Multi-agent Framework for a Virtual Enterprise of Demand-Responsive Transportation Daniel Cabrera and Claudio Cubillos Pontificia Universidad Católica de Valparaíso, Escuela de Ingeniería Informática, Av. Brasil 2241, Valparaíso, Chile
[email protected],
[email protected]
Abstract. This work presents a multiagent framework design for DemandResponsive Transportation, considering a virtual enterprise domain. The agent architecture obtained provides a baseline for the integration between end-users of the transport service and multiple transport operators affiliated to a virtual enterprise which provides flexibility in the incorporation and leaving of transport operators. The participation of governmental organizations and active destinations within the system allows the virtual enterprise having additional information on potential opportunities of business and assures transport system users a wider and more complete service search. The PASSI methodology has been used as base software engineering methodology for leveraging the multiagent architecture. Keywords: Framework, Agents, Virtual Enterprise, Demand-Responsive Transportation, PASSI.
1 Introduction Passenger transportation in urban areas constitutes an increasingly important problem in our society. Given the quantity and nature of the different actors involved in the passenger transportation scenario, it is required that these systems are able to effectively integrate various heterogeneous systems, and provide criteria to ensure the efficiency and quality of service to passengers. Therefore, the trend is to move from a group of transport operators, partial or totally disconnected among them, towards the conformation of an integrated transport service, sustained by a virtual enterprise (VE) for passenger transportation. The framework development has been realized on the basis of the use of PASSI (Process for Agent Societies Specification and Implementation) [1], a multiagentoriented methodology for systems development, which integrates design models and concepts from both, OO software engineering and artificial intelligence approaches using the UML notation. Additionally, we have incorporated some elements offered by a non-standard UML profile called UML-F [7], devoted to the development of object-oriented software frameworks. The novelty of our work relies on conceptualizing the integration of diverse passenger transportation operators as a Virtual Enterprise and modelling it as a multi-agent S. Bergler (Ed.): Canadian AI 2008, LNAI 5032, pp. 66–71, 2008. © Springer-Verlag Berlin Heidelberg 2008
Multi-agent Framework for a Virtual Enterprise of Demand-Responsive Transportation
67
framework. A second issue is the use of PASSI complemented with a general process for framework development plus UML-F for formalizing the variable points in the resulting agent architecture.
2 Related Work In some european countries, pilots for DRT systems were developed during projects such as SAMPLUS [9], SIPTS [3], and FAMS [5]. Regarding to examples of MAS applied to ITS, only to mention some iniciatives, Roozemond and Danko [2] proposed a UTC model primarily based on several coupled intersection control Intelligent Traffic Signaling Agents (ITSA), some authority agents and Road Segment Agents (RSA). In 2001, an intelligent forecasting system was presented by Shou-Feng et al. [8], in which agents were used to select the best traffic forecast model suited to the current traffic state, evaluating the performance of the models and to update the parameters automatically. It should be noted that none of the above initiatives used to some extent the agent paradigm as modelling abstraction, nor considered a formal modeling of the software architecture obtained (for example, through the use of UML artifacts). These are two important contributions of the current work. Additionally, this work takes the ideas of the FAMS project regarding an integrated agency for transportation and concretizes it by means of a virtual enterprise devoted to passenger transport services offer. This work represents the continuity of a past reseach in this transportation domain [6], concerning the development of an agent system for passenger transportation for a single operator under a demand-responsive scenario.
3 Towards a Virtual Enterprise for Passenger Transportation The Intelligent Transport Systems (ITS) have been attracting interest of the transport professionals, the automotive industry and governments around the world. Regarding the public transport domain, in the last years the Demand Responsive Transport (DRT) services have risen in popularity for several reasons, among them strong incorporation of information and communications technologies, increasing the efficiency and diminishing the operations cost. However, geographical coverage problems among transport operators’ services, difference in the volume and quality of handled information and, in general, a fragmentation in the transport service provision, gives origin to problems that range from wrong evaluations coming from state-regulatory entities, up to direct problems with the system final users, which definitively results in a poor quality of service. For these reasons in many cases the solution implies a better integration and coordination of the diverse parties, leveraging the concept of virtual enterprise. In this sense, we may think in a virtual transportation enterprise, with an increased level of adaptability to the offer, considered the variability in the levels of existing demand. With this, and under new business opportunities, the virtual transportation enterprise adapts its structure to meet the existing demand.
68
D. Cabrera and C. Cubillos
4 Multi-agent Framework Design The first diagram presented corresponds to the Agents Identification Diagram (see Figure 1), which is framed within the first stage of the PASSI methodology, corresponding to the System Requirements Model. It is possible to indicate that the generation of diagrams is given on the basis of the use of a graphical tool available for PASSI, denominated PASSI Toolkit [4]. This diagram takes as starting point the description of UML use-cases, offering a general view of all the functionality provided by the system and in addition, it incorporates a grouping of use-cases for each agent identified within the system in order to visualize the responsability level that each of the agents has regarding the system.
User
VE Custom...
(from 01-Doma...)
(from 01-Doma...)
UserAgent
OperationManagerAgent Trip-RequestAgent
TO Solver (from 01-Doma...)
Service Request Management
(from UserAgent)
User Requests Management
Generate Proposals
(from Trip-RequestAgent)
(from OperationManagerAgent)
User Profile Management
ScheduleAgent
(from UserAgent)
Generate Early Payment Request User Events Management User Events Processing (from UserAgent) (from UserAgent)
Trip Schedule Operative Fleet Visualising
(from ScheduleAgent)
(from OperationManagerAgent)
(from T rip-RequestAgent)
Vehicle Itinerary Management (from ScheduleAgent)
VirtualEnterpriseAgent
Traffic Informat...
TrafficISAgent
(from 01-Doma...)
VE Transact...
(from 01-Doma...)
Traffic Information Processing
Virtual Enterprise Management
(from T rafficISAgent)
(from VirtualEnterpriseAgent)
VE Administrator
GovernmentAgent
Driver (from 01-Doma...)
(from 01-Doma...)
PlannerAgent
VE - Affiliates Enterpri...
Virtual Enterprise Affiliation Management
Transport Operator
(from VirtualEnterpriseAgent)
Governmental Entity Events Management
(from 01-Doma...)
(from 01-Doma...)
(from GovernmentAgent)
TransportOperatorAgent Events Management
(from PlannerAgent)
Fleet Events Management
(from TransportOperatorAgent)
(from T ransportOperatorAgent)
Government Entity (from 01-Doma...)
Actual Fleet Management
Events Processing (from PlannerAgent)
ActiveDestinationAgent TO - Fleet Managem... (from 01-Doma...) Active Destination
Active Destination Events Management (from ActiveDestinationAgent)
(from 01-Doma...)
Fig. 1. Agent Identification Diagram
Multi-agent Framework for a Virtual Enterprise of Demand-Responsive Transportation
69
The figure 2 shows the Domain Ontology Description, which corresponds to a class diagram that contains specific domain concepts and its relations. The common knowledge of the domain is described through this diagram. In this sense, the ontology allows the definition of a common vocabulary, necessary for trips programming, transport operators management within the virtual enterprise, as well as the events that can arise and may affect the itineraries planned previously.
GenerateGovernmentEntityEvent Actor: GovernmentAgent generateEvent()
registerVehiclesFleet()
ActiveDestinationEvent
generateEvent()
ManagePermanence Actor: VirtualEnterpriseAgent
1..n
0..n
controls
ActiveDestination
GenerateUserEvent Actor : UserAgent
RegisterFleet Actor: TransportOperatorAgent
0..n
GovernmentEntity
GenerateActiveDestinationEvent Actor : ActiveDestinationAgent
GovernmentEntityEvent
manages
manages
affiliateOperator() checkStatus() removeOperator()
VehiclesFleet 1..n 1 has
1..n generateEvent()
1..n
advising
ExternalEventUser
TransportOperator communicates VirtualEnterprise incorporates 1 1..n OperatorID 1 0..n
administers
WithAirConditioning value : Boolean
User UserID
1
WithBicycleRack value : Boolean
has
+bicycleRack
+air
Vehicle VehicleID Type Capacity
UserEvent TransportRequest RequestID emits EmissionDate 1 1 ServiceDate 1..n UserID Cancellation Delay OriginPlace DestinationPlace OriginHour has DestinationHour ProfileDetails : UserProfile 1..n
1
+light +wc
WithWC value : Boolean
UserProfile ProfileID VehicleType MaxTimeDelay
+wheelchairRack
WithWheelchairRack value : Boolean
createProfile() manageProfile() +dvdPlayer
WithDVDPlayer value : Boolean
GenerateProposal Actor: ScheduleAgent
+share
ShareVehicle value : Boolean
+light HasReadingLight value : Boolean +wc
HasWC value : Boolean +bicycleRack
HasBicycleRack value : Boolean +wheelchairRack
1 Itinerary
CreateUserProfile Actor : UserAgent
+air
1..n
includes
WithReadingLight value : Boolean
0..n
HasAirConditioning value : boolean
1..n
manages
1..n
1
1
1
0..n receives
registerUser()
has
RegisterUser Actor: UserAgent
1
1
1
1..n
scheduleTrip()
HasWheelchairRack value : Boolean +dvdPlayer
HasDVDPlayer value : Boolean
Fig. 2. Domain Ontology Description
According to the defined ontology, the virtual enterprise incorporates one or many transport operators, which on their turn can as well have multiple fleets of vehicles, each one composed with at least one. Each vehicle has associated a trip itinerary, which includes at least one transport request emitted by a transport (end) user. Each transport request defines, among other things, the date of emission and service fulfilment for the required trip, origin and destination points involved, departure and arrival hour to destination and a user identifier. Each transport user has associated a user profile, which contains his service preferences (type of vehicle, need of
70
D. Cabrera and C. Cubillos
wheelchair rack, etc.). Also, transport users, governmental entities and active destinations they are all qualified to indicate events that are external to the virtual transportation enterprise and that may alter in some way or another the normal flow of activities. Finally, a deployment/component hybrid diagram of the general framework architecture is included (see Figure 3). On it, a set of "compute nodes" are identified, each one distinguishable by its representation as a package. Inside each package a set of software components are identified, those of which can correspond to agents (as is the case of the package with the stereotype) or to independent systems (as in the "Virtual Enterprise Information System" package) or to a mixture of both, agents with applications and management systems, as it happens in the case of the remaining packages. Some components have been identified as hot-spots or points of variability within the framework architecture. One example is the type of technique or technology used for the trips scheduling within the passenger transportation system. This technique or technology may correspond to a heuristic algorithm (genetic algorithms, to name a possible technique), or Branch & Bound solvers as CPLEX [10], LINDO [11], etc.
User GUI
UserAgent
Traffic Information System
Trip-requestAgent
VE - Affiliates Enterprises Management System
VE - Transaction System
PlannerA gent
EV Administrator GUI
GovernmentAgen t
OperationManagerA gent
Transport Operator GUI
Schedule Agent
VE - Customers Manager System
VirtualEnterp riseAgent
TransportOperatorA gent
TO Solver
ActiveDestinationAgent
Government Entity GUI
Active Destination GUI
TO - Fleet Management System
Fig. 3. Deployment/Component hybrid diagram of the framework
5 Conclusion A multi-agent framework for a virtual enterprise devoted to passengers’ transportation has been achieved. The domain context and their involved actors have been defined, which can correspond to information systems or people. Also, the domain ontology allows understanding the most fundamental concepts of the software framework, knowledge base for the obtaining of a flexible architecture. Such architecture includes a set of identified agents which conform a society of agents and that interact with both, the final user of the transport system, and information systems and applications external to it.
Multi-agent Framework for a Virtual Enterprise of Demand-Responsive Transportation
71
Currently, a functional prototype is being developed by extending the multi-agent framework proposed, and is being tested with Solomon’s benchmark data sets for VRP and specially adapted for the passenger transportation problem.
Acknowledgements This work has been partially funded by the Pontifical Catholic University of Valparaíso (www.pucv.cl) through project No. 209.746/2007 entitled ”Coordinación en una sociedad multiagente dedicada a la programación y control bajo ambiente dinámico”.
References 1. Burrafato, P., Cossentino, M.: Designing a multiagent solution for a bookstore with the passi methodology. In: Fourth International Bi-Conference Workshop on AgentOriented Information Systems (AOIS 2002) (2002) 2. Roozemond, D.: Using Intelligmt Agents for Pro-active Real-time Urban Intersection Control. European Journal of Operational Research 131(2), 293–301 (2001) 3. SIPTS - TEN45607 - Services for Intelligent Public Transport Systems, http://www.novacall.fi/sipts/e_default.htm 4. PASSI Toolkit (PTK), http://sourceforge.net/projects/ptk 5. FAMS - Flexible Agency for Collective Demand Responsive Services. IST-2001-34347, http://www.famsweb.com/ 6. Cubillos, C., Guidi-Polanco, F., Demartini, C.: MADARP: Multi-Agent Architecture for Passenger Transportation Systems. In: Proceedings of the 8th IEEE International Conference on Intelligent Transportation Systems (ITSC 2005), Vienna, Austria (September 2005) 7. Fontoura, M., Pree, W., Rumpe, B.: The UML Profile Framework Architectures. Addison Wesley, Reading (2000) 8. Ma, S.-F., He, G.-G., Wang, S.-T.: A traffic flow forecast supported system based multiagent. In: IEEE Intelligent Transportation Systems Conference Proceedings, pp. 620–624 (2001) 9. SAMPLUS TR 4023 - Systems for the Advanced Management of Public Transport Operations http://www.cordis.lu/telematics/tap_transport/research/projects/samplus.html 10. Ilog Cplex, http://www.ilog.com/products/cplex 11. Lindo Systems, http://www.lindo.com
