Computers in Railways VII, C.A. Brebbia J.Allan, R.J. Hill ... · approach for decentralised...

Train control by multi-agent software systems

A. Fay

ABB Corporate Research, Heidelberg, Germany.

Abstract

Train traffic reaches - in its current form of operation - more and more the limitsof its infrastructure. Therefore, new control concepts are being investigatedwhich allow a more efficient usage of the existing infrastructure. A promisingapproach for decentralised control are intelligent agents. They provide a meansfor flexible resource allocation and, thus, for achieving an optimised balancebetween infrastructure load and customer requirements. The paper describes howintelligent agents can be used for the flexible planning and operation of railwaysystems.

1 Motivation

Several railway systems are already restricted (in the amount of traffic beingcarried) by the limitations of their infrastructure, and even more will be facedwith this situation in the near future. Instead of infrastructure extensions, whichbear enormous costs and are difficult to realise today, smarter train traffic controlapproaches allow for a more efficient utilisation of the existing infrastructure.Today, the infrastructure use is not at equilibrium, i.e. there are overloadedtracks and - more or less parallel - tracks with open capabilities. Therefore,incentives have to be given to increase operation flexibility and to use thepreferable track - which might be also a side track. A well-balanced usage of theinfrastructure can be achieved by employing modern information technology fortraffic control.

The situation becomes even more pressing as existing governmental railwayinfrastructure monopolies are - similar to telecommunication and energymonopolies - gradually replaced by commercially-organised and competinginfrastructure operators. The operators' desire to make optimal use of the

Computers in Railways VII, C.A. Brebbia J.Allan, R.J. Hill, G. Sciutto & S. Sone (Editors) © 2000 WIT Press, www.witpress.com, ISBN 1-85312-826-0

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infrastructure has to be balanced with the transport needs of the users. Aneffective and efficient conflict management will become more and moreimportant due to the growing number of companies and organisations involvedand their different interests. This includes the on-line marketing of slots, i.e. aflexible reaction on changing demands, and to take into account the currentinterests and priorities of the different customers for the railway infrastructureconflict management. Dispatching activities will in the future be partially shiftedto the customers, who can decide which connections to maintain etc.. In case ofadditional costs due to the shift of a slot, the parties involved have to negotiateabout the conditions and compensations. Often third parties will be affected byshort-term changes, which again have to be contacted for negotiations.

Today, due to missing information, dispatchers cannot respect the economicvalue of each train in each case. The complexity of the railway network and thetraffic operated on it result in overcharge of the operator's staff.

The requirements for a future slot management are, according to Partzsch [1]that it has to be

• reliable,• manageable,• discrimination-free,• optimal regarding traffic flow,• optimal regarding usage of resources,• flexible,• transparent but• confidential regarding sensitive customer data,• based on computer communication means.

Previous attempts, which aimed at a centralised short-term dispatching haveearned little success, because the spatial and temporal allocation of the tracks istoo complex: too many parties involved, too many combinatorical possibilitiesexist, too much dynamics in the behaviour of the system. A centralised controlapproach will be more and more difficult and clumsy. For example, on thenetwork of German Rail (DB), more than 35.000 train journeys are carried outeach day. This amount can with the methods of the past only be handled on along-term basis, leaving little space for short-term changes and optimisation. Theeven increasing deregulation in transport markets, both for regional and foreigntrain operators, will further increase the problems sketched above.

Therefore, a decentralised solution for the problems seems desirable.Concepts have already been sketched in the past for a decentralised trainprotection (e.g. Pierick et al. [2], Hertel [3]), but only with modern informationtechnology, a true decentralised approach can be implemented that fulfill theabove requirements and that will be robust, flexible, easy and inexpensive toinstall and maintain, and have to provide easy access for further traffic providers.


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2 The idea: traffic control by intelligent agents

Multi-agent systems (also often called "intelligent agents" or "autonomousagents") offer a promising concept for decentralised train traffic control,especially regarding the design of the software used. They are distributed, thusrobust in case of disturbances, flexible with respect to rapidly changingoptimisation aims and possibilities, and can adapt to their environmentalconditions.

Multi-agent systems for traffic applications have already been proposed forthe optimisation of transport needs. Buckert et al. [4] describe how agents canco-ordinate the combination of smaller transport tasks between differentshipping agencies. Applied on railway traffic, this resembles an optimisation ofthe "Train Coupling and Sharing" concept by agents as described by Zirkler etal. [5]. In both cases, agents are responsible for one lorry or train, respectively,and their co-ordination and possibly combination.

The system described in this paper, however, goes one step further, insofar asthat not only are the trains (as the moving and naturally "active" objects of thesystem) represented by agents, but also the track segments, which have beentreated as passive objects in the past, and their objectives (which are theobjectives of their owner) are represented by agents, too. Thus, track segmentagents can communicate with train agents to let the train safely travel on thetrack segment. Not only the train can reserve the desired track segments, but alsothe track segments can offer their service to trains. The payment has to benegotiated between the train and the track segment by their respective agents.Furthermore, the multi-agent system is capable of solving conflicts, which ariseby competing requests (different trains which request the same track segment atthe same time), by negotiations between the agents involved. The agentapproach is based on object-oriented concepts (see section 3) and, thus, allows tohide confidential information. This fulfils the confidentiality requirements of theparties involved in a much better way than former centralised planningprocedures which require all relevant data to be communicated to the networkoperator.

For train traffic operation and planning, two tasks have to be accomplished:

• determination which track should be taken for a journey -> request thenecessary track segments -> reservation of these track segments (withoutsafety relevance)

• assignment of track segments to trains (with safety relevance)

According to this distinction, an agent concept for these tasks is described insection 4 and 5, respectively.



3 Introduction to agent technology

3.1 Agents and object technology

Agents are based on distributed systems technology and on object technology.They show synchronisation and shared usage of resources like other distributedsystems, but with a higher degree of autonomy: the sub-systems are no longerco-ordinated by a central agency but co-ordinate their activities themselves.From object technology, agents inherit several aspects:

• Modularisation: the complex system - both data and methods - aredistributed into components (objects) with minimal interfaces betweenthe objects

• Encapsulation: internal data is hidden for the outer world and can only beaccessed (read/write) via well-defined interfaces

• Class structures: similar objects are grouped into classes

An agent does not only consist of a set of data, but also owns the methods tomanipulate this data and to communicate with its environment (e.g. otheragents). The multi-agent system comprises of several agents which cancommunicate with each other.

Agents extend the idea of object orientation by intentions and behaviour (e.g.Shoham [6]). The intentions can be subdivided into strategical intentions, i.e.long-term objectives which are usually fixed at system design, and tacticalintentions, which serve to achieve the strategical intentions and determine thesingle actions of the agent. The order of actions and their relation to the state ofthe agent's environment form the behaviour of the agent. Agents can be regardedas small expert systems, whose behaviour is determined by intentions (often inthe form of rules) and which can communicate with each other and whichoperate via "sensors" and "actuators" in their environment.

3.2 Features of agents

An agent is an instance which tries to achieve predefined goals by means ofautonomous actions. An agent represents a certain person or object that it actsfor. In the case of agents representing real persons, complex social or economicsystems can be modelled and analysed - and also individual traffic. But it is alsopossible to assign agents to objects which have no intelligence of their own. Inthis case, agent systems can be used for planning and co-ordination of theactions of these objects.

To be able to act for a person or an object, an agent needs a certain degree ofautonomy. The autonomy is limited by the predefined intentions, by the amountof resources available (both for the agent itself and in the environment), and bythe methods given to the agent.

Autonomy means freedom. But freedom needs intelligence to be able to makeuse of it in a sensible way. Therefore, an agent must be able


Computers in Railways 171

• to acquire information from the environment (which might include otheragents),

• to interpret ("understand") this information,• to derive suitable actions from its intentions,• to act on its environment,• to detect whether its actions were successful, and to which degree it has

achieved the goals,• to adapt its tactical intentions and its actions accordingly.

Though mobility is sometimes called a characteristic feature of agents, this is notalways required - not even for agents for railway systems. In the conceptsketched in this paper, some agents represent immobile objects, some representmobile objects, but the agents itself reside in their location.

3.3 Suitable fields of application

Agents can especially be applied in domains

• where the task to be solved is functionally and/or locally distributed ontosub-systems,

• where these sub-systems have to communicate heavily with each other,• which are subject to dynamical changes.

Applied in these domains, agent systems offer the following advantages:

• the complexity of the system can be coped with by "natural" splitting anddistribution of the task to be solved,

• the sub-systems are more robust and can adapt to changes in theirenvironment.

If the strategical intentions or the objective function of the agents differ, conflictsarise. These conflicts can be solved via negotiations between the agents.

4 Agents for train route planning

4.1 Changes in today's train route planning conditions

Conventional railway planning assigns each train for each journey a certaintrack, i.e. the arrival and departure times as well as the track segments to be usedbetween the stations are fixed. For regular (repetitive) journeys, this time table isestablished and published months in advance. The time table forms the basis

• for crew and resource scheduling• and for the underlying planning on the customers' side.

If additional demand arises on a short-term basis, i.e. a day or some hours beforethe journey should take place, the time table will be checked for the feasibility ofaccomplishing this additional journey without interfering with or infringingother traffic. If the additional journey is considered to be of major importance,


822 Computers in Railways VII

the schedules of other trains will have to be adjusted to include this journey. Thisshort-term re-planning is usually accomplished by the network operator's staff.

Customer 1 ) ( Customer 2 ) (Customer 3 ,

Fig. 1: State-of-the-art of customer-railway relationship

According to European Community law, in the near future, network operator andnetwork user will no longer be identical (as shown in Fig. 1) but will be separateparties. Therefore, the network operator's staff has to negotiate with theresponsible persons of the carrier (the network user, i.e. the customer of thenetwork operator) (Fig. 2).

Fig. 2: Separation of network operator and carrier

In the course of deregulation, the railway traffic market will be faced with agrowing number of railway traffic providers (carriers). The assignment of slotsto carriers has to follow certain rules to assure that it is free of discrimination(Fig. 3). The increasing competition between the carriers will increase thecustomer focus, especially to more respect for short-term customer demands.These tendencies cause significantly higher effort for traffic co-ordination and,thus, higher requirements on the quality of the track assignment, which can - bymeans of the state-of-the-art procedures - no longer be met by the networkoperator's staff.

Furthermore, it has to be taken into account that also the infrastructure willnot necessarily be in the hands of just one party, but alternative networkoperators might compete on the market (Fig. 4), which will again complicatematters.


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Customer 1 ) ( Customer 2 ) ( Customer 3

Fig. 3: Scenario with several competing carriers

Customer 1 ) ( Customer 2 ) ( Customer 3

Fig. 4: Scenario with several competing railway networks

4.2 Agents for track segment reservation

A need for transportation is characterised by certain desired figures, like origin,destination, time of departure, time of arrival, time interval, additionalrequirements, and maximal costs. These characterising figures might be given ascrisp or fuzzy numbers.

First, a carrier decides (at an arbitrary point in.time) which journeys shouldbe carried out at which time. The carrier defines the chain of stations to beserved, the rough arrival and departure times at these stations, and the maximumamount of money to be spend for the use of tracks. Then, an intelligent agent isin charge to put this transportation need into reality. This agent (henceforthcalled transportation need agent or for short T-agent) collects information aboutpossible routes between the stations to be served and the usual travel times onthese routes. This information might be available via digital maps orgeographical information systems (GIS). The GIS is based on the infrastructuredata of one or more network operators. The communication interface to theseGIS have to be standardised European-wide to assure discrimination-free accessfor all carriers. From the GIS, the T-agent receives pointers to the intelligentagents which manage the track segments on the different routes (henceforthcalled segment agents or S-agents). These segments can be real track segments



but also virtual segments (without a fixed physical counterpart) to allow forflexible adaptation of the track segments' lengths.

The T-agent selects one or several possible routes, sets up a priority list, andstarts negotiations with the S-agents of all the segments of one or several routes.The T-agent asks for the costs of the usage of the needed segments, sums themup for the different routes, and compares with the allowed costs of the journey. Ifthe sum of the costs lower than allowed, the journey can be carried out.Otherwise, the T-agent can try to negotiate with the S-agents to achieve a lowersum of costs. If the costs can be reduced by negotiation down to the allowedamount, the journey can be carried out. Otherwise, the T-agent might contact thecarrier to ask whether a higher price is acceptable. If not, the journey cannot berealised.

If the journey can be carried out, the T-agent reserves the needed segmentsfor the time interval agreed upon, i.e. closes a contract with the S-agents that henegotiated with.

In the above description, the T-agents have the more active part. But the S-agents can also take over a more active role - since it is in their interest to getenough journeys on their track segment to cover the costs of the infrastructure -and offer their service to T-agents. If several T-agents are interested in the sametrack segment at the same time, the S-agents can even select the most solventone.

4.3 Advantages of the proposed concept

With the concept described above, the necessary negotiations about tracksegment usage, which today have to be carried out between the staff of theinvolved parties, are automated and decentralised. Thus, several advantages canbe achieved:

• A parallel co-ordination of many journeys is made possible, which allowsfor individual and short-term inclusion of new journeys - which wouldhave been impossible if tried manually.

• Short-term re-planning of journeys, like changes in routes and departuretimes, becomes possible.

• The robustness of the railway system is increased because disturbancesconcerning one train or one track segment or one route or onecommunication link cause only limited deterioration of service, and thesystem can easily adapt to this situation by re-negotiating.

• The procedure and, thus, access to the network, is discrimination-free.• Network operation becomes more profitable, and both parties achieve

staff savings.

The formation of payments is no longer determined by the costs of the trackonly, but a result of supply and demand on the transport market. In the past, lessused side tracks were relatively expensive because the fixed costs were dividedby the few trips carried out on these tracks. Now, less used tracks are offered -



better: they offer themselves! - at relatively low prices, thus drawing traffic awayfrom the crowded main routes.

5 Agents for track segment assignment

In section 4, a concept was described to plan railway traffic by means ofintelligent agents. In addition - or even independent of this - it is also possible touse the agent concept for the save operation of railway traffic. In contrast to theabove, the agent system used for the operation of traffic has to meet significantlyhigher safety requirements - but the general idea is the same.

To avoid collisions, each track segment must not be used by more than onetrain at any time. Today, the routes for a train are set either manually, orpreselected routes are assigned to trains automatically. The former variant isexpensive and error-prone, the latter not flexible enough. Applying the agentapproach, for each train the best route can be reserved and locked.

The basic scheme is as follows: each train (better: the related T-agent)reserves its route itself, but not by selecting from a set of pre-defined routes, buton an individual basis by reserving the track segments which are needed for anoptimal course of the journey. This can be done some hours or even minutesbefore the respective track segment is used.

In this concept, both T-agents and S-agents act autonomously. First, the T-agent calculates an optimal order of track segments to be used, taking intoaccount the current situation and latest information (e.g. about which tracksegments are available and not used otherwise or out of order). On the basis ofits dynamic characteristics (position, speed, acceleration), the T-agent calculatesthe time intervals at which the individual track segments are needed. Then, theT-agent contacts the respective S-agents and makes an obligatory reservation.Thus, the track segment is blocked for other trains for this time interval. The S-agent confirms the reservation. After the train has passed the track segment, it isfreed again for further use by other trains.

Of utmost importance for the safe operation of this scheme is acommunication technology that prevents errors during reservation andconfirmation with sufficient probability.

By means of this approach, it is possible to automatically find the bestpossible route even in the case of short-term changes (like track failures orbroken-down vehicles). A further advantage is that the track segments are onlyreserved for the time needed. Thus, the capacity of the railway network can bemade best use of, and costs are minimised.

The concept for train route planning described in section 4 can be combinedwith the concept for train operation sketched in this section: the concept ofsection 4 is in that case an economically binding, but not safety-relevant pre-reservation of track segments, which forms the contractual basis for the safety-relevant reservation and blocking of track segments described in this chapter.



The similarity of the approaches described in sections 4 and 5, respectively,demonstrates the universality and scalability of the agent concept: it can be usedfrom the long-term planning down to short-term re-planning and dispatchingactivities. Thus, it overcomes today's system breaks between planning andoperation tasks in railway traffic.

6 Conclusion and Outlook

The paper describes an approach how "intelligent" agents can be employed fortrain traffic planning and operation tasks.

The system described is based on the concept of each train being anautonomous agent, trying to find an optimal route through the railway network(optimal with respect to travelling time, schedule, costs, customer interests, etc.),and each edge of the railway network being also represented by an autonomousagent, aiming at optimal utilisation of the capacity of the track and achievingmaximum benefit for the railway network provider. The short-term parallelnegotiations between train agents and track agents allow to overcome thedeficiencies of the past, when this had to be planned months in advance andallowed for little flexibility. The system described makes use of conceptssuccessfully applied in other domains (like telecommunication networks and theinternet), thus offering a promising solution for the flexible planning andoperation of railway systems for the mutual benefit of the train owner and therailway network owner.

References

[1] Partzsch, L.: Kundenorientiertes und flexibles Betriebsmanagement.Eisenbahntechnische Rundschau, BahnReport, 1997

[2] Pierick, K.; Wiegand, K.-D.: Die MCDS-Technik als Basismodul einerrechnerintegrierten Prozessregelung fur Bahnen. EisenbahntechnischeRundschau, 1994, Heft 11

[3] Hertel, G.; Senger, D.: Technologische Trends der Bahn.Eisenbahningenieur, 1998, Heft 3

[4] Biickert, H.J.; Fischer, K.; Vierke, G.: Transportation scheduling withholonic multi-agent systems - the teletruck approach. PAAM'98, London,1998.

[5] Zirkler, B.; Bocker, J.; Lind, J.: Optimising operation management with amulti-agent approach - using TCS as an example. WCRR'99, Tokyo, 1999.

[6] Shoham, Y.: Agent-Oriented Programming. Artificial Intelligence,Elsevier, 1993.


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