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Developing A New Model for Assessment of Heavy Vehicle-Pedestrian Collisions

Author(s): ORCID

ORCID
Medium: journal article
Language(s): English
Published in: The Baltic Journal of Road and Bridge Engineering, , n. 3, v. 18
Page(s): 102-123
DOI: 10.7250/bjrbe.2023-18.610
Abstract:

The treatment and analysis of accidents involving heavy transport vehicles and pedestrians include the identification and treatment of a certain number of factors that may differ from the cases of passenger vehicle-pedestrian accidents. The aim of this paper is to develop a new model with better performance for speed estimation and reconstruction of accidents involving heavy vehicles and pedestrians. In a large number of cases during the research, it was observed that the experts used the same models for passenger vehicles as for transport vehicles. Likewise, a number of factors that have an impact on heavy vehicle accidents with pedestrians are not included as factors that have an impact on other accidents. The newly developed model, which has better performance than other models, can help experts in the case of analysis, speed determination, and reconstruction of accidents involving heavy vehicles and pedestrians. The model describes more than 94% of the most influential factors in the model (R2 = 0.945). This model will provide a novel way to examine crashes involving heavy vehicles and pedestrians, generating highly precise results for speed calculation which can be used to recreate the technical aspects of the accident. Additionally, it will help specialists in the field when preparing their expert opinion, specifically when heavy vehicles and pedestrians are involved, by providing a model which is different from the standard approach and yields more reliable outcomes.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.7250/bjrbe.2023-18.610.
  • About this
    data sheet
  • Reference-ID
    10743076
  • Published on:
    28/10/2023
  • Last updated on:
    28/10/2023
 
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