In order to determine the impact of real-time information on travel behaviors, car commuters' travel behaviors were investigated with the presence of a smartphone multi-modal travel information system. Based on a stated preference survey of Shanghai travelers, behavioral data were collected with the smartphone multi-modal travel information system that provides two auto routes (mainly based on overhead and ground) and one subway park-and-ride route. A descriptive analysis and multivariate logit model was proposed to identify contributing factors. It is shown that travel decisions are influenced by traveler attributes about the driving experience, number of family private cars, frequency of driving, frequency of traffic information access and user experience of subway park-and-ride as well as the information about travel time and crowdedness status of subway. In addition, some suggestions were given for guiding the traffic planning and management and developing the multi-modal travel information system.