Passenger share research of different transport modes based on the travel behavior analysis and Agent theory

Passenger share research of different transport models will help the transport sector to develop a more rational operating strategy and provide an important basis for the future transport planning and construction. The development of the Agent theory provides a new direction for the simulation of the passenger share. The purpose of this paper is to research the passengers’ decision-making mechanism by analyzing their travel behavior and use the Agent theory to simulate the passenger share of the four travel modes (the high-speed rail, the common rail, the highways and the civil aviation) in the ShangHai-NanJing transport line. Firstly, each passenger in this paper is considered to be an Agent according to the Agent theory and the passenger’s travel choice and transform mechanism is designed after analyzing the passenger’s travel choice behavior. Secondly, the genetic algorithm was used to design the passengers’ interaction and learning mechanism (including the elimination, crossover and mutation mechanism) under the research of the passengers’ travel choice. Thirdly, the Security, Convenience, Comfort, Ticket Price and Train Speed are selected to be the 5 main factors to evaluate the passenger’s satisfaction and an Agent satisfactory evaluation criteria is established. Fourthly, an Agent based simulation model is established and an empirical research was conducted in the ShangHai-NanJing transport line to simulate the passenger share of the four transport modes. At last, a sensitivity analysis is made for the five factors (Security, Convenience, Comfort, Ticket Price and Speed) that affect the passenger’s travel choice. From the research, we can get the conclusion that the high-speed railway induced new passenger flows and the passengers with different travel purpose have different sensitivity to the Security, Convenience, Comfort, Ticket Price and Speed factors.