Passenger Route Identification of Rail Transit Based on AFC Data

2017 2nd International Conference on Artificial Intelligence and Engineering Applications (AIEA 2017) ISBN: 978-1-60595-485-1 Passenger Route Identification of Rail Transit Based on AFC Data RUILI ZHAO, ZHIZHONG ZHANG and JIE ZHU ABSTRACT In view of the problem of passenger route identification in the complex urban rail transit network, taking into account that the IC card only records passenger's travel time, the entry and exit station information, without recording the specific information of the stations they passed, therefore, to infer passenger's travel route, a passenger route identification scheme based on AFC data is designed in this paper, which based on the analysis of the main factors influencing the passengers' route choice and their route choice behavior. Firstly, the collected AFC data was preprocessed; Secondly, according to the main factors influencing passenger's route choice, the most possible routes were screened out; Then the time training between entry and exit stations was carried out, and passengers' travel routes were selected according to the entry time and exit time; Finally, taking the Chongqing rail transit network as an example, the route identification scheme designed in this paper was verified by actual survey data. The result shows that the accuracy of route identification was 76.2%, and the travel route obtained by the scheme has high accuracy , which proves the feasibility of the scheme. KEYWORDS Prediction model Track IC card, Data mining, Path identification, K shortest path. INTRODUCTION Recent years, as the urban rail transit is developing quickly, the flexibility of passenger's travel condition has improved significantly, meanwhile, it enhances the complexity of passenger's travel path selection. AFC (Automated Fare Collection) system technology emerged. The use of the AFC system significantly reduces the flow of passenger cash, and increases the efficiency of subway operations. In addition, the extensive application of the seamless transfer mode makes it convenient for passenger's transfer, but at the same time the AFC system only obtains the OD (Origin Destination) information of the passenger's travel. It is helpless for the detailed understanding of the passengers' specific route in the orbit network. The accuracy of passenger's travel route identification is significant, as for ticketing points, subway emergency management, passenger travel path induction, passenger flow forecast, and these all need an accurate grasp of the passenger s traveling route. _________________________________________ Ruili Zhao, [email protected], Zhizhong Zhang [email protected], Jie Zhu, [email protected], Chongqing University of Posts and Telecommunications, Chongqing 400065, China 516 At present, relevant research on the route choice of rail transit passengers are: In the literature [1]-[4], Naohiko and Hibino et al studied the influencing factors of passenger travel choice and the law of route selection in the rail transit system based on RP passenger flow survey. In the literature [5]-[7], Bingfeng Si et al proposed a general path selection behavior model based on generalized cost, and analyzed the optimization algorithm of passenger flow distribution of rail transit. This paper analyzes the main influencing factors of the urban passenger flow distribution, then puts forward the theoretical model for the distribution problem, and designs the corresponding algorithm to verify the problem. In references [8]-[10],according to the status of rail transit operations, Xiangyun Wu et al proposed the urban rail transit passenger flow distribution model and use the appropriate algorithm for solution. In the above study, the problem of passenger routing choice and the distribution of passenger flow in traffic network have been analyzed respectively. Based on the above research, this paper analyzes the main influencing factors of passenger route selection in urban rail transit, designs the passenger route identification of urban rail transit network, and verifies the design scheme through statistical investigation and computer simulation. PASSENGER'S TRAVEL ROUTE IDENTIFICATION SCHEME As the requirements of transfer time, travel time are different for different people, resulting in the choice of travel routes are not same. In a complex urban rail transit network, each OD pair offers some alternative paths in theory, but only a part of the route will be considered by passengers because of the impact of factors such as travel time, transfer times, crowdedness and price. How to weigh these factors, design a suitable scheme to identify the passenger travel route has become a hot topic of rail transit. Factors that affect passenger route selection. (1) Travel time The total time spent by the passenger from the departure place to the destination is called the travel time. In the urban rail transit system, the passenger travel time is positively related to the mileage of the train, and it is the most important factor when selecting the path. (2) Travel expenses In the urban rail transit system, the travel expense refers to the total cost of the passenger from the departure point to the destination, and the travel expense is also a major consideration when passenger select the path. (3) Transfer situation Transfer times and the walking distance while transferring can be reflected by the transfer time. When the passenger travels face multiple path choices and time costs are close, at this time convenience will be the main factor affecting the passenger's choice. (4) Comfortableness Comfortableness mainly depends on the degree of crowding, when the degree exceeds a certain value, it will directly affect the choice of passengers' selection. 517 Preprocessing data Delete this data marked as 22 Grouped by user Sorted by time N Check next record whether the entry/ exit flag is 21 Check the first record whether N Y the entry/ exit flag is 21 Y N Delete the former data Check next record whether the marked as 21 entry/ exit flag is 22 Y Match N Check next record whether the Y Check next record whether the N successfully, entry/ exit flag is 22 entry/ exit flag is 22 output data Y Delete the former data marked as 21and later two data marked as 22 Figure 1. The flow chart of OD match. Take the median of it Output N Y Get group numbers The number of time samples of by square and take each OD is > 50? the upper bound Range divide group number, get the class interval OD data(delete data whose time Take the maximum below 120 seconds or longer than value of each OD 9000 seconds),delete staff data Take the median of the group Take the range of each OD pair Take the minimum Choose the value of each OD Divide into groups group which has by range the most sample Figure 2. OD time training flow chart. Specific scheme design. The specific process of passenger' route identification is as follows: Step 1: Collect the data of the IC card of the rail transit passengers. The original data is sorted and processed into the preprocessing data. Then use the OD match for the preprocessing data, mainly by time series. Users were sorted by time, combined with the entry and exit identification to determine the user's each pair of OD, the specific implementation process of OD match is shown in Figure 1; 518 Step 2: According to K (K = 3) asymptotic paths searching algorithm, choose three feasible routes ,each route is from the inbound station to the outbound station, which are, the shortest path, the second shortest path, the third shortest path; The process is as follows: (1) The shortest path According to the urban rail transit network map, an oriented graph is constructed in which the distance of the connected nodes is described as the travel distance between adjacent stations. For the OD pair that needs to be calculated, we can find the shortest path between the OD pairs through the classical Dijkstra shortest path algorithm. (2)The second shortest path According to the shortest path between the OD pairs obtained by the algorithm (1), each time we delete the edge of the shortest path from the original oriented graph and we use the algorithm(1) for the new oriented graph formed, A temporary second shortest path is obtained, and the process is repeated until all the edges in the shortest path obtained in algorithm (1) are deleted, and then we compare all temporary second shortest paths, and the shortest one is defined as the second shortest path. (3) The third shortest path If the shortest path and the second shortest path obtained by (1) (2) contain the same edge, then we delete one same edge from the original image each time, and then use the algorithm (1) to search until the remaining edges of the shortest path and the second shortest path do not contain same edges, and then make these two groups of remaining into pairs, each time we delete a pair, and then use the (1) to search; Finally, we compare all the temporary paths, the shortest one is the third shortest path. Step 3: Do the OD time training according to the matching OD data, obtain the average training time from departure place to the destination, the specific operation process is shown in Figure 2. Step 4: The final route selecting, according to the training time in step 3 and the passengers’ entry and exit time information, find the most likely travel path from above three routes obtained from Step2, the specific process is shown in Figure 3. CASE TESTING In order to test the rationality of the scheme, take the Chongqing rail transit network as the research object. By December 2016, Chongqing Rail Transit has four operating lines, including 1,2,3,6 line (including the EXPO line, airport line) , covering the entire city of Chongqing, which contains 126 stations, eight transfer points, 213 km operating mileage, the highest daily passenger volume is 261.82 million times.

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