Modeling And Verification Of Train Operation Regulation On Bat-Inspired Algorithm

Urban rail transit owns the characteristics of large transportation capacity, low operation cost, Energy-efficient, safe and comfortable and so many other aspects. It is becoming a new vehicle in relieving city’s traffic pressure. The development of train control technology, especially the CBTC system based on the application of wireless communications, largely shorten the interval track of trains and improve the traffic density. However, urban rail transit train suffered interference by random factors extremely during the running, making the original running order deviation from the plan diagram. When the train was delayed slightly by the random factor, it generally can restore orderly operation through extra time set in the follow-up station and interval as quickly as possible. When the train delays too long, it tends to affect the orderly operation of the subsequent trains, causing more trains to be late. Automatic train operation control system needs to adjust the disturbed trains real-time and efficiently, make the trains resume operation according to the plan diagram as soon as possible, achieve the purpose of improving urban rail transit operational efficiency.As an optimization problem of multi-objective under multiple constraints, Train Operation Adjustment has been known as NP-hard (Non-deterministic Polynomial Problem) puzzle in the field of mathematics and computer science. Therefore, it is necessary for us to solve the problem by depth study in the adjustment operation process of urban rail transit, constructing a reasonable operation adjustment model and selecting an efficient and precise algorithm. Based on referencing relevant literatures from domestic and foreign, we analyze the running characteristics of urban rail transit trains, construct an mathematical adjustment model and then simulate the model by using the bats algorithm. Through the analysis of simulation results, it proved that the mathematical model established in the thesis is correct and the optimization method is suitable for solving the adjustment problem of urban rail transit trains.