Exploring Critical Factors and Algorithm Development for Predicting Performance Condition of Highway Ditches: A Case Study of Washington State

Highway ditches are critical elements to vehicle safety and overall highway performance. This paper aims to determine critical factors influencing the performance condition of highway ditches and develop a predictive algorithm based on a data-driven approach. By providing a systematic approach to the development of predictive models, the algorithm makes it possible to predict the performance condition of ditches. A two-round questionnaire survey involving professionals from the Washington State Department of Transportation (WSDOT) was used to identify the critical factors affecting roadway ditches. The Relative Importance Index (RII) approach was employed to rank the identified factors in order of significance. To ascertain if the gathered dataset was normally distributed, the SPSS Kolmogorov–Smirnov and Shapiro–Wilk tests were run. Mann–Whitney U tests were run to ascertain group differences. According to the test results, the top 17 factors—also known as critical factors—were scored statistically considerably higher than the 18th factor. Including the critical factors, an algorithm was developed to predict the performance condition of roadway ditches. The study's findings help highway agencies develop prediction tools to improve ditch performance that makes public transportation safer.