An Arrival Time Prediction Method for Bus System

This letter proposes random neural networks (RNNs) to randomly train several neural network (NN) models for the promotion of traditional NN. Moreover, an arrival time prediction method (ATPM) based on RNNs is proposed to predict the stop-to-stop travel time for motor carriers. In experiments, the results showed that the average accuracies of RNNs are 94.75% for highway and 78.22% for urban road, respectively. Furthermore, the accuracies of the proposed ATPM are higher than previous data mining methods. Therefore, the proposed ATPM is suitable to predict the stop-to-stop travel time for motor carriers.