Flavien Balbo

Dynamic modeling of a disturbance in a multi-agent system for traffic regulation

This paper presents the modeling of a disturbance on a public transportation line. The proposed model allows the synthesis, evaluation and update of available information in order to help human regulators in their monitoring task. It begins with a formal modeling of the disturbance concept. This modeling makes it possible to capitalize the knowledge available within a monitoring station and to follow up the evolution of the disturbances in real time. The paper goes on to propose a multi-agent representation of an incident allowing the integration of the disturbance processing within the activity of a network system.

Toward a Multi-agent Modelling Approach for Urban Public Transportation Systems

In this paper, a multi-agent system (MAS) for bus transportation management is presented. The aim of our MAS is 1) to diagnose problems in the bus lines (bus delays, bus advances,...) and 2) to detect inconsistency in positioning data sent by buses to the central operator. Our MAS behaves as a Multi-Agent Decision Support System (MADSS) used by human regulators in order to manage bus lines. In our model, buses and stops are modeled as autonomous agents that cooperate to detect faults (disturbances) in the transportation network. An original interaction model called ESAC (Environment as Active Communication Support) was designed to allow nonintentional as well as direct communication. The system was implemented using ILOG RULES and was tested on data coming from the Brussels bus transportation network (STIB).

Regulated multi-party communications and context awareness through the environment

Recent research in the multi-agent systems field has highlighted the relevance of complex interaction models such as multi-party communication and context awareness. Nevertheless, there are no generic interaction model and infrastructure that enable to apply them in a standardized way. Emerging as a first-order abstraction, the environment, in the sense of a common medium for the agents, is a suitable paradigm to support these new interaction models. We present an operational model called Environment as Active Support of Interaction, that enables each agent to actively modify the environment according to its interaction needs. This model provides a suitable framework for the regulation of MAS interactions, and priority policies are given to manage the rules. An algorithm is proposed and assessed with an example stemming from the ambient intelligence domain.

Environment as active support of interaction

Indirect interactions have been shown to be of interest in MultiAgent Systems (MAS), in the simulation area as well as in real applications. The environment is also emerging as a first-order abstraction. Intuitively, the environment being a common medium for the agents, it should be a suitable paradigm to provide an infrastructure for both direct and indirect interactions. However, it still lacks of a consensus on how the two relate to each other, and how the environment can support effectively notions as communication or awareness. We propose a general and operational model, Environment as Active Support of Interaction, that enables the agents to actively participate in the definition of their perceptions. Then, we show how the model provides a suitable framework for the regulation of the MAS interactions.

A Formal Model of Communication and Context Awareness in Multiagent Systems

Awareness is a concept that has been frequently studied in the context of Computer Supported Cooperative Work. However, other fields of computer science can benefit from this concept. Recent research in the multi-agent systems field has highlighted the relevance of complex interaction models such as multi-party communication and context awareness for simulation and adaptive systems. In this article, we present a generic interaction model that enables to use these different models in a standardized way. Emerging as a first-order abstraction, the environment, in the sense of a common medium for the agents, is a suitable paradigm to support the agents’ awareness. We present an operational model, called Environment as Active Support of Interaction, to take into account all the agents that can be interested in a communication. This model is then extended for the regulation of multiagent systems interactions. Priority policies are given to manage the rules governing the context (un-)awareness of the agents. We also present a new AUML connector to create protocols that take into account the agent awareness to implement proactive behaviour, and several communication scenarios are proposed to show practical applications of this model.

Management of urban parking: an agent-based approach

In the context of road urban traffic management, the problem of parking spots search is a major issue because of its serious economic and ecological fallout. In this paper, we propose a multi-agent system that aims to decrease, for private vehicles drivers, the parking spots search time. In the system that we propose, a community of drivers shares information about spots availability. Our solution has been tested following different configurations. The first results show a decrease in parking spots search time.

A multi-agent system to regulate urban traffic: Private vehicles and public transport

This paper proposes a strategy of urban bimodal traffic regulation based on multi-agent modelization. The objective of this strategy is to work on the duration of the traffic lights to regulate traffic for transport modes that include private and public transport vehicles, principally the bus. The model respects the method of bus regulation with a route agent, who supervises all the vehicles on the route while ensuring that they respect the regular time intervals between them. Bus priority is granted by reserving a green stage for buses as soon as they enter the route in question. This stage is prioritised for those buses running late, and whose priority does not lead to deterioration in the regularity of the time intervals between them and the preceding vehicle; an interval they must respect at bus stops. Regulation is obtained thanks to communication, collaboration and negotiation between the agents; the programming is developed under the JADE (Java Agent Development Framework) platform.

Agent information server: a middleware for traveler information

This paper proposes an Agent Traveler Information Server (ATIS) for a daily trip in an urban area. It is based on the multi-agent paradigm and is using the Environment as Active Support of Interaction (EASI) model. It instantiates the mutual awareness concept. The purpose is to allow services, information sources and human travelers to be represented by a unified agent structure and to allow them to interact homogeneously although they are conceptually different. Given that the whole information process must be envisaged in a real time configuration, the increase of the interactions has to be taken into account and the classical interaction modes become rapidly inefficient. The EASI model enables agents to build their interaction interests egocentrically and delegates the interaction management to the multi-agent environment.

Contextual activation for Agent-Based Simulation

When designing agent-based simulation, thechoice of a coordination model is a key issue, since oneof the difficulties is to link the activation of the agentswith their context efficiently. Current solutions separatethe activation phase from the action phase of theagents, and each action phase is based on local agentcontext analysis which is time-expensive. Moreover, becausethe link between the context and the action is aninternal part of the agent, it is more difficult to modifythe way the agent reacts to the context without alteringthe way the agent is implemented. Our proposal, calledEASS (Environment as Active Support for Simulation),is a new approach for agent activation, where the contextis analysed inside the environment and conditionsthe activation of the agents. The main result of contextualactivation is to simplify the achievement of complexsimulations and to decrease run-time. The EASS modelhas been implemented within the kernel of MadKit, amulti-agent platform, and the first results are given.

An agent-based computational approach for urban traffic regulation

This paper proposes a bimodal urban traffic control strategy based on a multi-agent model. We call bimodal traffic, a traffic which takes into account both private vehicles and public vehicles such as buses. The objective of this research is to improve global traffic, to reduce bus delays and to improve bus regularity in congested areas of the network. In our agent-based approach, traffic regulation is obtained thanks to communication, collaboration and negotiation between heterogeneous agents. An important feature of our system is that it allows regulation at two levels: macroscopic and microscopic levels. To model in depth regulation procedures, we have introduced special features such as priority levels for buses, computation and update of traffic signal plans, urgency index of intersection stages depending on the level of congestion on the arcs. We have tested our strategy on a small network of six intersections, using the JADE platform. The simulation is described and preliminary results are presented. They show that our MAS strategy improves bus travel time while improving also private vehicles’ travel time, decreases bus delays and improves its regularity compared to a classical strategy called fixed-time control strategy.