GLOBAL DYNAMIC TRAVEL REQUIREMENT ESTIMATION METHOD BASED ON MULTI-SOURCE TRAFFIC DATA

摘要

A global dynamic travel requirement estimation method based on multi-source traffic data estimates global travel data of residents in real time by fusing dynamic traffic data with static historical signaling data of mobile phones, and by combining global historical travel data of residents and real-time traffic travel data, thereby greatly reducing time and financial costs of an OD survey. A Chi-square distance is further introduced to measure the accuracy of a constructed fusion model, such that an optimal dominant travel mode threshold is determined, and an accurately estimated fusion model is acquired. The method combines real-time data of traveling by taxi and subway with historical signaling data of mobile phones to effectively sense a real-time travel status of residents travelling en masse, and to sense and provide a timely warning about the occurrence of a crowd gathering, thereby making a contribution of great significance to urban planning and management.