Public Transport Dispatching Optimization Based On The Information Of Real-time Passenger Flow

Nowadays, with the rapid growth of urbanization in China, the city's public transport problem has more and more attention of various departments, while the city's traffic congestion is the main problem in Beijing, Shanghai and other large and medium-sized cities.So the intelligent traffic control system has more attention of various cities, intelligent traffic control system can improve the urban traffic congestion, improve the city's impression, and subtly change the way people travel, also to a certain extent, can improve the competitiveness of the city and provide transportation support for the city's future development.This article made some research on the Shenzhen traffic dispatch system; made ? ? a comprehensive exposition on the intelligent transportation system; elaborated my own views on the system of data collection, the system of data processing, short-term passenger flow forecast algorithms and bus dispatch algorithm; creativity made explanation of the passenger traffic collection system, and in the terminal the data is amended to increase the correctness of the system data, in order to improve the reliability of the subsequent algorithm.To take traffic flow as a reference, this article focused on the issue of passenger data processing, took revise algorithm when passenger data is lost, and discussed the practicality of the algorithm in the instance; in the short-term passenger flow forecast, compared the current passenger flow prediction methods and put forward a more suit algorithm for prediction algorithm according to the characteristics of passenger flow data- passenger traffic prediction algorithm based on the nonparametric regression; Finally, took genetic- simulated annealing algorithm in the passenger optimize dispatching model, made the actual application in city bus dispatching of Shenzhen and proved that this model can meet the requirements.