A Route-Planning Algorithm Based on Subway Passenger Routes Choice Behavior Analysis

With the rapid development of city subway systems, subway networks become more complex and subway route planning services becomes necessary. Conventional route planning algorithms are based on the least travel time rule. However, a survey illustrates that travel time is not the only influential factor in route choice behavior. Thus, it is necessary to establish a new route planning algorithm based on the greatest generalized cost which can reflect real route choice preference with consideration of multiple influencing factors. First, a route choice model is established using questionnaire data collected in the Beijing Subway to analyze route choice behavior based on the discrete choice theory. Factors such as travel time, transfer time, and number of transfers are included in the utility function, but ticket price is excluded because of the flat-fare system of the Beijing Subway. Second, a new route planning algorithm is proposed. The optimal route found by the Dijkstra Algorithm with the greatest utility value, and another route with the least travel time are provided to passengers. Finally, the proposed route planning algorithm is compared with the conventional one. The results show that the former is more consistent with the real situation.