Abstract
This paper presents a novel methodology for determining the overall highway safety level by integrating statistical analysis and analytic network process (ANP) with set pair analysis (SPA) which is applied in the evaluation of the overall highway safety for the first time. The methodology accounts for both quantitative and qualitative factors that contribute to traffic safety. The statistical analysis uses crash, alignment, intersection, and other data to determine the significant indices (variables) that affect safety. These indices are then combined with the planning (qualitative) indices to determine the weights of all indices based on expert opinions using ANP. Finally, the overall safety level of the highway is determined using SPA. The methodology is illustrated using data collected from two highways in China. The results demonstrate that the proposed methodology is sound and reliable. The methodology is applicable to existing or new highways and can help to effectively evaluate the overall safety of a highway and develop long-term strategies for safety improvements.
Highlights
With the increased mobility on highways, traffic crashes have substantially increased and safety assessment has become increasingly important [1]
The crash was used as the dependent variable, where the index takes a value of 1 if it affects traffic safety and takes a value of zero otherwise
To establish the standard values for assessment grade, the evaluation domain of highway traffic safety was divided into five grades, as previously described
Summary
With the increased mobility on highways, traffic crashes have substantially increased and safety assessment has become increasingly important [1]. Theofilatos [3] adopts Bayesian and finite mixture logit models to predict the likelihood and severity of road accident in urban arterials. Wang and Huang [2] apply Bayesian hierarchical joint model to evaluate road network safety. Christoforou et al [4] use multivariate probit models to examine the relationships between a variety of traffic factors and type of crash. Kweon [7] uses regression analysis with correction for serial correlations to identify factors affecting the changes in traffic safety. These studies are mainly based on “hard data” or quantitative indices, which do not consider the full spectrum of indices that may affect highway safety. There is limited attempt that integrates these methods for evaluating overall highway traffic safety, so as to aid local and national government agencies’ planning decisions for improving traffic safety
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