Multi-Agent Environment for Modelling and Solving Dynamic Transport Problems

The transport requirements in modern society are becoming more and more important. Thus, offered transport services need to be more and more advanced and better designed to meet users demands. Important cost factors of many goods are transport costs. Therefore, a reduction of costs, a better adjustment of strategies to the demand as well as a better planning and scheduling of available resources are important for the transport companies. This paper is aimed at modelling and simulation of transport systems, involving a dynamic Pickup and Delivery problem with Time Windows and capacity constraints (PDPTW). PDPTW is defined by a set of transport requests which should be performed while minimising costs expressed by the number of vehicles, total distance and total travel time. Each request is described by two locations: pickup and delivery, periods of time when the operations of pickup or delivery can be performed and a load to be transported. The nature of this problem, its distribution and the possibility of using a lot of autonomous planning modules, lead us to use a multi-agent approach. Our approach allows the modeling of entities which do not appear in the classical PDPTW such as company organisation, communication among vehicles, interactions between vehicles and company dispatcher or different strategies of requests acceptation by different vehicles. This paper presents also a software environment and experimentations to validate the proposed approach

An integrated model for interactive systems

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Simulation and Evaluation of Urban Bus Networks using a Multiagent Approach

International audienceEvolution of public road transportation systems requires analysis and planning tools to improve service quality. A wide range of road transportation simulation tools exist with a variety of applications in planning, training and demonstration. However, few simulation models take into account traveler behaviors and vehicle operation specific to public transportation. We present in this paper a bus network simulation tools which include these specificities and allows to analyze and evaluate a bus network at diverse space and time scales. We adopt a multiagent approach to describe the global system operation as behaviors of numerous autonomous entities such as buses and travelers

An Agent-Based Approach for Single and Multi-Level Location Problems

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Location Problems Optimization by a Self-Organizing Multiagent Approach

International audienceThe Facility Location Problem (FLP) requires locating facilities in order to optimize some performance criteria. This problem occurs in many practical settings where facilities provide a service, such as the location of plants, bus-stops, fire stations, etc. Particularly, we deal with the continuous version of location problem where facilities have to be located in an Euclidean plane. This paper contributes to research on location problems by exploring a new approach based on reactive multiagent systems. The proposed model relies on a set of agents situated in a common environment which interact and attempt to reach a global optimization goal. The interactions between agents and their environment, which are based on the artificial potential fields approach, allow to locally optimize the agent's locations. The optimization of the whole system is the outcome of a process of agents self-organization. Then, we present how the model can be extended to the multi-level version of the location problem. Finally, the approach is evaluated to check its relevance. These evaluations concern both presented versions of the location problem

A voting strategy for high speed stereo matching - Application for real-time obstacle detection using linear stereo vision

International audienceIn this paper we propose a new stereo matching algorithm for real-time obstacle detection in front of a moving vehicle. The stereo matching problem is viewed as a constraint satisfaction problem where the objective is to highlight a solution for which the matches are as compatible as possible with respect to specific constraints. These constraints are of two types: local constraints, namely position, slope and gradient magnitude constraints, and global ones, namely uniqueness, ordering and smoothness constraints. The position and slope constraints are first used to discard impossible matches. Based on the global constraints, a voting stereo matching procedure is then achieved to calculate the scores of the possible matches. These scores are then weighted by means of the gradient magnitude constraint. The correct matches are finally obtained by selecting the pairs for which the weighted scores are maximum. The performance of the voting stereo matching algorithm is evaluated for real-time obstacle detection using linear cameras

Decentralized microgrid coordination using multi-agent systems

International audienceMicrogrid (MG) networks are expected to help increase grid flexibility and the integration of renewable generation. To improve network cooperation performance, this paper proposes a novel distributed control strategy to manage energy flows using a multi-agent system. Power dispatching is achieved through flexible electricity markets to maximize MG profit. A distributed power flow calculation algorithm is proposed to guarantee that the power flow in the network is within line capacity. Simulation shows that the control strategy manages to ensure MG power balance while maximizing profit. Additionally, the power flow is within line capacity to guarantee system security

Multilevel Model of the 3D Virtual Environment for Crowd Simulation in Buildings

AbstractMultiagent-based simulations enable us to validate different use-case scenarios in a lot of application domains. The idea is to develop a realistic virtual environment to test particular domain-specific procedures. This paper presents a multilevel model of a physic environment for the simulation of crowd in a virtual 3D building. The major contributions of this paper is the agentification of the model to support multilevel simulation of the environment. Finally, the application of the model inside an airport terminal is presented