Path Analysis Model of Heavy-Duty Vehicle Safety for Road Environment Improvement and Accidents Prevention
DOI:
https://doi.org/10.53848/jlsco.v11i1.271296Keywords:
Path analysis, Heavy-duty vehicle safety, Road environment, Accident preventionAbstract
The 2018 WHO report shows that Thailand has the highest road fatalities and injuries in Asia. This study uses 400 DBQ samples and near-miss data from ADAS and DMS in 246 heavy-duty vehicles to analyze risky driving behaviors from May to July 2022.The research aims to understand the causes of accidents by presenting a safety measurement model in logistics. Each dimension includes the indicators derived from the consensus of the experts, whose backgrounds are in logistics and safety from public and private entities, under the Delphi method. While the methods to evaluate opinions vary upon researchers, without a fixed procedure, the most widely used method is the Delphi method. With the Kendall's W of 0.402 and p-value less than 1, the study has found that there are four dimensions with 15 factors and 55 indicators explaining the topic. The four dimensions: driver behaviors; unsafe road environments; vehicles; and near-miss events, were tested for their correlations among the variables that relate to road accidents with path analysis, a statistical tool to analyze correlations among variables. The result shows that the improvement in unsafe road conditions and driver behaviors is critical to reduce the road accidents in Thailand. Therefore, the path and correlation analysis enhance the understanding on the correlations of each factor. Moreover, the reliability test has found that the absolute fit indices, including the CMIN/DF of 1.26, RMSEA of 0.026, GFI of 0.97, AGFI of 0.95 and RMR of 0.024, are in satisfactory level as well as the incremental fit indices with the NFI of 0.98, CFI of 0.99, TLI of 0.98 and IFI of 0.99. Therefore, the study on the drivers’ behaviors unsafe road environments, vehicles and near-miss events in this research, together with the proposed model, enable responsible authorities to promote road safety by improving environments and driver behaviors as well as planning the strategy to reduce accidents nationwide.
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