Analysis Of Individual Travel Behavior Based On Learning Potential

Urban transportation is a complicated giant system. Traffic congestion has become a big stumbling block of urban economic development as urban land and population expansion. In some of China cities, traffic jams seem to be more evident while transportation infrastructure constructions are speeding up. In recent years, transportation administrations are gradually beginning to recognize that the cause of traffic jams lies in that there is a gap between traffic demand and supply. It is a widely accepted principle that travel demand is derived from activity demand. Therefore, we can affect residents'activity decisions by travel demand management policies so as to re-assign traffic flow in term of time and space, which has been proved to be an effective solution to traffic congestions. As the result, more and more attentions are paid to activity-based travel demand forecasting theory, which provides additional guidance for modeling the individual and household decisions of urban residents.The dissertation is trying to identify residents'travel behaviors and characteristics in Binhai New District, Tianjin. For one thing, qualitative analysis of travel demand is conducted. Then hypothetical model is proposed. Last, the author examines the hypothesis testing. The dissertation certres on the following aspects:Firstly, the author summarizes the current achievements and tendency on travel demand forecasting model in domestics and abroad. The differences between trip-based and tour-based model are also demonstrated.Secondly, the author introduces the fundamental theory and ideas underlying activity-based travel demand forecasting model. Subsequently, important theory and method of disaggregate model are presentd as well. Then the author gives a broad review of activity-based travel behavior analysis and demand forecasting models, which have been subdivided into two methodological categories, econometric and hybrid simulation model. And the differences among modeling approaches are also discussed.Thirdly, the author states that learning potential exerts a distinguishing influence on travel behaviors, and develop structural equation model of travel behavior analysis to explore the complicated causal interrelationships among socio-demographics, individual's learning potential and travel behavior characteristics.Lastly, an empirical analysis has been done to test the proposed hypothesis. With the daily travel data derived from Binhai New District, Tianjin, the author conducts model estimation, evaluation and modification. The results show that we are able to capture and understand the relationship among socio-demographics, individual's learning potential and travel behavior characteristic by examining the direct, indirect and total effect in the model system. Furthermore, it indicates that there is a strong effect of learning potential on travel behavior.