Bus Arrival Time Estimation Based on GPS Data by the Artificial Bee Colony Optimization BP Neural Network

The problem of vehicle delay is one of the higher complaint rates among the passenger opinions of bus companies, and it is also one of the important reasons why citizens give up choosing public transportation. Estimating bus arrival time is of great significance for improving passenger satisfaction and improving the problem of urban traffic congestion. In this paper, the vehicle GPS data were used to classify the data according to different scenarios, and then the BP neural network was trained and compared with the artificial colony optimization BP neural network. The comparison results show that artificial bee colony optimization BP neural network algorithm is superior to BP neural network algorithm, so we select the better artificial bee colony optimization BP neural network algorithm to establish a vehicle arrival time prediction model.