Literature DB >> 30771589

Powered two-wheeler crash scenario development.

Deniz Atalar1, Pete Thomas2.   

Abstract

Powered two wheeler (PTW) riders are a group of vulnerable road users that are overrepresented compared to other road user groups with regards to crash injury outcomes. The understanding of the dynamics that occur before a crash benefits in providing suitable countermeasures for said crashes. A clearer interpretation of which factors interact to cause collisions allows an understanding of the mechanisms that produce higher risk in specific situations in the roadway. Real world in-depth crash data provides detailed data which includes human, vehicular and environmental factors collected on site for crash analysis purposes. This study used macroscopic on-scene crash data collected in the UK between the years 2000-2010 as part of the "Road Accident In-depth Study" to analyse the factors that were prevalent in 428 powered two-wheeler crashes. A descriptive analysis and latent class cluster analysis was performed to identify the interaction between different crash factors and develop PTW scenarios based on this analysis. The PTW rider was identified as the prime contributor in 36% of the multiple vehicle crashes. Results identified seven specific scenarios, the main types of which identified two particular 'looked but failed to see' crashes and two types of single vehicle PTW crashes. In cases where the PTW lost control diagnosis failures were more common, for road users other than the PTW rider detection issues were of particular relevance.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Crash causation; Human behavior; Human functional failure; Powered two-wheelers

Mesh:

Year:  2019        PMID: 30771589     DOI: 10.1016/j.aap.2019.02.001

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


  2 in total

1.  Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network.

Authors:  Lining Liu; Xiaofei Ye; Tao Wang; Xingchen Yan; Jun Chen; Bin Ran
Journal:  Int J Environ Res Public Health       Date:  2022-05-15       Impact factor: 4.614

2.  Factors affecting driver injury severity in fatigue and drowsiness accidents: a data mining framework.

Authors:  Ali Tavakoli Kashani; Marzieh Rakhshani Moghadam; Saeideh Amirifar
Journal:  J Inj Violence Res       Date:  2022-02-06
  2 in total

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