An Integrated Approach for Selection of Intercity Transport Schemes on Railway Networks

A major problem connected with planning the organization of trains on a railway network is the optimization of the scheme of movement, which determines the routing and the number of trains. In this paper, an integrated approach of fuzzy linear programming method and multi-criteria analysis including three steps is proposed. In the first step, we defined the schemes of transportation of intercity trains and optimized each scheme in terms of direct operating costs by taking into account the uncertainty of passenger flows and utilization of train capacity using the fuzzy linear programming method. In the second step we determined the additional technological criteria to assess the variant schemes. The Fuzzy AHP method was applied to determine the weights of criteria. Using the results obtained from Fuzzy AHP, we prioritized the variant schemes of transportation by applying the PROMETHEE method. The third step presents the optimal choice of transportation of trains on a railway network based on minimum ratio of normalized costs and normalized PROMETHEE net outranking flow. In this step, the model uses the results obtained in the first and second steps. The practicability of the integrated approach is demonstrated through the case study of Bulgaria’s railway network, and nine schemes were investigated. The model results and the real situation were compared. It was found out that the optimal scheme of intercity train transportation improves the service and reduces direct operating costs

Train Repathing in Emergencies Based on Fuzzy Linear Programming

Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm

Timetable coordination of first trains in urban railway network: A case study of Beijing

A model of timetable coordination of first trains in urban railway networks, based on the importance of lines and transfer stations, is proposed in this paper. A sub-network connection method is developed, and a mathematical programming solver is utilized to solve the suggested model. A simple test network and a real network of Beijing urban railway network are modeled to verify the effectiveness of our suggested model. Results demonstrate that the proposed model is effective in improving the transfer performance in that they reduce the connection time significantly

Reducing land take and energy use of high-speed railways through the robust design of operations

I address the problem of the high capital cost of high-speed railways and the need to reduce their energy use through the design of robust operations at the planning stage. Given the cost structure and benefits of different solutions, reducing the size of termini and maintaining robust operations in and near the termini is identified as a promising option for cost reduction. Two methodologies from manufacturing industry, namely, the Lean principle for cost reduction and the Taguchi method for robust design, are confirmed as suitable tools to realise the objective of improving the design of high-speed railways. I developed a novel approach that combines Lean and Taguchi techniques to deal with characteristic features of high-speed railways, such as the severe requirement for robust operations. Finally, the worth of the combined approach has been demonstrated by means of case studies of current British conventional railway practice, current Japanese high-speed railway operations and the planned High Speed Two (HS2) line. The latter work has shown the possibility of a reduction in the proposed number of platforms at Euston Station, the main terminus of HS2 in London, as well as energy saving for traction

System energy optimisation strategies for DC railway traction power networks

Energy and environmental sustainability in transportation are becoming ever more important. In Europe, the transportation sector is responsible for about 32% of the final energy consumption. Electrified railway systems play an important role in contributing to the reduction of energy usage and C0$_2$ emissions compared with other transport modes. Previous studies have investigated train driving strategies for traction energy saving. However, few of them consider the overall system energy optimisation. This thesis analyses the energy consumption of urban systems with regenerating trains, including the energy supplied by substations, used in power transmission networks, consumed by monitoring trains, and regenerated by braking trains. This thesis proposes an approach to searching energy-efficient driving strategies with coasting controls. A Driver Advisory System is designed and implemented in a field test on Beijing Yizhuang Subway Line. The driver guided by the DAS achieves 16% of traction energy savings, compared with normal driving. This thesis also proposes an approach to global system energy consumption optimisation, based on a Monte Carlo Algorithm. The case study indicates that the substation energy is reduced by around 38.6% with the system optimised operations. The efficiency of using regenerative braking energy is improved to from 80.6 to 95.5%

Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013

Challenges arising from an increasing traffic demand, limited resource availability and growing quality expectations of the customers can only be met successfully, if each transport mode is regarded as an intelligent transportation system itself, but also as part of one intelligent transportation system with “intelligent” intramodal and intermodal interfaces. This topic is well reflected in the Third International Conference on “Models and Technologies for Intelligent Transportation Systems” which took place in Dresden 2013 (previous editions: Rome 2009, Leuven 2011). With its variety of traffic management problems that can be solved using similar methods and technologies, but with application specific models, objective functions and constraints the conference stands for an intensive exchange between theory and practice and the presentation of case studies for all transport modes and gives a discussion forum for control engineers, computer scientists, mathematicians and other researchers and practitioners. The present book comprises fifty short papers accepted for presentation at the Third Edition of the conference. All submissions have undergone intensive reviews by the organisers of the special sessions, the members of the scientific and technical advisory committees and further external experts in the field. Like the conference itself the proceedings are structured in twelve streams: the more model-oriented streams of Road-Bound Public Transport Management, Modelling and Control of Urban Traffic Flow, Railway Traffic Management in four different sessions, Air Traffic Management, Water Traffic and Traffic and Transit Assignment, as well as the technology-oriented streams of Floating Car Data, Localisation Technologies for Intelligent Transportation Systems and Image Processing in Transportation. With this broad range of topics this book will be of interest to a number of groups: ITS experts in research and industry, students of transport and control engineering, operations research and computer science. The case studies will also be of interest for transport operators and members of traffic administration

Algorithms for Scheduling Problems

This edited book presents new results in the area of algorithm development for different types of scheduling problems. In eleven chapters, algorithms for single machine problems, flow-shop and job-shop scheduling problems (including their hybrid (flexible) variants), the resource-constrained project scheduling problem, scheduling problems in complex manufacturing systems and supply chains, and workflow scheduling problems are given. The chapters address such subjects as insertion heuristics for energy-efficient scheduling, the re-scheduling of train traffic in real time, control algorithms for short-term scheduling in manufacturing systems, bi-objective optimization of tortilla production, scheduling problems with uncertain (interval) processing times, workflow scheduling for digital signal processor (DSP) clusters, and many more

Disruption analytics in urban metro systems with large-scale automated data

Urban metro systems are frequently affected by disruptions such as infrastructure malfunctions, rolling stock breakdowns and accidents. Such disruptions give rise to delays, congestion and inconvenience for public transport users, which in turn, lead to a wider range of negative impacts on the social economy and wellbeing. This PhD thesis aims to improve our understanding of disruption impacts and improve the ability of metro operators to detect and manage disruptions by using large-scale automated data. The crucial precondition of any disruption analytics is to have accurate information about the location, occurrence time, duration and propagation of disruptions. In pursuit of this goal, the thesis develops statistical models to detect disruptions via deviations in trains’ headways relative to their regular services. Our method is a unique contribution in the sense that it is based on automated vehicle location data (data-driven) and the probabilistic framework is effective to detect any type of service interruptions, including minor delays that last just a few minutes. As an important research outcome, the thesis delivers novel analyses of the propagation progress of disruptions along metro lines, thus enabling us to distinguish primary and secondary disruptions as well as recovery interventions performed by operators. The other part of the thesis provides new insights for quantifying disruption impacts and measuring metro vulnerability. One of our key messages is that in metro systems there are factors influencing both the occurrence of disruptions and their outcomes. With such confounding factors, we show that causal inference is a powerful tool to estimate unbiased impacts on passenger demand and journey time, which is also capable of quantifying the spatial-temporal propagation of disruption impacts within metro networks. The causal inference approaches are applied to empirical studies based on the Hong Kong Mass Transit Railway (MTR). Our conclusions can assist researchers and practitioners in two applications: (i) the evaluation of metro performance such as service reliability, system vulnerability and resilience, and (ii) the management of future disruptions.Open Acces