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How informatization promotes the development of integrated transportation system is discussed in this paper. A model of the relationship between transportation development and space-time structure of economy is presented in order to explain the transportation system characteristics and development requirements in the information society. The key role of information and communication technology (ICT) is analyzed by combing through the developing clues of transport. Logistics, SCM and third-party organizations are employed as well to study integrated transportation system for comprehensive consideration.

We propose a deep-learning-based illumination analysis and efficient local imaging method. Based on the wavefield forward modeling, seismic illumination can intuitively express the energy propagation of direct waves, reflected waves, and transmitted waves, while it requires high calculation costs. We use a series of convolution operations in deep learning to establish the nonlinear relationship between the model and the illuminations to realize single-shot illumination result of the model. Stacking the single shot illumination results obtained by the network prediction can further help determine the target area. For the target area, we use a deep learning method to obtain the low illumination area of the geological model. Each shot has contribution to the low illuminated area; single shot is selected based on the contribution of the shot being greater than the average illuminance, and the low illumination area is imaged by reverse time migration on the selected shot gather. The trained convolutional neural network can help us quickly obtain the single shot illumination result of the model, which is convenient to analyze the energy distribution of various areas of geological model, and do further imaging for target areas. Using part of the shot gathers to image a local area can recover the complex geological structure of the area and improve the efficiency of reverse time migration especially for 3D problems. This method has universal applicability and is suitable for local imaging of various complex models such as subsalt areas and deep regions.

The urban rail based Transit Joint Development (TJD) has become one of the most important financing channels for constructing urban rail transit systems in China. Compared to the extensive research and application in planning field, the implementation of TJD still faced some difficulties such as organizational model selection, distribution of benefits and so on. In the 1980s and 1990s, the United States, Japan and Hong Kong developed a series of TJD practices and they formed three kinds of TJD mode: Public-Private Partnership, Enterprise Oriented, and Franchise. Empirical evidences have shown that differences among three modes are mainly reflected in the selection of implementation agency, allocation of functions and distribution of benefits. Then these distinctions will cause various impacts on the scale, cycle, form and operational management of TJDs. The conclusions of this research could provide valuable experience to the ongoing work of TJD in Chinese mega cities.