Literature DB >> 19664441

Factors correlated with traffic accidents as a basis for evaluating Advanced Driver Assistance Systems.

Maria Staubach1.   

Abstract

This study aims to identify factors which influence and cause errors in traffic accidents and to use these as a basis for information to guide the application and design of driver assistance systems. A total of 474 accidents were examined in depth for this study by means of a psychological survey, data from accident reports, and technical reconstruction information. An error analysis was subsequently carried out, taking into account the driver, environment, and vehicle sub-systems. Results showed that all accidents were influenced by errors as a consequence of distraction and reduced activity. For crossroad accidents, there were further errors resulting from sight obstruction, masked stimuli, focus errors, and law infringements. Lane departure crashes were additionally caused by errors as a result of masked stimuli, law infringements, expectation errors as well as objective and action slips, while same direction accidents occurred additionally because of focus errors, expectation errors, and objective and action slips. Most accidents were influenced by multiple factors. There is a safety potential for Advanced Driver Assistance Systems (ADAS), which support the driver in information assimilation and help to avoid distraction and reduced activity. The design of the ADAS is dependent on the specific influencing factors of the accident type.

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Year:  2009        PMID: 19664441     DOI: 10.1016/j.aap.2009.06.014

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  6 in total

1.  The increased risk of road crashes in attention deficit hyperactivity disorder (ADHD) adult drivers: driven by distraction? Results from a responsibility case-control study.

Authors:  Kamal El Farouki; Emmanuel Lagarde; Ludivine Orriols; Manuel-Pierre Bouvard; Benjamin Contrand; Cédric Galéra
Journal:  PLoS One       Date:  2014-12-23       Impact factor: 3.240

2.  Research on Target Detection Based on Distributed Track Fusion for Intelligent Vehicles.

Authors:  Bin Chen; Xiaofei Pei; Zhenfu Chen
Journal:  Sensors (Basel)       Date:  2019-12-20       Impact factor: 3.576

3.  Physiological indices and driving performance of drivers at tunnel entrances and exits: A simulated driving study.

Authors:  Jinliang Xu; Xiaodong Zhang; Huan Liu; Kaige Yang; Fangchen Ma; Haoru Li; Yufei Sun
Journal:  PLoS One       Date:  2020-12-17       Impact factor: 3.240

4.  Data-Driven Estimation of a Driving Safety Tolerance Zone Using Imbalanced Machine Learning.

Authors:  Thodoris Garefalakis; Christos Katrakazas; George Yannis
Journal:  Sensors (Basel)       Date:  2022-07-15       Impact factor: 3.847

Review 5.  Review of Studies on Older Drivers' Behavior and Stress-Methods, Results, and Outlook.

Authors:  Yanning Zhao; Toshiyuki Yamamoto
Journal:  Sensors (Basel)       Date:  2021-05-18       Impact factor: 3.576

6.  Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO).

Authors:  Lixin Yan; Yishi Zhang; Yi He; Song Gao; Dunyao Zhu; Bin Ran; Qing Wu
Journal:  Sensors (Basel)       Date:  2016-07-13       Impact factor: 3.576

  6 in total

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