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Park and Ride (P&R) systems are an effective way to attract road users to rapid transit, which helps both reduce the traffic entering the center of a city and improve the efficiency of urban rail transit systems. In Beijing, fast growing car ownership is putting significant strain on the already congested roads and reducing the number of cars on highways is an important goal of the planned P&R system. This paper describes a Stated-Preference (SP) survey of potential users of a Park-n-Ride system being planned in Beijing. The objective of the study is to understand the intent of auto-drivers in response to a future P&R system. People often have preferences when making choices. This is also true when it comes to choosing travel modes, which needs to be considered when developing a travel mode choice model. To model such preferences, the survey sample is divided into auto-captive, P&R-captive and choice users. The characteristics of the three groups are analyzed and preferences are considered in the choice models. Mode choice models were developed based on the whole sample, choice-user sample, and the whole sample considering preference. The results from the model show improvements in interpreting the independent variables and accuracy of the models. The research provides a tool for forecasting the demand and supply of P&R systems and demonstrates analyses of effects of choice preference in behavior models.
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