Integration of Traffic Management and Traveller Information Systems: Basic Principles and Case Study in Intermodal Transport System Management

As they involve many interacting agents behaving in numerous ways that are extremely difficult to predict, urban transportation systems are complex in nature. The development of intermodal passenger transportation solutions to address the mobility issues constitutes a major thrust area of urban transport policies. But, to offer citizens comprehensive seamless mobility, intermodal transportation system management (ITSM) requires the integration of two major components. The traffic regulation support system, to help the operator responsible for the regulation tasks: coordination of timetables, synchronising arrival and departure times between the different transportation modes, and the traveller information system, giving customers access to information and using a comprehensive set of information tools. In this paper, a generic model of a transport management system, integrating these two components is proposed. This generic model is then used to elaborate a traffic regulation system in the case of a bimodal transportation system (tram-bus). The traffic regulation support system, based on the decision model of an operator, and the traveler information system are described.

[1]  Jens Rasmussen,et al.  Information Processing and Human-Machine Interaction , 1986 .

[2]  Christophe Kolski,et al.  Agent Oriented Specification of Interactive Systems: Basic Principles and Industrial Case Study , 2002, CADUI.

[3]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1988, IJCAI 1989.

[4]  B. Schneirdeman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction , 1998 .

[5]  René Mandiau,et al.  Traffic control assistance in connection nodes: multi-agent applications in urban transport systems , 2001, Proceedings of the International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. IDAACS'2001 (Cat. No.01EX510).

[6]  Christophe Kolski,et al.  Modelling of an interactive system with an agent-based architecture using Petri nets, application of the method to the supervision of a transport system , 2006, Math. Comput. Simul..

[7]  Florin Gheorghe Filip,et al.  Decision support and control for large-scale complex systems , 2008, Annu. Rev. Control..

[8]  Mark A Miller,et al.  Assessing Opportunities for Intelligent Transportation Systems in California's Passenger Intermodal Operations and Services , 2001 .

[9]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[10]  Jens Rasmussen,et al.  Information Processing and Human-Machine Interaction: An Approach to Cognitive Engineering , 1986 .

[11]  P. Millot,et al.  TWO APPROACHES FOR MAN–COMPUTER COOPERATION IN SUPERVISORY TASKS , 1990 .

[12]  H. Ezzedine,et al.  Intermodal transportation system management : towards integration of traffic management system and users information system. , 2006, The Proceedings of the Multiconference on "Computational Engineering in Systems Applications".

[13]  Ben Shneiderman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction (4th Edition) , 2004 .

[14]  Christophe Kolski,et al.  Agent-oriented design of human-computer interface: application to supervision of an urban transport network , 2005, Eng. Appl. Artif. Intell..

[15]  Abdelwaheb Trabelsi Contribution à l'évaluation des systèmes interactifs orientés agents , 2006 .

[16]  S. Hammadi,et al.  Régulation Spatio-Temporelle d’un Réseau de Transport Multimodal , 2005 .

[17]  Nathalie Cassaigne,et al.  Predictive and reactive approaches to the train-scheduling problem: a knowledge management perspective , 2001, IEEE Trans. Syst. Man Cybern. Part C.

[18]  Flavien Balbo,et al.  Dynamic modeling of a disturbance in a multi-agent system for traffic regulation , 2005, Decis. Support Syst..

[19]  P. Fitts,et al.  INFORMATION CAPACITY OF DISCRETE MOTOR RESPONSES. , 1964, Journal of experimental psychology.