Firstly, this paper summaries and analyzes the present development of intelligent transportation systems from two aspects:urban ITS and new technologies. Then, the prospective discussions are given for the traffic big data platform, the video technology, the AI technology, the traffic control technology, the vehicle-road coordination, the urban traffic brain and the non-contact technology. Finally, the key directions and some suggestions for the development of the intelligent transportation in the future are put forward.

Intelligent Transportation system (ITS) is one of the leading edges of the modern transportation technology. It has been developed for more than 20 years since the name was officially adopted in 1994. The development of the advanced technology and the travelers' new demands have brought about different and distinctive technical directions and R & D hot spots in the ITS field. Firstly, this paper analyzes the hot spots and the dynamics of the international ITS research and development in recent years, focusing on the progress of the ITS technology and the hot areas brought by the new generation of the information technology, as well as the direction of the ITS technology and the industry development. Secondly, compared with the development of the ITS in China in recent years, the paper analyzes the similarities and differences of the development ideas at home and abroad and the enlightenment gained from the hot research and development of developed countries. Finally, some suggestions on the development of the ITS are put forward, including seeking truth from facts to treat the gap, the similarities and the differences at home and abroad, strengthening the research and development of the ITS characteristic technology, and establishing a new development model based on the market.

This paper reviews the green transportation development at home and abroad and the new requirements of the urbanization development., as well as challenges facing the green transportation development. Corresponding suggestions are put forward from macro, medium and micro perspectives, based on the analysis of the current development trend of the green transportation. It is suggested to focus on the differentiated characteristics of each city and each region, and to further coordinate the transportation and the land use arrangement in an all-round way in the process of the green transportation development. Additionally, the transportation structure should be fully optimized, focusing on the details, to build a transportation model dominated by the "public transportation+non-motorized transportation".

The informatization plays a significant role in ensuring safety, improving efficiency, controlling cost and increasing benefit of high-speed railway. This paper firstly reviews the construction achievements and the present situation of the informatization construction of China high-speed railway. Moreover, the function and the key technologies of the main information system are analyzed. Then, the concept and the characteristics of the intelligent high-speed railway are discussed. Lastly, the paper analyzes the main development directions of the intelligent high-speed railway.

With the development of intelligence in the civil aviation in mind, this paper analyzes the key factors affecting the future development of the civil aviation, the development trend of the international civil aviation, the development of intelligence in China civil aviation and the possible measures taken by the Civil Aviation Administration of China(CAAC), as well as the goal and the vision of China civil aviation.

With the wide applications of information and intelligence in transportation services and management, large and rich data resources are accumulated in the industry. This paper analyzes the characteristics, the types and the data volume of the transportation big data, and briefly describes the structure, the function and the application of the integrated traffic travel big data open cloud platform, and analyzes application cases in several aspects, such as the traffic big data in the traffic congestion control, the highway intelligent inspection, the passenger flow statistics and the civil aviation management. Finally, it is suggested that the transportation data are very hybrid in nature, and the processing results may involve contradictory conclusions. As the data amount increases, the influence of inaccuracy on the whole analysis conclusion becomes smaller. When the data volume is expanded, simple algorithms may be more practical.

The real-time perception of the road network operation in a low-cost way is the key factor to gurantee the transportation safety and the unblocked operation. The rapid and accurate detection of traffic incidents and the collection of traffic data are often difficult. The traditional method is not visual, real-time and cost-effective. In recent years, the development of video big data and artificial intelligence provides a new way to solve these problems. This paper reviews the research history and application limitations of the intelligent video analysis in the field of transportation, as well as the characteristic connotation of video big data, the design of an artificial intelligence platform driven by video big data, and the solution and the application for highway traffic.

The adaptive traffic signal control method is adopted to effectively control the traffic lights at the urban road junctions, with the rapid growth of the traffic flow in Shenzhen. Shenzhen traffic police asked for a real-time, distributed and adaptive control on the basis of the self-developed smooth signal control. Joint innovation has developed the reinforcement learning based on the deep neural network. Through online learning of various traffic loads, and the real-time reasoning, the information control period, phase, phase sequence, signal cycle, split and phase difference are calculated. This paper reviews the reinforcement learning model used in the traffic signal control, and makes an evaluation on the spot.