Overcoming Capacity Constraints - A Simulation Integrated with Optimisation for Nodes (OCCASION)

Lead Research Organisation: University of Southampton
Department Name: Faculty of Engineering & the Environment


The OCCASION project brings together the University of Southampton's expertise in railway simulation and control (Transportation Research Group) with more generic expertise in operational research (Centre for Operational Research, Management Science and Information Systems). This project will identify and assess innovative approaches to overcoming nodal capacity constraints by examining the scope for technological improvements and operational changes. Although the emphasis is on modelling, it will also cover technological and operational issues. This will include examination of incremental changes, such as improved design of points, changes in signal spacing and overlaps, but also more radical changes including concepts from other modes (e.g. intelligent speed adaptation) and a relaxation of the Rules of the Route/Plan. We will adopt a layered approach by examining nodes of increasing complexity on the South West Main Line before developing a detailed case study of Reading station and its approaches. Our methodology will consist of four main elements. Firstly, we will provide a state of the art review which will examine how nodal capacity problems have been tackled to date in Britain and overseas. We will also examine systematic approaches to innovative problem solving, as proposed by the TRIZ methodology and general systems theory. Second, we will develop a generic meso-level model and simulation tool, based on RailSys, which will determine train routeings and schedules, levels of disruption and reactionary delay and measures of capacity utilisation at nodes. Third, we will develop a micro-level optimisation by applying production scheduling techniques to rail scheduling, and by specifically investigating shifting bottleneck procedures and local search approaches. Fourth, we will integrate the simulation and optimisation models by using a multi-commodity integer programming formulation to examine cost versus service quality trade-offs, using techniques we have previously applied to rail freight. This will be used to determine the most effective technological solutions (including enhancements to signalling, switches and crossings) and operational solutions (including dynamic traffic management). In undertaking this work, we will be assisted by our industrial partners, Arup (operations) and Balfour Beatty Rail (technology). Arup will also use the Legion simulation model to determine the extent that pedestrian movements within the station may constrain the scheduling of trains through the station. Our key outputs will be prototype software tools that will assess the extent to which nodal capacity can be increased. This could be subsequently applied to other bottlenecks on the National Rail network. An advice guide would also be produced on measures to overcome capacity constraints at nodes.

Planned Impact

There will be a large number of potential beneficiaries of this research outside of the academic research community. This includes rail industry bodies such as the Association of Train Operating Companies, Network Rail and the supply industry, represented by the Railway Industry Association. It also includes public sector bodies such as the Department of Transport and the Office of Rail Regulation. At the international level, beneficiaries might include members of the International Union of Railways (UIC) and the Association of the European Rail Industry (UNIFE). For our Reading case study, beneficiaries will include local stakeholders such as Reading Borough Council, the South East England Development Agency and First Great Western. The two research fellows and the two research students we propose to involve in this proposal are also potential beneficiaries, along with some students on three related Masters courses. These benefits will mainly arise from the prototype modelling toolbox, and related documentation, which will be developed within this proposal. The toolbox will be able to indicate for any node of the rail network the extent to which capacity can be increased and/or capacity better utilised through technological improvements (particularly to signalling, switches and crossings) and operational changes. For our case study at Reading, we will make specific recommendations as to how the benefits from the proposed infrastructure investments can be maximised through complementary technological and operational measures. Our communications and engagement strategy will include two stakeholder workshops and a final dissemination event and a project website. We will employ clerical support to assist us in this. We will develop links with the Technology Strategy Advisory Group and the Advisory Group on Rail Research and Innovation in the UK and overseas bodies such as the Korea Railroad Research Institute, the JR Railway Technical Research Institute and the Association of American Railroad's Transportation Technology Center. We also propose an international expert panel of internationally leading Professors from Germany (Pachl), the Netherlands (Hansen) and the US (Barken). We will attend academic and industry focused conferences and seminars, publish in the academic and the trade press and produce a research monograph at the end of the project. We will engage with the relevant professional institutions and with the existing Knowledge Transfer Network in transport. We will develop collaboration agreements with our existing industrial partners, Arup and Balfour Beatty Rail. To exploit the modelling toolbox we will consider Knowledge Transfer Partnerships and Knowledge Transfer Secondments, based on the experience of Professor Chris Potts who has developed links with Logical Transport Ltd to develop resource scheduling applications. All those involved in this proposal will engage in impact activities, with appropriate support from the University of Southampton. We also propose to collaborate with other EPSRC/RSSB projects awarded as a result of this, and related, calls.


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Armstrong J (2017) Capacity utilisation and performance at railway stations in Journal of Rail Transport Planning & Management

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Armstrong J (2017) Addressing nodal constraints on the capacity of railways in Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit

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D Paraskevopoulos (Author) (2012) A cycle-based evolutionary algorithm for the multi-commodity network design model in 5th International Workshop on Freight Transportation and Logistics

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John Armstrong (Author) (2011) Developing a CUI-based Approach to Network Capacity Assessment in Railway Operations Research

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John Armstrong (Author) (2012) Scheduling Trains to Maximise Railway Junction and Station Capacity in International Conference on Advanced Systems for Public Transport

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John Armstrong (Author) (2011) Overcoming the Capacity Constraints Imposed by Nodes on Railway Networks in International Seminar on Railway Operations Research,

Description OCCASION's objective was to identify and investigate innovative methods of increasing the capacity of nodes (i.e. junctions and stations) on the railway network, without substantial investment in additional infrastructure. This project has involved four main tasks. Firstly, a state-of-the-art review of recent and on-going work in this area has been conducted. Secondly, a method has been developed to assess existing and predicted levels of capacity utilisation at nodes, using Peterborough on the East Coast Main Line (ECML) as a case study. Thirdly, approaches to optimising capacity at a particular node (or set of nodes) have been developed based on a 'Job Shop' approach to re-routeing and re-scheduling trains. Fourthly, the interactions between timetable changes at one node (Peterborough) and at adjacent nodes (broadly the ECML between London King's Cross and Retford) are assessed using a tactical planning model based on the Multi-Commodity Network Design Problem. These tools have then been used to examine incremental changes to existing railway technologies (e.g. improved switches and crossings) and operating practices (e.g. relaxations of the Timetable Planning Rules).

Following preliminary work on the South West Main Line, Capacity Utilisation Indices (CUIs) for the 190 individual links and nodes that comprise Peterborough station and the surrounding area were determined by ascertaining the detailed routeings of individual trains through the modelled network, aggregating and sorting the resulting times for all trains by individual node and link, compressing these to the minimum specified headways and margins, and thus calculating the individual and average utilisation indices. The job shop optimisation tool was then applied using a construction heuristic to generate initial timetable solutions, eliminating scheduled waiting time, and reducing overall capacity utilisation. An insertion mechanism was then used to add additional services; these results are then improved, using a Tabu search metaheuristic, and service frequency variations are minimised using a CPLEX solver. The tactical planning model, which was based on a hybrid evolutionary algorithm, was subsequently used to adjust the 'optimised' timetable to eliminate any congestion at adjacent nodes resulting from the initial solution. The initial network considered consisted of some 2,000 nodes and 6,000 links but this was reduced to consider the main stations and junctions on the network.

There are currently 53 train movements through Peterborough in the morning peak two hours and with optimisation this can be increased to 67. The CUI of the most heavily used node increased from 64% to 81%, with the latter above the maximum for mixed traffic lines in the peak recommended by international guidelines (75%). However, the average nodal CUI only increased from 23% to 25%. Despite this, the only additional train movements identified are off the ECML towards Spalding/Lincoln and Ely. The most important result was that optimisation could eliminate the 24.5 minutes of scheduled waiting time that existing trains faced with the current timetable. The tactical planning model identified the fast line between Peterborough and Huntingdon as a key bottleneck, with headways needing to reduce to 90 seconds before an additional London service could be added. Heterogeneous headways were assumed, replicating the existing situation. If headways could be homogenous (for example, three minutes), the number of trains through Peterborough could increase further but platform occupation constraints prevent additional London trains. The methodology developed illustrated how trains could be scheduled more efficiently (to reduce scheduled waiting time) and how extra services could be run on sections of the route considered, but there were no 'easy wins' in terms of additional London services.
Exploitation Route OCCASION was undertaken jointly by the Transportation Research Group (TRG) and the Centre of Operational Research, Management Science and Information Systems (CORMSIS) at the University of Southampton with industrial support from Arup on rail operation and Balfour Beatty Rail on the design of Switches and Crossings (subsequently Progress Rail and then Andy Foan Consultancy Ltd). Given the applied nature of the research, potential use in non academic contexts is one of the project's key objectives . An automated tool to develop capacity utilisation indices for any rail node on the national network has already been developed, is being applied and is receiving wider interest from industry. Plans are being drawn up to develop end user versions of the job shop scheduling and tactical planning software, whilst discussions are being held with train operators as to how our practical findings can be taken forward. The project was undertaken in conjunction with the Rail Safety and Standards Board (RSSB). RSSB organised a series of seminar with industry (including East Coast Trains) whilst the project's findings were disseminated via SPARK (Sharing Portal for Access to Rail Knowledge). The project benefitted from having an Advisory Board that included representatives of the Association of Train Operating Companies, the Department for Transport, EPSRC, Network Rail and RSSB. The project also benefitted from support from an international advisory group that included academics from the Braunschweig Technical University, Danish University of Technology, Delft University of Technology and the University of Illinois at Urbana-Champaign. Dissemination has involved over a dozen presentations to international conferences, including the World Congress on Rail Research and the Transportation Research Board, and active participation in the International Association of Rail Operations Research and the Rail Special Interest Group of the World Conference on Transport Research Society.

The capacity utilisation calculation methods and tools developed in the course of the project are being used by Arup in Network Rail's Capacity Charge Recalibration process, currently underway, and there is scope for their further use, together with the other tools developed, within the railway industry.

Although the project has numerically demonstrated the benefits of integrating the capacity utilisation calculation methods, the job shop optimisation and the tactical planning tools, further work is needed to automate the integration to be embedded in a practical software tool to be used in the rail industry. We have had discussions at the RRUK Association Conference (November 2012) with an SME who may able to collaborate with us in taking this forward. The resultant software tool would meet a number of rail industry needs. As Network Rail moves towards a more centralised and automated approach to timetable planning via the Integrated Train Planning System (ITPS), there is scope to incorporate these new methods and tools in the overall planning process, to provide increased nodal and network capacity for additional passenger and freight services, while maintaining timetable robustness and service reliability.

Subsequently, this work has been be taken forward by the Rail Technical Strategy Leadership Group's Future Traffic Regulation Optimisation (FuTRO) project. In September 2014, RSSB commissioned DITTO (Developing Integrated Tools to Optimise Rail Systems), a three year research project led by the University of Southampton, but also including Swansea University and the University of Leeds. The Interim Report for DITTO was delivered in February 2016, with the project due to complete in September 2017.
Sectors Digital/Communication/Information Technologies (including Software),Transport

URL http://www.trg.soton.ac.uk/research/rail/occasion.htm
Description Dissemination of findings has been on-going since OCCASION's inception in 2010. The research findings were co-produced with industry, in particular the Association of Train Operating Companies, the Department of Transport and RSSB. The finding that optimised schedules could eliminate scheduled train waiting times and release additional train paths has attracted interest from individual train operators such as East Coast Trains. The findings of OCCASION were disseminated to industry, in conjunction with three other projects, at a seminar in London organised by RSSB and held on 10 June 2013. The results were also disseminated by SPARK (Sharing Portal for Access to Rail Knowledge) which is managed by RSSB.
First Year Of Impact 2010
Sector Digital/Communication/Information Technologies (including Software),Transport
Impact Types Economic

Description Membership of Scientific Committees: the Future Traffic Regulation Optimisation (FuTRO) Project Control Board and the Vehicle/Train Control and Communications Systems Interface Committee.
Geographic Reach National 
Policy Influence Type Membership of a guideline committee
Description Future Traffic Regulation Optimisation (FuTRO)
Amount £905,000 (GBP)
Organisation Rail Safety and Standards Board 
Sector Public
Country United Kingdom
Start 08/2014 
End 08/2017
Description Impact Acceleration Account Knowledge Transfer Secondment
Amount £46,000 (GBP)
Organisation Arup Group 
Sector Private
Country United Kingdom
Start 09/2013 
End 09/2014