01518673

Component

https://doi.org/10.3141/2424-03

http://scholar.google.com...mdar&publication_year=2014

The main objective of this study was to identify near crashes in vehicle trajectory data with interdriver heterogeneity and situation dependency considered. Several efforts have been made to evaluate the effects of near-crash events on safety with the use of naturalistic driving data, driving simulators, and test tracks. However, these efforts have faced some challenges because the observations reflected only the equipped vehicles. The development of connected vehicle technology provided the essential data to study high-risk maneuvers in the entire traffic stream. In this study, two near-crash detection algorithms were proposed. One algorithm had its basis in fixed thresholds, while the other considered interdriver heterogeneity and estimates driver-specific thresholds. The models were tested against two NGSIM trajectory data sets. Initial results showed that consideration of driver preferences resulted in more realistic identification of near crashes than otherwise.

01539592

14-3631

English

pp 20–28

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295093

Print

Figures (7) ; Illustrations; Maps; References (22) ; Tables (5)

Crash risk forecasting; Traffic conflicts; Traffic safety; Vehicle to vehicle communications; Vehicle trajectories

Vehicle infrastructure integration

Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment; I80: Accident Studies

TRIS, TRB, ATRI

Jan 27 2014 3:15PM

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