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...

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Main Authors: Hussain A. Nasr, Helai Huang, Jieling Jin, Hanchu Zhou
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:European Transport Research Review
Subjects:
Online Access:https://doi.org/10.1186/s12544-025-00709-w
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author Hussain A. Nasr
Helai Huang
Jieling Jin
Hanchu Zhou
author_facet Hussain A. Nasr
Helai Huang
Jieling Jin
Hanchu Zhou
author_sort Hussain A. Nasr
collection DOAJ
description 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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spelling doaj-art-d8e30b85851a4d8cb6ed03c4dcaa751c2025-08-20T03:09:34ZengSpringerOpenEuropean Transport Research Review1866-88872025-05-011711810.1186/s12544-025-00709-wRear-end conflicts analysis at non-signalized intersection based on vehicles trajectory dataHussain A. Nasr0Helai Huang1Jieling Jin2Hanchu Zhou3School of Traffic and Transportation Engineering, Central South UniversitySchool of Traffic and Transportation Engineering, Central South UniversitySchool of Traffic and Transportation Engineering, Central South UniversitySchool of Traffic and Transportation Engineering, Central South UniversityAbstract 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.https://doi.org/10.1186/s12544-025-00709-wNon-signalized intersectionsRear-end conflictsinD datasetRandom parametersUnnecessary intended deacceleration
spellingShingle Hussain A. Nasr
Helai Huang
Jieling Jin
Hanchu Zhou
Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data
European Transport Research Review
Non-signalized intersections
Rear-end conflicts
inD dataset
Random parameters
Unnecessary intended deacceleration
title Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data
title_full Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data
title_fullStr Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data
title_full_unstemmed Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data
title_short Rear-end conflicts analysis at non-signalized intersection based on vehicles trajectory data
title_sort rear end conflicts analysis at non signalized intersection based on vehicles trajectory data
topic Non-signalized intersections
Rear-end conflicts
inD dataset
Random parameters
Unnecessary intended deacceleration
url https://doi.org/10.1186/s12544-025-00709-w
work_keys_str_mv AT hussainanasr rearendconflictsanalysisatnonsignalizedintersectionbasedonvehiclestrajectorydata
AT helaihuang rearendconflictsanalysisatnonsignalizedintersectionbasedonvehiclestrajectorydata
AT jielingjin rearendconflictsanalysisatnonsignalizedintersectionbasedonvehiclestrajectorydata
AT hanchuzhou rearendconflictsanalysisatnonsignalizedintersectionbasedonvehiclestrajectorydata