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Auxiliary stopping area (ASA) is the necessary emergency facility for train safety of the normal high-speed maglev. The study addresses the ASA layout problem of the high-speed maglev operated bidirectionally on single track. First, an optimization model of the ASA layout for unidirectional double-track lines considering train safety, operation efficiency, and construction cost is established, and two basic methods of the ASA layout are investigated based on the distance demand characteristic of ASAs. Then, the ASA layout problem of bidirectional single-track lines is analyzed, and an ASA two-way coordination layout algorithm (ASA-TWCLA) is proposed. Finally, a numerical experiment is carried out. The results suggest that under the premise of train safety and operation efficiency, compared with using the basic methods separately on the two directions, adopting the ASA-TWCLA algorithm can obtain a more economical ASA layout scheme for the same scenario.

Automatic train operation (ATO) system is one of the important components in advanced train operation control systems. Ideal controllers are expected for the automatic driving function of ATO systems. Aiming at the intelligence requirements of the systems, an NSGA-II-based parameter tuning method for the fuzzy immune PID (FI-PID) controller and a grey model GM(1,1)-based fuzzy grey immune PID (FGI-PID) controller were proposed. Taking a maglev train’s model as the control object and a velocity-time curve as the input, the feasibility of the parameter tuning method for the FI-PID controller and the applicability of the FI-PID controller and the FGI-PID controller for the ATO system were tested. The results showed that the optimized parameters were ideal, the two controllers all showed good performance on the indicators of traceability and comfort level, and the FGI-PID controller performed better than the FI-PID controller. The results exhibited the effectiveness of the proposed methods.

The district handover is one of the key technologies in the high-speed maglev operation control system. It completes the transfer of safety responsibilities when a train passes across two districts, and it directly affects the safety and stability regarding train operation. This article first makes a general analysis of its mechanism, including the essential characteristics, stakeholders and tasks of the district handover. In order to simplify the complexity of the behavior models, the whole procedure is divided into four phases, namely, the preparation phase, the stopping point stepping phase, the vehicle reception phase and the termination phase. The information interaction and timing relationship of these models are presented by UML.

Operating scenarios have important value in the development and operation of rail transit systems. Based on literature search results, the concept of operating scenarios is discussed firstly. Then, taking railway, subway, tram, and maglev as objects, the development status, operation control systems and operating scenarios of the them are described. Furthermore, the basic composition of operating scenarios of rail transits is analyzed, the typical characteristics of operating scenarios are given, and the value of operating scenarios are discussed.

Auxiliary stopping area (ASA) is the key guarantee for high-speed maglev train operation safety. Aiming at the layout of the ASA along the track, this article constructs an optimized model of ASA layout and proposes a solving algorithm based on the single target genetic algorithm by analyzing the influence factors of ASA layout. The result of the numerical experiment shows that the proposed method could fulfill the requirements of the maglev train operation safety and efficiency and optimize the cost of the ASA layout while taking the complex line situation, train tracking operation, and bidirectional operation on a single line into account.

The safety of equipment operation is important for the operation of rail transits. The lifetime of equipment and its improvement methods have become one of the key issues in the operation and maintenance of rail transits. Based on the fuzzy comprehensive evaluation process and evaluation result data, the decision-making algorithm for improving the lifetime of the equipment was discussed, including the strategy recommendation algorithm based on assessed data and the strategy matching algorithm based on case reasoning. Taking the actual data of onboard ATC equipment of Line 11 in a city as an example, the effectiveness of the two methods was verified. The methods in the study can support the decision-making process for maintenance departments.

In order to save people's travel time in searching parking spaces, this paper firstly analyzes the changes data of available parking spaces in five parking lots with different capacities, which are located in Xi'an, China. Then this paper uses two methods to predict the data of available parking spaces. The results show that: (1) Available parking spaces in the urban parking lots are fluctuating according the survey data, parking spaces with large capacity of the parking lot will have a larger data fluctuation range, and parking saturation of parking lot will also be affected by the parking lot size and location. (2) Back propagation (BP) neural network model can be used to predict the available parking space of parking lots, no matter the capacity and different geographical location of those carparks is different. Moreover, a model of combination of genetic algorithm (GA) and BP neural network is more reliable than a simple BP neural network model according the results of data contrast are used.