| With city development and life improvement, our nation puts a lot of efforts to construct the infrastructure of urban transportation. Unfortunately, the fast-growing transportation evolution has ever never caught up with citizen’s expectation. Government, enterprise and society make joint efforts for the construction of transportation infrastructure and restriction of citizen’s expectation.Technically speaking, Intelligent Transportation is an emerging solution, which automatically and dynamically allocates limited transportation resources using information sharing, resource management technologies. The vehicle sharing, as one of the Intelligent Transportation technologies, matches up passengers who have similar route demands and provides taxi sharing or carpooling suggestions. According to the historical researches, this problem can be described by three models:1) Different single origination and single destination, 2) Different single origination but same destination,3) Different multiple origination and destination.This thesis chose the third model to depict the real peer-to-peer passenger network that refers individual as a minimum unit. We introduced constraint and premise into the traditional model, established the mathematic model using the graph theory, and define the measurement of the solution. It finally turns out to be a NP-hard problem, which is difficult to resolve by mathematical analysis. We cited Hierarchy Clustering as the core algorithm and made plenty of optimization and enhancement based on the mathematic model and corresponding data structure. In the end, a vehicle sharing system was built by proper logical and physical structure.Our major work and innovation include:1) Selected an embryotic technical field and adopted a common traditional model to establish the mathematic model.2) Designed an improved and customized Hierarchy Clustering algorithm for this problem and, moreover, implemented a vehicle sharing system by spatiotemporal data mining. |
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