Effective use of urban rapid railway systems requires that the railway systems be effectively con-nected with other transportation modes so that they are accessible. This paper uses the logit model and data to analyze the factors influencing railway access choices in a railway choice access model. The results indicate that access time, access cost, and access distance are factors significantly affecting railway access choices. The user’s income significantly affects the probability of choosing to walk rather than to take a taxi, but is not related to choosing buses or bicycles. Vehicle ownership significantly affects the probability of choosing a taxi, but is not significantly related to the other modes. The conclusions provide an analysis tool for urban railway planning and construction.
Traditional trip generation forecasting methods use unified average trip generation rates to deter-mine trip generation volumes in various traffic zones without considering the individual characteristics of each traffic zone. Therefore, the results can have significant errors. To reduce the forecasting error pro-duced by uniform trip generation rates for different traffic zones, the behavior of each traveler was studied instead of the characteristics of the traffic zone. This paper gives a method for calculating the trip efficiency and the effect of traffic zones combined with a destination selection model based on disaggregate theory for trip generation. Beijing data is used with the trip generation method to predict trip volumes. The results show that the disaggregate model in this paper is more accurate than the traditional method. An analysis of the factors influencing traveler behavior and destination selection shows that the attractiveness of the traffic zone strongly affects the trip generation volume.
