The uncontrolled growth in urbanization and motorization generally contributes to an urban land use and transportation system that is socially, economically, and environmentally unsustainable. This paper uses Karachi as a case study, which is the largest urban and economic centre of Pakistan, passing through an uncontrolled phase of rapid urbanization and motorization. The paper first reviews research related to sustainable transportation systems to comprehend the concept of sustainable development and transportation. The paper then evaluates the existing transportation and infrastructure system, national transportation policies, and urban transportation projects to determine if the current paradigm is moving toward or away from sustainable transportation. Furthermore, the principles for sustainable urban transportation are developed to see what significance national transportation policies have given to urban transportation from a sustainable transportation point of view. Finally some strategies are suggested, adoption of which may lead to a sustainable urban development and transportation system in Karachi.

The theory of complex networks was used to classify public transport networks into public transportation route networks, public transportation transfer networks, and bus station networks. The practical significance of the network parameters was then analyzed. The public transport networks in Langfang, Jining, and Dalian were then chosen as specific research cases. The results show that the public transportation networks have the characteristics of complex networks. In addition, the urban transportation network parameters all significantly affect the accessibility, convenience, and terrorist security capability of the urban public transportation network. The results link the findings with the actual situations to explore means to solve transportation system problems.

The conventional traffic demand forecasting methods based on revealed preference (RP) data are not able to predict the modal split. Passengers' stated intentions are indispensable for modal split forecasting and evaluation of new traffic modes. This paper analyzed the biases and errors included in stated preference data, put forward the new stochastic utility functions, and proposed an unbiased disaggregate model and its approximate model based on the combination of RP and stated preference (SP) data, with analysis of the parameter estimation algorithm. The model was also used to forecast rail transit passenger volumes to the Beijing Capital International Airport and the shift ratios from current traffic modes to rail transit. Experimental results show that the model can greatly increase forecasting accuracy of the modal split ratio of current traffic modes and can accurately forecast the shift ratios from current modes to the new mode.