Modeling of BRT System Travel Time Prediction Using AVL Data and ANN Approach

Improving the quality of public transportation systems and encouraging passengers to use them are effective solutions for reducing problems in metropolitan. Prediction travel time providing information significant factors this process. In research not only components Bus Rapid Transit (BRT) system were investigated but also an Artificial Neural Network (ANN) model a regression prediction presented. To enhance aim, data was collected by AVL field observation after investigating primary independent variables, ones determined using statistical analysis, then ANN development done. Moreover, linear method used purpose. The results prove that although both models have high level accuracy, outperform accuracy route sections with no signalized intersections is higher than others.