Study On Passenger Travel Route Matching And Impact Of Emergency In Urban Rail Transit Network Based On AFC Data

With the rapid development of urban rail transit, such as Beijing, Shanghai, Guangzhou, the network operation degree becomes more and more complex. In urban rail transit system the passengers can transfer conveniently. Howerer it leads a lot of transfer paths between an OD pair. Therefore, passenger travel path choice becomes more and more complex. Under the situation of "one ticket transfer", accurately and effectively matching the passenger travel route is the basic of ticket income distribution and passenger transport management. Under this background, passenger flow assignment in rail transit network can be used to more accurately reflect passenger flow distribution in rail transit network, which is of great significance for planning and operation management in rail transit network.At present, most of urban rail transit in the world use Automatic Fare Collection (AFC) system to realize the process of passenger self-help enter and exit station. The AFC system can record passenger travel data in the urban rail transit network. Therefore, it is possible for us to match passenger travel route by analyzing the inherent travel information contained in AFC data. This paper firstly study the spatial-temporal distribution of passenger travel in urban rail transit network. Based on this, we analyzed the multi-route choice behavior in urban rail transit network, and proposed an estimation method for solving function of travel time density. To performce this, we divided passenger travel time into two parts:the fixed time in the train and the random time (walking, waiting, etc). Then, we developed a method to match passenger travel route in urban rail transit based on density peak clustering and fuzzy matching. The result showed that the proposal method is more suitable for matching passenger travel path in urban rail transit compared with the method based on travel time distribution in the case study.With the expansion of urban rail transit network, the number of passengers and lines is constantly increasing, which causes the occurance of emergency in urban rail transit network with high probobility. Emergency will cause the adjustment of train operation which will affect the safety in urban rail transit. How to identify passenger flow abnormally and make effective evaluation of the abnormal incident is the basis to make the effective management stratagies and play an important role in the operating of unban rail transit. This paper identifies abnormal passenger flow in urban rail transit based on Bayesian method, and builds a model of the influence of emergency. Then we analyzed the effects of emergency on passenger flow distribution.Finally, we take Beijing rail transit network as a case study to verify the proposed models.