Research On Model And Algorithm Of The Automatic Train Regulation System In Urban Railway

With the rapid development of China’s rail transit technologies and their popularization in each big city, most citizens increasingly prefer the efficient and comfortable urban rail transit. In recent years, as the CBTC system has substituted the traditional CBTC system as the controlling technology for train operation, the trains have increased their departure frequency and shortened the intervals between each departure, thus largely enhanced the running frequency of the trains. However, this progress has put forward new requirements for the tolerance of delay. Rail transit is often operated according to prescribed schedules, which include times of arrival and departure as well as durations of stops. Once delays happen due to some accidental factors, it is very likely that relevant schedules will be disordered, causing turbulent operation that impacts running efficiency and disturbing passengers’ travel plans. Therefore, how to bring delayed trains back on schedule with the least negative influence has become a hot topic in the research of the control technology of urban rail transit.As an important subsystem of ATS, ATR shows prominent performance in handling delays. ATR can bring delayed trains back on schedule after some time or miles of running by adjusting the time of stop at each station with some strategies, without affecting the security of operation. However, on one hand, ATR adjusting strategies of each of the world’s major urban rail transit systems differ according to different situations of lines or operation; on the other hand, the adjustment of trains is getting more and more difficult with the rapid development of modern cities, the increasing urban population and the shortening intervals of operation. All these are endowing the issue of train adjustment with new significance for research.Firstly, based on the reasons and influence of delayed trains, this essay analyzes the basic approaches for adjusting the delay. Then, by discussing the optimization objectives of delayed trains, it establishes an improved model for automatic adjustment in combination with the traditional model. On this basis, a model solution based on mixed DESA algorithm is put forward according to the difficulties with adjustment and the characteristics of the model, and a specific explanation is made about the process of model solution. In the end, taking the real operational situation of Chengdu Subway Line 1 as an example, the essay constructs a simulation platform for automatic adjustment and GIS platform for train operation simulation based on operation diagram. Further, the essay tests the performance of the adjustment plans it puts forward by imitating single train delay and propagated delay. The result proves the practicability and good performance of the improved adjustment model and the DESA algorithm in adjusting delayed CBTC trains back on schedule.