Long-Term Analysis of Driver Behaviour in the Dilemma Zone at a Signalized Intersection

Understanding the relationship between traffic conflict severity and frequency is essential for enhancing road safety measures and implementing effective traffic management strategies. We aim to extend existing research by providing a case study about the comparison of severity and frequency of traffic conflicts occurring at the same location. The theoretical background of our study stems from the conceptual framework, which visualizes the relationship between traffic conflicts and accidents in the form of a pyramid. While this framework provides valuable insights, there remains a research gap of studies that empirically validate and quantify this relationship. Thus, our study seeks to address this gap by utilizing long-term observational data collected from a high-traffic urban intersection. Our research methodology involves the comprehensive analysis of trajectory data obtained from extensive observations conducted over multiple months. Specifically, we focus on a scenario involving unprotected left turns crossing oncoming traffic, a common traffic maneuver associated with a risk of accidents and conflicts. By leveraging advanced data analytics techniques, we aim to identify patterns that are relevant for the conflict. Our results indicate a relationship between the severity and frequency of traffic conflicts. While the number of accidents detected is low, the frequency of minor conflicts and encounters is notably higher. This disparity underscores the importance of refining and standardizing automated conflict detection methods to accurately capture the spectrum of traffic events. Thus, we highlight the need for ongoing research to explore alternative methodologies for conflict detection. In conclusion, our study contributes to the growing body of literature on traffic safety by validating the relationship between severity and frequency of traffic events. Overall, our study confirms the hypothesis that accidents are less frequent than minor conflicts, suggesting potential implications for traffic safety interventions and policy development. https://www.ictct.net/wp-content/uploads/36-Hague-2024/ICTCT2024_paper_41.pdf

Publication Details

Journal
elib (German Aerospace Center)
Published
2025-10-16
Primary Topic
Traffic and Road Safety
Type
article
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article

Long-Term Analysis of Driver Behaviour in the Dilemma Zone at a Signalized Intersection

elib (German Aerospace Center)
Traffic and Road Safety
article

Long-Term Analysis of Driver Behaviour in the Dilemma Zone at a Signalized Intersection

article en

Abstract

Understanding the relationship between traffic conflict severity and frequency is essential for enhancing road safety measures and implementing effective traffic management strategies. We aim to extend existing research by providing a case study about the comparison of severity and frequency of traffic conflicts occurring at the same location. The theoretical background of our study stems from the conceptual framework, which visualizes the relationship between traffic conflicts and accidents in the form of a pyramid. While this framework provides valuable insights, there remains a research gap of studies that empirically validate and quantify this relationship. Thus, our study seeks to address this gap by utilizing long-term observational data collected from a high-traffic urban intersection. Our research methodology involves the comprehensive analysis of trajectory data obtained from extensive observations conducted over multiple months. Specifically, we focus on a scenario involving unprotected left turns crossing oncoming traffic, a common traffic maneuver associated with a risk of accidents and conflicts. By leveraging advanced data analytics techniques, we aim to identify patterns that are relevant for the conflict. Our results indicate a relationship between the severity and frequency of traffic conflicts. While the number of accidents detected is low, the frequency of minor conflicts and encounters is notably higher. This disparity underscores the importance of refining and standardizing automated conflict detection methods to accurately capture the spectrum of traffic events. Thus, we highlight the need for ongoing research to explore alternative methodologies for conflict detection. In conclusion, our study contributes to the growing body of literature on traffic safety by validating the relationship between severity and frequency of traffic events. Overall, our study confirms the hypothesis that accidents are less frequent than minor conflicts, suggesting potential implications for traffic safety interventions and policy development. https://www.ictct.net/wp-content/uploads/36-Hague-2024/ICTCT2024_paper_41.pdf

elib (German Aerospace Center)
Sustainable cities and communities
Openalex Percentile: Top 40%
Traffic and Road Safety
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