Authors
Anurag Pande, Sai Chand, Neeraj Saxena, Vinayak Dixit, James Loy, Brian Wolshon, Joshua D Kent
Publication date
2017/4/1
Journal
Accident Analysis & Prevention
Volume
101
Pages
107-116
Publisher
Pergamon
Description
This paper describes a project that was undertaken using naturalistic driving data collected via Global Positioning System (GPS) devices to demonstrate a proof-of-concept for proactive safety assessments of crash-prone locations. The main hypothesis for the study is that the segments where drivers have to apply hard braking (higher jerks) more frequently might be the “unsafe” segments with more crashes over a long-term. The linear referencing methodology in ArcMap was used to link the GPS data with roadway characteristic data of US Highway 101 northbound (NB) and southbound (SB) in San Luis Obispo, California. The process used to merge GPS data with quarter-mile freeway segments for traditional crash frequency analysis is also discussed in the paper. A negative binomial regression analyses showed that proportion of high magnitude jerks while decelerating on freeway segments (from the driving data …
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