Abstract

International audience; City systems, consisting of the various social and technical infrastructures required for urban areas to function, are facing major challenges in the coming decades as global urbanization and the pressure on resource efficiency and sustainability continue. Agent-based simulation and modelling techniques enable us to study these systems from various levels of abstraction looking at actors as well as system level perspectives, and are particularly suited to understand the dynamics of underlying structures and experiment with various scenarios and the effect of local decisions on emerging system properties. This special issue aims to showcase innovative use of agent-based modelling (ABM) and multi-agent system (MAS) approaches for effective decision support regarding urban innovations in fields linked with urban development and to explore and identify how researchers in different disciplines integrate their knowledge through agent models. We are inviting researchers from across a wide range of disciplines (including computer science, physics, engineering, economics, sociology and others) to submit papers to this special issue that exhibit state-of the art innovation in ABM/MAS applied to cities. This innovation may come in the form of computational, conceptual, analytical, participatory or epistemological advances for a range of aims and motivations associated with the challenge of combining competitiveness and sustainable urban development in city systems. Possible topics include, but are not limited to, the following:[...]

Abstract

International audience; Process flexibility has been investigated in depth in the context of intra-organisational processes, but it is still an open issue when processes cross the boundaries of companies. In this paper, we address the modelling of flexible inter-organisational processes using a version-based approach. Indeed, versions are known to be a powerful technique to deal with variability, evolution and adaptation of processes, which are the three main needs of process flexibility. More precisely, this paper presents VP2M (Version of Process Meta-Model), a meta-model supporting the modelling of versions of inter-organisational processes, addressing both static and dynamic aspects of VP2M. It also illustrates process version modelling within the Subsea Pipeline process example.

Abstract

International audience; Autonomous vehicles promise an important opportunity for a complete paradigm shift for the design of transportation systems. These systems will become more flexible and efficient by adapting to the travelers' demand. On the other hand, multi agent systems offer an intuitive and powerful way to design complex distributed systems and agent based simulation has proved to be well suited for studying the performance of mobility services and their impact on the users and the traffic in general. In this study, we use an Agent-Based modeling approach to design a mobility system based on a fleet of autonomous vehicles (robo-taxis and shuttles) and connected road side units, each of these elements represented by intelligent collaborative agents. In our model, the control is distributed among the agents and the global behaviour of the system emerges from local decisions. We then used a microsimulation tool to test the model on the real road network of the Paris-Saclay area. Since this area is planned to become a center for technology, innovation and education and is currently under constant development, it offers an opportunity for the design and the implementation of new models of transportation services. We designed our mobility system in an incremental manner by introducing more components and more intelligent behaviour and testing its performance at each step. Our results suggest that for our area of study, a mobility service that relies on autonomous vehicles aided by connected road side units that allow to retrieve information about the traffic would perform better than a regular service.

Abstract

International audience; Traffic congestion in large cities became a huge problem, which can lead to a lot of losses especially at the human and material levels. This paper proposes a decentralized model based on multi-agent systems (MAS) and complex event processing (CEP). The new control scheme aims to improve green light time in order to reduce the average waiting time of vehicles in front of the traffic light, especially if the road is empty, and to reduce congestion at crossroad. This improvement is provided by the observation of the intersection through Cyber Physical Systems (CPS). This paper propose an auto-adaptive model for smart regulation traffic lights. The developed model will be evaluated and analyzed using different metrics and scenarios so as to test their influence on system performance.

Abstract

International audience; Cardio-pulmonary arrest is a common emergency situation causing over 400,000 deaths per year, more than a 1000 per day, in the USA alone. The goal of this work is to develop an agent based computer simulator that will allow trainers to experiment with different communication protocols, such as those found in air traffic control. This paper describes the first step in designing the simulator development. The design is based on an analysis of communications during real life training simulations using the FIPA standard categories.

Abstract

Inland navigation transport takes part in the Trans-European network program (TEN-T ), which aims at promoting this mode of transport by creating favorable conditions for the further development of this sector. The NAIADES Action Program comprises numerous actions and measures to boost transport on inland waterways. Among these actions, the infrastructure issue is dealt with. It requires the inventory of the existing infrastructure and the study of the possible effects of the expected climate change. This was one of the objectives of the GEPET-Eau project (2013-2016), which led to the proposal of multi-scale modeling approaches and adaptive and predictive control architectures. The resilience of inland waterways against the increase of navigation demand and the expected extreme drought and flood events was studied by considering deterministic models. The proposed architecture is suitable to consider two scales of space and time to optimize the water resource allocation among the inland networks and to guarantee the navigation conditions by proposing advanced control and fault detection tools. These approaches, which were designed by considering inland waterways in the north of France, are still being improved. Indeed, it is firstly necessary to consider all the uncertainties that are inherent to large-scale and environmental systems. Secondly, the advanced control and fault detection tools require further development to deal with the very complex dynamics that characterize inland waterways. The main objective of this work is to present the current state of the tools that have been developed in order to study and manage the inland waterways in a climate change context. The global framework that allows describing the link between these two management scales will be detailed. The water resource allocation approach can be based on three different techniques: the Constraint Satisfaction Problem (CSP), the quadratic optimization and the Markov Decision Process (MDP). The MDP-based approach will be emphasized due to its suitability to study complex systems with uncertainties, and its main advantages and drawbacks will be discussed and compared to the other techniques. Advanced control and fault detection tools require an in-depth knowledge of the inland waterway dynamics. Characteristics of navigation reaches, i.e. slope, resonance phenomenon, uncontrolled inputs and interconnections, need to be taken into account. A big effort has been made to improve the modeling step of the navigation reaches by considering the IDZ (Integrator Delay Zero) model. The designed tools are based on this accurate model, and they aim at improving the water level control of each reach of the inland waterways and at performing predictive maintenance strategies by detecting, isolating and forecasting faults on sensors and actuators (limnimeters, gates, locks, etc.). The designed management tools will be presented by considering a part of the real inland navigation network in the north of France. Perspectives and future developments will be described. Peer Reviewed Document type: Article

Abstract

Traffic congestion has a significant impact on quality of life and the economy. This paper presents a decentralised traffic management mechanism for intersections using a distributed constraint optimisation approach (DCOP). Our solution outperforms the state of the art solution both for stable traffic conditions (about 60% reduced waiting time) and robustness to unpredictable events. 

Abstract

International audience; Shared autonomous vehicles are considered to have a transformative impact on future urban transportation and especially Shared Mobility. In order to assess the transport-related impact of this new mode, various models and simulations are under development. The majority of recently proposed simulations are based on activity-based multi-agent approaches. Thanks to the disaggregated level of data in multi-agent simulation, the traveler decision making mechanisms might be individualized according the attributes. In this paper we try to take in advantage of this granularity in order to explore the impact of user preferences on the modal split of shared autonomous vehicles. To illustrate the proposed methodology the transport system of Paris is simulated by using an activity-based multi-agent tool called MATSim. The traveler preferences toward shared autonomous vehicles use are also summarized based on the literature review. Document type: Conference object

Abstract

International audience; Air traffic generators are widely used in the air traffic control and aeronautics industry for training purposes and to validate new concepts or new systems. But it is difficult for a machine to generate realistic trajectories and behavior for an aircraft which lead to the participation of many humans in the simulation to compensate. Traditional generators require performance data for aircrafts and heavy preparation to generate realistic trajectories. Our approach takes advantage of widespread flight location data to learn from their behavior and improve traffic generation. Combining cooperative multi-agent learning methods [1] and big data we show that it is possible to design and generate a realistic and intelligent traffic more easily and without human intervention.

Abstract

International audience; In the near future, air traffic control (ATC) will have to cope with a radical change in the structure of air transport [1]. Apart from the increase in traffic that will push the system to its limits, the insertion of new aerial vehicles such as drones into the airspace, with different flight performances, will increase its heterogeneity. Current research aims at increasing the level of automation and partial delegation of the control to on-board systems. In this work, we investigate the collision avoidance management problem using a decentralized distributed approach. We propose an autonomous and generic multi-agent system to address this complex problem. We validate our system using state-of-the-art benchmarks. The results underline the adequacy of our local and cooperative approaches to efficiently solve the studied problem.