, the average velocity of the following vehicle, the average acceleration of the following vehicle and the difference of distance between leading and following vehicles are found to be significant. In addition, a new phenomenon, Unnecessary Intended Deacceleration, of car-following events which increases the safety risk at the non-signalized intersection is briefly addressed. The findings of the study underscore the urgent need for proactive intervention strategies to reduce rear-end conflicts at non-signalized intersections.

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Publication Details

Journal
European Transport Research Review
Published
2025-05-06
DOI
https://doi.org/10.1186/s12544-025-00709-w
Citations
3
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
3.91

Funders

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article

Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data

Jieling Jin, Helai Huang, Hanchu Zhou, Hussain A. Nasr
3 citations
European Transport Research Review
Traffic and Road Safety
3.91
article

Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data

Jieling Jin, Helai Huang, Hanchu Zhou, Hussain A. Nasr
article en
3 citations

Abstract

Abstract With the raise of implementation of both signalized and ITS intersections at many municipalities around the world, countries such as Germany, USA, Canada and others still use the stop-control (non-signalized) intersections in their traffic network systems. The safety of these non-signalized intersections has been a major concern for researchers and city planners. Therefore, this study aims to investigate the safety in terms of exploring the rear-end conflicts of non-signalized intersections in a Two-way stop intersection in Germany. The Intersection Drone Dataset from an intersection in the city of Aachen in Germany is used to measure traffic conflicts between car-following (leading and following vehicles) when approaching the intersection, then the microscopic variables leading to these conflicts are explored using the random parameter logit model with heterogeneity in means and variances. The results show that there is a concerning number of conflicts over a short period of time at the non-signalized intersection and variables such as the standard deviation velocity of the leading vehicle, the average acceleration of the leading vehicle, the average velocity of the following vehicle, the average acceleration of the following vehicle and the difference of distance between leading and following vehicles are found to be significant. In addition, a new phenomenon, Unnecessary Intended Deacceleration, of car-following events which increases the safety risk at the non-signalized intersection is briefly addressed. The findings of the study underscore the urgent need for proactive intervention strategies to reduce rear-end conflicts at non-signalized intersections.

European Transport Research ReviewVol. 17(1)
Central South University (CN)
National Natural Science Foundation of China, Central South University, Fundamental Research Funds for Central Universities of the Central South University
Openalex Percentile: Top 8%
Traffic and Road Safety
3.91
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