The Integration Study Of High-speed Train Operation Control And Scheduling

High-speed train scheduling is an effective means to optimize the resource allocation of the high-speed railway network. It is also a basis of the train operational plan and train schedule, and a key technology to deal with train disturbance. The efficiency of high-speed train scheduling affects the service level and operational efficiency of high-speed railway network directly. Therefore, a scientific and efficient high-speed train scheduling has an important practical significance. In addition, high-speed train control can guide the concrete operation of a train. Studying the train scheduling combined with train control is able to optimize train scheduling on basis of train speed and location in real time, and is able to analyze the assessment criteria (such as total travel time and total energy consumption) quantitatively, which makes the train scheduling more scientific and reasonable.According to the literature in the area of train scheduling and train control at home and abroad, this paper studies the integration problem of the high-speed train scheduling and train control. We establish the train scheduling and controlling integration model, and design the improved genetic algorithm to obtain the accepted solution within a short time. At last, a simulation method is applied to the train movement to verify the validity of the proposed model and algorithm.The main work of this paper is as follows:1. For purpose of shorting the total travel time, reducing the total traction energy consumption and ensuring the operational safety, this paper introduces the coasting control method and establishes a time-energy balanced optimal strategies (TEBS). We investigate a dynamic model for mixed trains running on a high-speed railway network, and a simulation method is applied to simulate the train movement and prove the validity of the TEBS.2. An event-based model and a time-based model are proposed in this paper to adjust the train movement with train disturbance. The event-based model mainly constrains the starting time of events and the minimum running time on sections, and a two-stage greedy algorithm is designed to solve the problem. The time-based model defines a series of train adjusting strategies, and deal with the disturbance by choosing the adjusting strategy for each train based on TEBS. A simulation algorithm is also designed.3. A high-speed train routing and train control compound model is proposed in this paper. The model does not only consider the train control constraints, but also takes the passenger demand into account. Under the premise of meeting the control constrains, it can minimize the total travel time and total traction energy consumption by allocating the trains to each route on the high-speed railway network. An improved simulation-based genetic algorithm (GATC) is proposed to achieve the near optimal solution.4. A series of simulation experiments are showed to verify the validity of the above models and algorithms. The results prove that the solution obtained by TEBS is [10%,20%] higher than that of the basic control strategy. The event-based model deals with the train disturbance within a short time but without the real-time control, so it suits the large-scale railway network; while the time-based model deals with the train disturbance in a longer time but obtains a more accurate solution, so it suits the small-scale railway network. In addition, the high-speed train scheduling and train control compound model and algorithm can obtain an accepted train allocation solution to minimize the total travel time and total traction energy consumption.