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Target Population for Intersection Advanced Driver Assistance Systems in the U.S.

Journal Article
ISSN: 2327-5626, e-ISSN: 2327-5634
Published April 14, 2015 by SAE International in United States
Target Population for Intersection Advanced Driver Assistance Systems in the U.S.
Citation: Kusano, K. and Gabler, H., "Target Population for Intersection Advanced Driver Assistance Systems in the U.S.," SAE Int. J. Trans. Safety 3(1):1-16, 2015,
Language: English


Intersection crashes are a frequent and dangerous crash mode in the U.S. Emerging Intersection Advanced Driver Assistance Systems (I-ADAS) aim to assist the driver to mitigate the consequences of vehicle-to-vehicle crashes at intersections. In support of the design and evaluation of such intersection assistance systems, characterization of the road, environment, and drivers associated with intersection crashes is necessary. The objective of this study was to characterize intersection crashes using nationally representative crash databases that contained all severity, serious injury, and fatal crashes. This study utilized four national crash databases: the National Automotive Sampling System, General Estimates System (NASS/GES); the NASS Crashworthiness Data System (CDS); and the Fatality Analysis Reporting System (EARS) and the National Motor Vehicle Crash Causation Survey (NMVCCS).
Straight Crossing Path (SCP), Left Turn Across Path Opposite Direction (LTAP/OD), and Left Turn Across Path Lateral Direction (LTAP/LD) made up 78% to 98% of all crossing path crashes. Furthermore, between 73% and 95% of these top three crossing path scenarios occurred at intersections. The analysis in this paper, therefore, focused on SCP, LTAP/OD, and LTAP/LD crashes at intersections, referred to as simply intersection crashes for the remainder of this summary.
This paper quantified traffic control devices, speed limits, environmental conditions, alcohol involvement, and driver age in intersection crashes. Using the additional driver and crash contributing data included in the NMVCCS data, this paper also quantified critical reason for crashes, maneuvers approaching the intersection and avoidance maneuvers in intersection crashes. The results of this study are crucial for the design and evaluation of I-ADAS.