Finding a real passenger path in a complex transit network using a smart card record

초록

Korea has a very elaborate transit trip data, smart card record. We can know exact trip origin stop and destination stop when you are using public transportation in Korea especially Seoul Metropolitan Area (SMA). These data can be used to calibrate path choice based stochastic transit assignment model which can describe passenger behavior more precisely. However, the model has to decide alternative path set in huge network. This paper reviews search methods of multiple reasonable paths to implement multimodal public transportation assignment model with network of Seoul. Such a large scale multimodal public transportation network as Seoul, the computation time of path finding algorithm is a key and the result of path should reflect route choice behavior of public transportation passengers. Search methods of alternative path are divided into removing path method and deviation path method. Applying path finding algorithm in public transportation network, transfer and loop constraints must be included to be able to reflect real behavior. To validate the availability of algorithm, experiments conducted with Seoul metropolitan public multimodal transportation network consisted with 41,950 nodes and 171,176 links by using the deviation path method, suitable for large-scale network.