New paradigms and developments for the future of train traffic management. Paris, France

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1 New paradigms and developments for the future of train traffic management C. Lérin 1, X. Baumgard 2, G. Dessagne 1, F. Pinton 3, C. Weber 1 1 SNCF Innovation & Research Dept, 2 SNCF Engineering Dept, 3 SNCF Traffic Operation Dept, Paris, France Abstract The research program is carried out to design, prototype and experiment new decision support functions dedicated to the traffic management. In a final step, the objective is to connect these functions with the control and command layer, especially for route programming and transmission of speed or schedule instructions to trains. A new concept which is supported and modelled through the research program is the forecast train traffic plan. It updates the train traffic plan with the confirmed traffic management decisions and their foreseen consequences. This paper gives an overview of the target decision support system subject of the SNCF research program. Introduction When incidents or delays occur during train operating, decisions have to be made quickly to limit the consequences of this situation and to avoid snow-ball effects. This problem is complex because of the limited efficiency of local decisions and the quasi-necessity to build a global view of the potential consequences before choosing the best solution, or at least good ones. From the mathematical point of view, this problem is difficult and highly combinatorial. Despite of their great expertise, traffic managers and dispatchers come up against difficulties for estimating the impact of the occurring events, the consequences of their potential decisions, and to inform concerned people once decisions have been made. Additional difficulties arise from the fact that train traffic is increasing whereas traffic control centres become larger and larger in order to manage the whole traffic more globally. The research program is carried out to prototype and experiment helpful decision support functions for traffic management. The main objectives of such a program are to: - allow operators to better control disrupted situations and to improve their reactivity face to deviations and disruptions, - improve the quality of service of traffic management: reliability of the process; punctuality of trains; quality and precision of information given to train operating companies about the incidents and events, and about their consequences. Methodology The research program is carried out upon five main directions. Three axes concern the design and prototyping of decision support tools for the main traffic management functions which are: - traffic supervision, with projection of the foreseen consequences of the events and incidents; - primary incident management, with, among other themes, statistical estimation of the incident duration; - management of the incident consequences, with the help of what-if functions allowing the traffic manager to simulate solutions of his own, and re-scheduling functions proposing solutions to the operator. Beyond the simulation and optimisation approaches used for the prototyping of such tools, important themes are: the acquisition of knowledge about events and incidents, and the new representation modes for the user interfaces.

2 The research program follows also two transversal axes dealing with: co-operation methods and tools between the different actors of the traffic management process including external actors such as train operating companies, who interact a lot with the traffic management process; and human management, which mainly focuses on the ergonomics and acceptability of the new generation of decision support tools. These five axes are not sequential. There are linked all together and their interaction is a fundamental key of the traffic efficiency. A new concept: forecast train traffic plan Today, traffic management mainly relies on knowledge and representations of theoretical and current train traffic. The theoretical traffic plan stays the reference to comply with, whereas the situation and disruption of traffic make it temporarily unreachable in many real cases. Co-ordinating all involved actors is difficult, particularly when information about the state of the global system, the train location, etc. are imprecise and give too limited prediction for inferring the consequences of deviations from the plan. In order to overcome these difficulties, operational actors are quite free to interpret and act consequently the better as they can, according to their great professional experience, but without a real vision of the global objective. The new paradigm will give the priority to the global objective and plan, which the actions relative to local constraints should be subordinated to. The new concept which is supported and modelled through the research program is the forecast train traffic plan. It is the updated reference of the train traffic plan with the more recent decisions and their foreseen consequences. This is a great vector for information and decision broadcasting to concerned actors and systems. Theoretical train traffic plan t0 Forecast train traffic plan ti Traffic management Decisions taken between ti and tj Forecast train traffic plan tj Figure 1: forecast traffic plan The communication of this plan is done by: - display on man machine interfaces such as space-time diagrams, - transmission to the control-command layer mainly the system in charge of program and command of train routes, - transmission to other concerned systems and actors. The research program aims to allow planning and broadcasting of the forecast train traffic with the help of new decision support functions. Several steps are concerned, which are described in the following of the paper.

3 The target users of the new decision support system Three main responsibility levels are concerned by the traffic management process: - The control and command level, which is achieved by operators named agents circulation, that today are mainly in charge of security actions, and programming and command of train routes. The new system in deployment phase dedicated to these actors is MISTRAL. It provides accurate control views of the traffic in real-time and adapted mamachine interfaces for programming and commanding the routes for the trains. Automatism for local traffic management can be parameterised; for example, rules similar to the FIFO principle (for homogeneous traffic) or automatic programming of the theoretical traffic plan can be set. These automatisms can of course be bypassed by operator. In the target version of our system, the forecast traffic plan will be automatically programmed into the control and command system. The control and command level is not a target user of our decision support system, as it has a limited role in traffic management. This is the subject of other prospective studies relative to new human-machine interaction for example, that are outside the scope of this paper. - The regional traffic management level, organised around several juxtaposed centres covering the national infrastructure. This level is in charge of traffic management within its concerned geographical area: supervision of the train traffic, diagnostic and management of occurring incidents, management of the consequences of the incidents on the planned traffic and works (rescheduling). Traffic managers indeed mentally build the forecast traffic plans dealing only with their geographical areas. Existing tools support their missions, with graphical outputs such as space-time diagrams (GALITE tool) superimposing theoretical and current traffic. However, when incidents occur and disrupt the traffic, the current tools are not adapted for facing and solving the problems. Intensive oral communication must be engaged between actors in order to characterise the situation, find solutions and broadcast them. This level of management is the first privileged target of our system. - The national traffic management level, constituted by one national centre. Around the national traffic managers, operators from train operating companies are present to dialog and built new transport plans in case of major incidents or events. The national traffic management level is in charge of directly managing special traffic axis, such as high speed lines, and co-ordinating actions of the regional traffic centres in case of important incident or event often involving reduction of capacity. Today, the national traffic managers rely mainly upon the EXCALIBUR system [4]. This system centralises information about the network characteristics in order to quickly provide detailed information on and around the location of incidents. Incidents characteristics and management steps are described in realtime by operators into the system. That allows to broadcast information automatically, via Intranet geographical views or alert s. Moreover, this activity feeds a database that is used to estimate the duration of incidents in real-time, by comparison with similar incidents and statistical analysis of durations. Although the EXCALIBUR system is a first advanced step for decision support, two main complementary axes are to be developed. The first one aims to increase the effectiveness of the management system with the regional traffic management level and the train operating companies. The second one aims to improve and increase the decision support functions. This level of management is the second privileged target of our system. Traffic supervision and diagnostic The objectives of our supervision functions are classically to help operators for: 1. following the effective running of operations in order to correct it if necessary, 2. anticipating problems in order to have more time to solve them.

4 Knowledge of the current state of the traffic system Today, existing systems that follow the effective running of traffic are based on detectors installed on the infrastructure that are often too much spaced to give an accurate view of the traffic running and to detect problems in real-time. A system based on GPS technology enables to follow in real-time how the traffic is going on the network (current location, speed, delays, unexpected stops of trains, etc.). Combined with the ground detectors, this should be the basis of our system. Knowing the current state of the traffic system also means being aware in real time of the occurring (or foreseen) events and incidents that may have an impact on the traffic. This knowledge is today mainly acquired by oral and phone communication and is not always formalised into numerical systems. The EXCALIBUR system already stores and broadcasts real-time information about the main disruptions on the network (cf. figure 2). It constitutes the first milestone of our future information system about events and incidents tracking. We cannot get away from manual input for this kind of information, but we pay particular attention to the development, where possible, of automatic capture of data and alarm correlation and diagnosis. Figure 2: EXCALIBUR national view of incidents Estimation of the forecast state of the traffic system and anticipating problems Providing the forecast state of the traffic system to the operators will be helpful for anticipating problems, and then having more time to solve them. This function will be allowed by the continuous simulation and projection of the future states of the system, according to: - the last forecast traffic plan, - the current state of the traffic system (cf. previous paragraph), including the events and incidents occurring on the network and their estimated duration, - the knowledge, when possible, of future problems; for example, train operating companies shall inform as soon as possible the traffic manager of departures foreseen with delays, - the routes programmed by control operators who may have bypassed the last forecast traffic plan for some reason.

5 At the finest level, the kernel of this function calculates the forecast running of the trains, knowing their current characteristics and performances, the routes they have to follow (taking into account the current state of the infrastructure speed limitations, ), according to the last forecast traffic plan. The automatisms parameterised in the control and command system and the programming actions of operators are taken into account in the simulation, in order to allow the traffic managers to detect the eventual deviations from the last forecast traffic plan. Moreover, the events and incidents known by the system are included in the simulation, in order to allow the operators to anticipate their consequences on the traffic. This simulation will allow the operators to anticipate the deviations from the last forecast traffic plan, by: - visualisation of the projections on graphical interfaces (e.g. Space-time diagrams), - warnings about predicted conflicts between trains (and/or works), - indicators of deviations from the forecast traffic plan (delays, alerts on level of disruption, capacity reduction, ). Aggregated views of the forecast state of traffic have to be defined and produced, according to the levels of traffic management. Research works particularly concern here the real-time capacity and accurateness of simulation. A compromise has to be found between: - Microscopic simulation, that is up to give the more pertinent results, but needs many detailed data, particularly on infrastructure, and could require too much calculation time for real-time application; this kind of simulation is used in the SISYFE simulator [3], today used in traffic studies and robustness evaluation (cf. figure 3). - Macroscopic simulation, that provides less precise projections, but should be more compliant with real-time needs. This kind of projection is used in the LIPARI simulation environment of traffic management systems [6]. Figure 3: traffic simulation with SISYFE A train is delayed (bold dotted line) and SISYFE simulates the consequences on the other trains. Estimation of incident duration Concerning important incidents generally involving capacity reduction, the estimation of their impact on the traffic is strongly related to the value of the estimation of their duration. The

6 duration of an incident depends on many factors, such as the type (and subtype) of incident, its location, etc. EXCALIBUR provides today estimation about incident duration, statistically calculated from stored similar incidents (cf. figure 4). Research works are realised for refining this estimation (see [2] and next paragraph). 50% of this kind of incidents last less than 2h30 (median) 50% of this kind of incidents last between 1h30 and 4h03 If the incident lasts more than 4h00, its duration may reach 16h Figure 4: EXCALIBUR information box plot about estimated duration of incidents Incident management According to the nature, location and context of the incident, a lot of operations are to be done and supervised (emergency operations, infrastructure release interventions, etc.). Different scenarios can be built and evaluated for re-establishing the normal situation, in particular when a choice is possible between immediate, partially or totally postponed, repair of infrastructure. The impact of these scenarios on the traffic is evaluated in adapting and re-planning the forecast traffic plan see next paragraph. Once a scenario has been chosen, the effective running of operations has to be followed in order to be able to identify deviations from the scenario, re-evaluate the incident duration if necessary and re-plan the traffic forecast plan. It is considered to help the incident manager with tools to pilot the incident in a project management way, with the help of GANTT-like predefined diagrams (or on-demand built). Each of the needed operations for the incident management will be clearly formalised, with the necessary human resources team, the dependencies with other operations, the estimated duration time, etc. The global incident duration will be re-estimated automatically according to the endings of operations. These diagrams will be managed in real-time, and will allow the system to provide appropriate alerts about deviations of the forecast traffic plan. Adapting and re-scheduling forecast train traffic plan The supervision and diagnosis functions will allow the operators to estimate the level of disruption, to know which problem(s) they are facing, and then to enter a solving mode. A first level of decision support will offer what-if functions to the traffic manager in order to allow him to simulate solutions of his own, and to check their efficiency, before confirming one or several of those. The efficiency is measured by projecting and simulating the consequences of the decisions, and providing consequently performance indicators, for example the expected delays at strategic points (main stations, forks, etc.). A second level of decision support, that can be combined with the first one, will propose scenarios or new solutions to adapt the traffic plan or re-plan it, according to the level of

7 disruption (minor or extensive). This level will rely on predefined scenarios (when possible), case-based reasoning, and optimisation techniques. We can distinguish two main levels of disruption: - minor disruption level, which can be solved with actions such as re-ordering of trains or changing routes inside nodes. These disruptions are generally solved at the regional traffic management level, as they do not need strong co-ordination between centres. The adapted partial forecast traffic plan, once confirmed, is propagated to the next centres via the projection functions (cf. figure 5). - extensive disruption level, which is often related to reduction of capacity and which is mainly solved at the national level of traffic management. In that case, the traffic management has first to make the trains already on the network reach their destination, and then to determine the new traffic plan according to the available capacity. Decisions such as re-routing of trains or partitioning of line operations are made. This level of disruption needs interactive communication between the traffic manager and the train operating companies, for building the upper level forecast traffic plan. Once built and confirmed, the plan will be transmitted to the concerned regional traffic management centres to be eventually refined according to local constraints (track affectation in stations, residual conflict solving, etc.). After confirmation by the traffic managers, the forecast traffic plan will update the programming sequences at the control and command level for application. National traffic management centre (NTM) Regional traffic management centre (RTM) System NTM System RTM Regional traffic management centre (RTM) Remarkable points (RP) : Important RP visible at NTM System RTM Flow: Forecast times and speeds at boundary RP of enlarged NTM Forecast times at important RP Boundary point between two enlarged RTM Other point Figure 5: transmission of forecast traffic plans between regional traffic management centres Research works deal here in particular with the design and application of models and solving techniques for the traffic adapting and re-scheduling problem. Collaborative works with universities and public research centres are carried out in the framework of this research field (cf. [5] for some details about them). Schedule or speed instructions to trains A further step concerns the transmission of schedule or speed instructions to trains, in order to enhance free flow traffic in nodes or in line. Once the forecast traffic plan has been determined

8 and programmed, residual potential conflicts may locally remain (or appear). These small disturbances could be managed precisely by local free flow functions that aim to minimise the impact of the conflicts. The figure 6 gives an example of free-flow traffic simulation with the LIPARI tool. Train T1 Train T3 Train T2 Figure 6: free-flow traffic with LIPARI of three trains running on a track crossing Planned paths are in black. Train T1 has a delay of 5 minutes. Without speed instructions (red paths), the trains T2 and T3 lost time because of conflicts with respectively T1 and T2. With reduction speed instruction before the track crossing (blue paths), T2 and T3 encounter line clear signals, and delays are reduced. Research works and prospective studies have been realised on free-flow traffic (cf. [1] and [6] for the more recent ones). If it is recognised that the performance of the traffic system is increased with such techniques, some prerequisites must be achieved before operating them: train precise location and speed acquisition, means for transmission and presentation of instructions to drivers, coherence with signalling information, etc. The deployment of free-flow techniques will be facilitated in the framework of the present research program, in addition with other current prospective works about new information system for drivers. Ergonomic approach of new traffic management decision support functions The research works on decision support tools for traffic management have to take into consideration their use by the operators and the impact of these new artefacts on their competences. The operators activities could be deeply modified by the new concepts and functionalities that are studied. For that reason, research studies also include the determination of traffic management cognitive mechanisms and the modelling of the human-machine interaction. This topic includes also ergonomic improvement for the screen views, and new representation modes, in particular for supervision functions.

9 An early implication in the project of the concerned actors is also realised to ensure the success and acceptability of the project. Potential for implementation The main SNCF opportunity for the implementation of such a research program is the current RFF 1 project for the concentration of command and control centres. This project will lead to the generalisation of infrastructure installations remote control, and in the homogenisation of control centres technologies. These two important aspects of the project give the potentiality for the deployment of innovative decision support tools. This research program offers two major interests for railway business. The first and main one is of course turned towards Traffic Managers who this research program is dedicated to. The second concerns Train Operating Companies who will appreciate to increase the punctuality of their trains and to obtain better and more precise information about the current situation and the estimated delays of their trains; that will allow them to better master their production and anticipate the consequences of incidents on their resources planning, as to better inform their customers. Acknowledgements We gratefully acknowledge all the SNCF staff participating to the research program as well as our precious academic and industrial partners. We also want to address special thanks to our PhD students, trainee engineers, and service suppliers for their involvement and realizations in our projects. References [1] X. Baumgard, C. Lérin and A. Gouvernaire, Automatic speed management of the trains within a node, Proc. of WCRR Seoul, (2008) [2] M. Chandesris, Dynamic and real-time prediction of duration of incident, Proc. of WCRR Seoul, (2008). [3] M. Fontaine, D Gauyacq. SISYFE: a toolbox to simulate the railway network functioning for many purposes. Some cases of application, Proc. of WCRR Köln, (2001). [4] D. Gauyacq, P. Tariel, A. Lhote, D. De Almedia and M. Pellion. Outils d aide à la supervision et à la gestion en opérationnel des circulations, Revue Générale des Chemins de fer, n 143, p.17 (2005) [5] L. Gély, G. Dessagne and C. Lérin, Modelling Train Re-scheduling with Optimization and Operational research techniques, Proc. of WCRR Montreal, (2006) [6] C. Lérin, C. Joie, LIPARI: train management solutions for very dense traffic flows, Computers in Railways, (2004). 1 As owner and manager of the French rail network, RFF (Réseau Ferré de France) is responsible for its maintenance and operation. As required by the French government, these responsibilities are carried out by RFF and SNCF, to which management has been delegated.