Relationships between Crash Involvement and Temporal-Spatial Driving Behavior Activity Patterns

Author:

Jun Jungwook1,Ogle Jennifer2,Guensler Randall1

Affiliation:

1. School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic Drive, Atlanta, GA 30332-0355.

2. Department of Civil Engineering, Clemson University, 116 Lowry Hall, Clemson, SC 29634-0911.

Abstract

Knowledge about characteristics of crash-involved drivers and their driving performance can enhance countermeasure programs designed to improve safety on roadways. However, few studies have been able to analyze detailed exposure data of individual drivers (travel by time of day and by roadway type) alongside driving performance data (speed, throttle, braking, and acceleration). Thus, researchers have been forced to base safety analyses on aggregate crash experience rather than on more frequent individual driving activities and driving performance parameters. This research evaluated driving exposure and performance differences between drivers who were involved in crashes versus drivers who were not involved in crashes during a 14-month study period, on the basis of data for vehicles with Global Positioning Systems. The objective was to verify whether the exposure of crash-involved drivers and driving performance were significantly different on the basis of disaggregated analyses by facility types and trip start times. Researchers found that the mileage exposure, speed, and acceleration patterns of drivers who were involved in crashes during the study period were significantly different from those of drivers who were not involved in crashes. Further, crash-involved drivers accumulated more mileage, consistently traveled at higher speeds, and engaged more frequently in hard deceleration events than their no-crash counterparts did. Although this study does not definitively correlate driver exposure and performance measures with crash causation, it does suggest that there is real potential to identify at-risk drivers on the basis of data obtained from vehicle-monitoring technologies. The identification and immediate correction of at-risk behaviors could obviate crash experience. If this research is successful, the surrogate measures also would reduce safety analysts' dependency on crash data.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

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