Zhibin Jiang

Scheduling Additional Train Unit Services on Rail Transit Lines

This paper deals with the problem of scheduling additional train unit (TU) services in a double parallel rail transit line, and a mixed integer programming (MIP) model is formulated for integration strategies of new trains connected by TUs with the objective of obtaining higher frequencies in some special sections and special time periods due to mass passenger volumes. We took timetable scheduling and TUs scheduling as an integrated optimization model with two objectives: minimizing travel times of additional trains and minimizing shifts of initial trains. We illustrated our model using computational experiments drawn from the real rail transit line 16 in Shanghai and reached results which show that rail transit agencies can obtain a reasonable new timetable for different managerial goals in a matter of seconds, so the model is well suited to be used in daily operations.

Multi-agent Delay Simulation Model in Mass Rail Transit System

A primary delay is the deviation from a scheduled process time caused by disruption within the process. Delay is controlled by timetable and shows the characters of random occurrence. Rail transit system is a complex system which is dynamic, nonlinear, self-adaptive, random-occurrence and schedule-controllability. The Multi-agent method enlarges the range of computer applying in rail system. This paper brings forward the delay simulation model which bases on Multi-agent, and discusses the definition, characters, applying of Multi-agent. Emphasizes the frame of delay simulation system basing on Multi-agent, and builds a Multi-agent delay simulation model which bases upon the train agent-gather, adjusted strategy agent-gather, and simulation environment. By the end, the model was illustrated by a sample of rail transit line 3 and line4 in Shanghai.

Train Delay Propagation Simulation in Rail Transit System

1 Abstract Urban rail transit system plays a key role in mobility in urban cities. The operation reliability of trains is a critical performance measure for passenger satisfaction and ultimately affects its market share. This paper discusses the train delay and Propagation characteristics in urban rail transit system. More specifically, this paper discussed the application of the model to assess how punctuality and reliability is affected by changes of availability, buffer time, and reserve rolling stock quantity and so on. A case study in Shanghai rail transit line 3 illustrates the practical value of the model. In this paper we use the simulations to explore the effect of some policy or parameter changes. For example, we use the simulation to compare a policy of allowing buffer time changes. Also, we use the simulations to examine a policy of allowing spare rolling stock number changes. This method can be used to test and compare the reliability of proposed timetable, or schedule changes, before adopting them. And it can also be used to explore some management method to reduce the influence of train delay.

A Branch and Bound Algorithm and Iterative Reordering Strategies for Inserting Additional Trains in Real Time: A Case Study in Germany

With the aim of supporting the process of adapting railway infrastructure and future traffic needs, we have developed a method to insert additional trains efficiently to an existing timetable without introducing large consecutive delays to scheduled trains. In this work, the problem is characterized as a job-shop scheduling problem. In order to meet the limited time requirement and minimize deviations to the existing timetable, the modification that consists of retiming or reordering trains is implemented if and only if it potentially leads to a better solution. With these issues in mind, the problem of adding train paths is decomposed into two subproblems. One is finding the optimal insertion for a fixed order timetable and the other is reordering trains. The two subproblems are solved iteratively until no improvement is possible within a time limit of computation. An innovative branch and bound algorithm and iterative reordering strategy are proposed to solve this problem in real time. Unoccupied capacities are utilized as primary resources for additional trains and the transfer connections for passengers can be guaranteed in the new timetable. From numerical investigations, the proposed framework and associated techniques are tested and shown to be effective.

A Turn-back Track Constraint Train Scheduling Algorithm on a Multi-interval Rail Transit Line

With the rapid increase of passenger volume, the interval of some rail transit lines in China has reached a minimum value, which makes turn-back capacity one of the main capacity-limiting factors instead of section headway, particularly during the peak hours on workdays. A general simulation modeling framework and algorithm in which the divide and conquer rule is adopted for train scheduling problems on a multi-interval rail transit line with turn-back track constraint is proposed in the paper, and the objective is to obtain a feasible timetable based on passenger demand at different time periods, line capacity, number of rolling stocks, location of depots, train routing, turn-back type. Lastly, a new version of the TPM software is programmed by the proposed framework and algorithm, and Shanghai Rail Transit Line 2 is presented to demonstrate. The result shows that the proposed algorithm performs very efficiently, and a feasible timetable with a five-interval period, 535 trains and one turn-back track constraint at GLR station is generated in 15 seconds by TPM.

Running Buffer Time Distribution Calculation Based on Delay Analysis in Mass Transit System

The most direct and effective measure to reduce the impact of delay is setting buffer time in train timetable. Based on the confirmation of total buffer time in mass rail transit line, this paper established a random integer programming model of running buffer time distribution, aiming at minimum total arriving delay time in the objective function. The model obtained running buffer time calculation formulas under three kinds of conditions, including total buffer time is equal to total delay time, total buffer time is less than total delay time, and total buffer time is more than total delay time. This model is finally validated through a calculation example. The results of this research can instruct the arrangement of train timetable and improve the reliability of train timetable.

Q-learning approach to coordinated optimization of passenger inflow control with train skip-stopping on a urban rail transit line

Abstract In the case of an over-crowded urban rail transit (URT) line, a large number of passengers may be left stranded and daily timetable may become infeasible. This paper proposes a coordinated optimization scheme for a URT line, which combines both the coordinated passenger inflow control with train rescheduling strategies. With the aim of minimizing the penalty value of passengers being stranded along the whole line, the coordinated passenger inflow control helps relieve demand pressure and ensure safety at over-crowded URT stations while the train rescheduling of skip-stopping helps to balance the utilization of train capacity. A novel Q-learning based approach to this combination optimization problem is developed. Simulation experiments are carried out on a real-world URT line in Shanghai. Basic principles of Q-learning are presented, which consist of the environment and its states, learning agents and their respective actions, and rewards. The results show that the coordinated optimization scheme solved by the Q-learning approach is effective in relieving the passenger congestion on the URT line. The Q-learning approach can offer accurate scheme to deal with the problem of passenger congestion and train operation on a URT line.

Corrigendum to Evaluating rail transit timetable using big passengers' data J. Comput. Syst. Sci. 82 (1, Part B) (2016) 144-155

This work was supported by the National Natural Science Foundation of China (Grants Nos. 61473210, 61472283, 51208381), the Fok Ying Tong Education Foundation, China (Grant No. 142006), the Fundamental Research Funds for the Central Universities (Grant Nos. 2013KJ034, 2100219043 and 1600219246). This project is also sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry. The acquisition of the transit operations data in the paper was supported by the Shanghai Shentong Metro Operations Management Center. The authors are grateful to these supports.

Turnback Capacity Assessment and Delay Management at a Rail Transit Terminal with Two-Tail Tracks

Terminal capacity and performance have become a major concern for rail transit agencies in China due to the ever increasing passenger demand. This paper develops a mixed integer programming (MIP) optimization model to estimate the turnback capacity and performance of a rail transit terminal with two-tail tracks. The capacity evaluation and delay propagation are described and assessed as an -track integrated model with minimal time span and train delay. Operations and design parameters such as tail track allocation strategies, maximum layover time, headway pattern, buffer time distribution scheme, and primary delay are also considered in this model. The effectiveness of the model is tested by a case study with computation results drawn from one terminal station in Shanghai, China. The case study results show that unfixed platform time and flexible tail track allocation strategies can improve the capacity of turnback operation, and the strategy of allowing swapping of the tail tracks has a significantly positive impact on delay absorption.