Literature DB >> 25662883

Efficacy of roll stability control and lane departure warning systems using carrier-collected data.

Jeffrey S Hickman1, Feng Guo2, Matthew C Camden3, Richard J Hanowski3, Alejandra Medina3, J Erin Mabry3.   

Abstract

INTRODUCTION: Large truck crashes have significantly declined over the last 10 years, likely due, in part, to the increased use of onboard safety systems (OSS). Unfortunately, historically there is a paucity of data on the real-world efficacy of these devices in large trucks. The purpose of this study was to evaluate the two OSSs, lane departure warning (LDW) and roll stability control (RSC), using data collected from motor carriers.
METHOD: A retrospective cohort approach was used to assess the safety benefits of these OSSs installed on Class 7 and 8 trucks as they operated during normal revenue-producing deliveries. Data were collected from 14 carriers representing small, medium, and large carriers hauling a variety of commodities. The data consisted of a total of 88,112 crash records and 151,624 truck-years that traveled 13 billionmiles over the observation period.
RESULTS: The non-LDW cohort had an LDW-related crash rate that was 1.917 times higher than the LDW cohort (p=0.001), and the non-RSC cohort had an RSC-related crash rate that was 1.555 times higher than the RSC cohort (p<0.001).
CONCLUSIONS: The results across analyses indicated a strong, positive safety benefit for LDW and RSC under real-world conditions. PRACTICAL APPLICATIONS: The results support the use of LDW and RSC in reducing the crash types associated with each OSS.
Copyright © 2014 Elsevier Ltd. and National Safety Council. All rights reserved.

Entities:  

Keywords:  Carrier data; Crash; Lane departure warning; Roll stability control; Truck

Mesh:

Year:  2015        PMID: 25662883     DOI: 10.1016/j.jsr.2014.12.004

Source DB:  PubMed          Journal:  J Safety Res        ISSN: 0022-4375


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Journal:  Accid Anal Prev       Date:  2015-09-19

2.  A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.

Authors:  Leandro Vargas-Meléndez; Beatriz L Boada; María Jesús L Boada; Antonio Gauchía; Vicente Díaz
Journal:  Sensors (Basel)       Date:  2016-08-31       Impact factor: 3.576

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Journal:  Sensors (Basel)       Date:  2017-04-29       Impact factor: 3.576

4.  Impact of Road Marking Retroreflectivity on Machine Vision in Dry Conditions: On-Road Test.

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Journal:  Sensors (Basel)       Date:  2022-02-09       Impact factor: 3.576

5.  Haptic Lane-Keeping Assistance for Truck Driving: A Test Track Study.

Authors:  Jeroen Roozendaal; Emma Johansson; Joost de Winter; David Abbink; Sebastiaan Petermeijer
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  5 in total

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