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