The public traffic flow has the gray characteristics of “small sample and poor information”, thereby a forecast method for transfer flow based on the gray soft computing is proposed. This method utilizes the gray system theory to establish gray neural network prediction model, aiming to improve performance of the neural network as well as the accuracy of the system’s prediction by using genetic algorithm. The results show that the optimized model can more accurately predict the traffic flow, providing a more effective way of location selection for public transit transfer hubs. Finally, take the planning of public transit transfer hubs in Lanzhou City as an example to carry out empirical analysis and evaluation for the transfer hubs using this method
In order to improve the security of public traffic, In the road engineering, traffic engineering facilities for basic theory,analyze the factors that affect public transport safety,and then conduct extensive questionnaire,analyze the degree that the major transport facilities affect the safety of traffic,determine the evaluation index and use the analytic hierarchy construct public transport safety evaluation system.Finally,applicate evaluation system to determine the best time for preventive maintenance of road markings,and also provide a new way of thinking for the study of traffic safety.
Research on the Design of Public Traffic Information System