Literature DB >> 14733981

Analysis of motor-vehicle crashes at stop signs in four US cities.

Richard A Retting1, Helen B Weinstein, Mark G Solomon.   

Abstract

PROBLEM: Nearly 700000 police-reported motor vehicle crashes occur annually at stop signs, and approximately one-third of these crashes involve injuries. The purpose of this study was to develop a better understanding of the crashes that occur at stop signs and to identify potential countermeasures.
METHOD: Police reports of crashes at stop sign-controlled intersections during 1996-2000 in four U.S. cities were examined in detail. At total of 1788 crash reports for intersections with two-way stop signs were included in the study.
RESULTS: Stop sign violations accounted for about 70% of all crashes. Typically these crashes were angular collisions. Among crashes not involving stop violations, rear-end crashes were most common, accounting for about 12% of all crashes. Stop sign violation crashes were classified into several subtypes - driver stopped, driver did not stop, snow/wet/ice, and other/unknown. In about two-thirds of stop sign violation crashes, drivers said they had first come to a stop. In these cases, inability or failure to see approaching traffic often was cited as the cause of the crash. Drivers younger than 18 as well as drivers 65 and older were disproportionately found to be at fault in crashes at stop signs. IMPACT ON INDUSTRY: Potential countermeasures include changing traffic control and intersection design, improving intersection sight distance, and increasing conspicuity of stop signs through supplemental pavement markings and other devices.

Entities:  

Mesh:

Year:  2003        PMID: 14733981     DOI: 10.1016/j.jsr.2003.05.001

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


  4 in total

1.  Augmented reality cues to assist older drivers with gap estimation for left-turns.

Authors:  Michelle L Rusch; Mark C Schall; John D Lee; Jeffrey D Dawson; Matthew Rizzo
Journal:  Accid Anal Prev       Date:  2014-06-18

Review 2.  Translating cognitive neuroscience to the driver's operational environment: a neuroergonomic approach.

Authors:  Monica N Lees; Joshua D Cosman; John D Lee; Nicola Fricke; Matthew Rizzo
Journal:  Am J Psychol       Date:  2010

3.  Investigation of the Contributory Factors to the Guessability of Traffic Signs.

Authors:  Jing Liu; Huiying Wen; Dianchen Zhu; Wesley Kumfer
Journal:  Int J Environ Res Public Health       Date:  2019-01-08       Impact factor: 3.390

4.  Traffic symbol recognition modulates bodily actions.

Authors:  Mayuko Iriguchi; Rumi Fujimura; Hiroki Koda; Nobuo Masataka
Journal:  PLoS One       Date:  2019-03-25       Impact factor: 3.240

  4 in total

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