KEYWORDS: Data modeling, Transportation, Modeling, Mathematical modeling, Global Positioning System, Databases, Education and training, Analytical research, Systems modeling, Statistical analysis
To obtain the historical travel time and space trajectories of public transportation (PT) passengers and analyze the characteristics and patterns of their trips and activities, the PT trip-chain modeling and analysis methods are studied. The mathematical expression and attribute classification of the PT trip-chain model are given, the theoretical framework of applying multi-source big data to build the PT trip-chain model is proposed, and the trip-chain method is applied to judge the bus passengers' alighting stops, the transfer behavior is judged by calculating the reasonable transfer time of passengers' two consecutive trips. The PT trip-chain model is constructed by integrating passengers' travel spatio-temporal information, and the PT travel is systematically summarized. The analysis contents of group and individual characteristics are summarized systematically. The proposed modeling and analysis methods are experimented and validated by applying large-scale actual data. The results show that the PT trip-chain model establishes a basis for systematically analyzing the travel characteristics and patterns of passengers, which can provide a scientific basis for the planning and management of PT systems.
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