DocumentCode :
2517250
Title :
Identification of target populations for current active safety systems using driver behavior
Author :
Kusano, Kristofer D. ; Gabler, Hampton C.
Author_Institution :
Virginia Tech, Blacksburg, VA, USA
fYear :
2012
fDate :
3-7 June 2012
Firstpage :
655
Lastpage :
660
Abstract :
Frontal Pre-Collision Systems (PCS) and Lane Departure Warning (LDW) systems are two of the first active safety systems to penetrate the passenger vehicle market. PCS can warn the driver, amplify the driver´s braking effort, and autonomously brake even if there is no driver input. LDW systems deliver a warning to the driver when the vehicle is drifting out of its lane. The potential effectiveness of these two systems in the field not only depends on the crash scenarios they are likely to activate in but also on driver behavior. This study utilized the National Motor Vehicle Crash Causation Survey (NMVCCS), which unlike traditional databases focuses on behavioral aspects that lead to a collision. The target populations for PCS and LDW were found by aggregating crashes that had a) crash scenarios and b) critical reasons attributed to the collisions that were most likely mitigated by the systems. The warning component of PCS was found to be potentially effective in 45% of applicable crash scenarios. The brake assist and autonomous braking components were potentially effective in 71% and 74% of collisions, respectively. LDW was potentially effective in 18% of road departure collisions. These target populations are not estimates of actual system effectiveness but are quantification of the specific crash and driver scenarios most likely to be mitigated by LDW and PCS.
Keywords :
automated highways; behavioural sciences computing; driver information systems; road safety; road traffic; LDW; NMVCCS; National Motor Vehicle Crash Causation Survey; PCS; autonomous braking components; behavioral aspects; brake assist; current active safety systems; driver assistance systems; driver behavior; driver braking effort; frontal precollision systems; intelligent vehicle systems; lane departure warning systems; passenger vehicle market; road departure collisions; target population identification; Computer crashes; Databases; Injuries; Roads; Safety; Vehicle crash testing; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2012 IEEE
Conference_Location :
Alcala de Henares
ISSN :
1931-0587
Print_ISBN :
978-1-4673-2119-8
Type :
conf
DOI :
10.1109/IVS.2012.6232236
Filename :
6232236
Link To Document :
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