The rapid and large-scale construction of urban rail transit in China in recent years has drawn worldwide attention. The progress report and analysis would be a good reference for regional urban transit planning and policy, and for financial investment and service improvement in future. This paper offers a high-level summary of infrastructure statistics. In particular, this paper reviewed the spatial service coverage, passenger service performance and operational efficiency of urban rail transit in Mainland China and analyzed the development characteristics, such as the developing scales and multi-type urban rail transit modes based on the Annual Report of the China Urban Mass Transit work from 2008 to 2015. Suggestions and trends for further development of urban rail transit in China are proposed.

Urban transit system is an important part of city transportation, which is an interdisciplinary industry, including traffic engineering, operation research, and computer science. To provide smart services for passengers while applying the new technologies, it is necessary to build an optimal transit network and transit service. A smart transit system is processed from strategic planning, tactical planning, operational planning, transit evaluation to marketing and policy. For each stage, large quantities of related literature have been introduced from different perspectives. The aim of this research is to document the main smart urban transit models, topics and implementations for future references and research in each stage. For the planning part, this paper first summarized the objectives, constraints, algorithms, and implications of the models currently in use and classified the objectives and constraints with classic category and new category. The prominent topics and potential research were captured clearly when comparing the two categories. The methodologies for solving those models were proposed and the genetic algorithm and simulated annealing have been mostly used, which will be helpful for filling the gaps for further research. Despite of the model updates, this study also summarized the application trends such as integrated network design in strategic planning, synchronization and timetable recovery from disruption in tactical and operational planning. To improve the transit system and service, evaluation models on service reliability, service accessibility, timetable robustness, and energy consuming are proposed, which highlight the gap between the idealized service and the real service. Some flexible fare scheme, investments, and commercial strategies are discussed in the financial part. The conclusion highlighted the future scope of the smart urban transit in passenger demand management, travel information service, facility and service optimization and shared mobility, in order to make it more convenient for the passengers and more friendly to the environment.

In the urban rail transit system, train timetabling according to the dynamic passenger demand is important to offer high-quality service. Timetable optimization with the predetermined train route plan cannot synchronously consider the spatial and temporal characteristics of demand. Based on the Automated Fare Collection (AFC) data, this study proposes the integrated optimization (IO) to make route plan and timetable. A mixed-integer nonlinear programming (MINLP) model is formulated with the aim of reducing passenger penalty travel time and operation penalty cost. An improved non-dominated sorted genetic algorithm-II (Improved NSGA-II) is applied to deal with the bi-objective problem. A numerical experiment is used to prove the effectiveness and efficiency of the model and the algorithm. Then, the IO approach is applied in a bi-directional urban rail transit line. The results show that the IO performs the best compared with two other feasible strategies, namely the current optimization (CO) and phased optimization (PO).

The train timetable is a crucial document for organization of railway traffic. A high-quality train timetable is not only implementable in operational environment, but also efficient in terms of capacity utilization of railway infrastructure. In this paper, we try to solve the train timetabling problem of a double track high-speed railway line with heavy traffic and trains with different operational speeds are operated. In order to obtain a feasible timetable with high efficiency, different kinds of headway time are distinguished in the process of train timetabling. With a time expanded graph describing train movements, an integer linear programming is formulated. A branch and price algorithm is proposed to solve the model. The case study shows that more trains will be scheduled when different kinds of headway time considered.

The key features of an intercity high-speed railway (IHSR) include its high frequency, the short intervals, and the short distances covered. The mode of rolling stock scheduling generally uses fixed segments. In view of the fact that intercity passenger demand has the characteristics of large fluctuations in terms of time and direction, the use of the traditional rolling stock scheduling plan with a fixed train formation will result in a mismatch between the train formation and passenger demand. In order to improve the matching of train formation and passenger demand and increase the utilization rate of rolling stocks, this paper puts forward the concept of flexible train formation by time period and constructs an integrated optimization model of the rolling stock scheduling and flexible train formation based on passenger demand. The model aims at minimizing the number of rolling stocks, the amount of coupling/decoupling necessary, and the deadhead time. The model takes into account constraints such as the connection method used, the source and destination of the rolling stock, the total amount of rolling stock, and the use of a flexible train formation. In addition, the Gurobi solver is used to accurately solve the problem through the linearization of the model. This paper also provides an example of the Beijing–Tianjin IHSR as a verification of the feasibility and effectiveness of the proposed model. The example compares the indicators in the fixed and flexible train formation modes. The results of the research show that, on the premise of meeting passenger demand, the flexible train formation mode can reduce the cost of rolling stock; increase the efficiency of rolling stock; improve the balance of rolling stock scheduling; and, consequently, provide a reference for the optimization of rolling stock scheduling plan with the background of “cost reduction and efficiency increase” in the railway industry.

It has been proven that developing urban rail transit (URT) is the key to solving the traffic problems in big cities, and transport efficiency is essential for scientific line planning and construction, operation management and sustainable development of urban rail transit. This paper focuses on the transport efficiency of the URT network and adopts shadow efficiency theory creatively to combine factors of passengers, capacity, and efficiency effectively. A quantitative calculation method of system utility based on “double time penalty” is proposed. According to the characteristics of Beijing URT, this paper puts forward a single optimization strategy and combinatorial optimization strategy and analyzes the results with DEA. The simulation of Beijing subway network proves the availability of the method and its optimization effects.