Implementation of Driver Behaviors Risk Detection and Safety Alert System in Road Transport Management: A Case Study of Nong Khai Border Checkpoint

This research analyzes the management framework for transnational commercial transport at the Nong Khai border checkpoint.This research aims to create an AI prototype for a cross-border commercial transportation management system by integrating a driver behavior risk identification and safety alert system.This study is a survey investigation that gathers data through a questionnaire.The sample population comprises 400 cross-border transportation operators.The data were examined utilizing descriptive statistics, frequency distribution with percentages, arithmetic mean, standard deviation, and inferential statistics.The technique employs confirmatory factor analysis (CFA) and structural equation modeling (SEM) to assess the alignment of the research model with empirical data (model fit).The model demonstrated consistency with the actual data, evidenced by a Chi-Square value of 70.920, degrees of freedom (df) of 57, significance (Sig.) of 0.102 (more than 0.05), and a CMIN/df ratio of 8.864 (less than 5.0).The analytical findings from the model adjustment indicated that seven indices were consistent, and these statistical values met the necessary criteria.This prototype Module system is designed to assess the effectiveness of cross-border freight services provided by Thai logistics operators and to enhance safety standards and the possibility for effective cross-border transport management between Thailand and Lao PDR.