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Erschienen in:

21.10.2024

Heavy Braking Patterns and their Applicability to Assess Traffic Conflicts

verfasst von: Yawar Ali, K. Ramachandra Rao, Niladri Chatterjee, Ashish Bhaskar

Erschienen in: International Journal of Intelligent Transportation Systems Research | Ausgabe 3/2024

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Abstract

Traffic safety has been a significant concern for ever-increasing injuries and fatalities. The advancement in technology and ITS infrastructure implementation has made traffic data collection and storage easier. This data can be further utilized to identify and suggest measures in preventing potential crashes. Despite the availability of huge vehicle trajectory data sets, assessing potential conflicts by segregating all the leader-follower (LF) pairs often becomes a tedious task. Heavy braking (HB) is a variable that is narrowly explored as a crash surrogate for safety assessment. In this study, the empirical vehicular trajectories are utilized to analyze HB events. HB events are based on the deceleration values of vehicles in the stream exceeding a chosen threshold. The vehicle trajectories are also used to estimate Deceleration Rate to Avoid Collision (DRAC) as a Surrogate Safety Measure (SSM). The empirical microscopic trajectory data for three cities in India, namely, Delhi, Surat, and Chennai, are utilized in this study. This study hypothesized that DRAC events are highly correlated with the heavy braking events within the stream. Thus, this paper attempts to understand the correlation between DRAC and HB events. The R2 value at each site is greater than 0.80, thus suggesting a strong correlation between the heavy braking events and the conflicting DRAC events. HB events can be used as a surrogate safety measure in identifying potential crashes or near misses.

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Metadaten
Titel
Heavy Braking Patterns and their Applicability to Assess Traffic Conflicts
verfasst von
Yawar Ali
K. Ramachandra Rao
Niladri Chatterjee
Ashish Bhaskar
Publikationsdatum
21.10.2024
Verlag
Springer US
Erschienen in
International Journal of Intelligent Transportation Systems Research / Ausgabe 3/2024
Print ISSN: 1348-8503
Elektronische ISSN: 1868-8659
DOI
https://doi.org/10.1007/s13177-024-00433-0

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