Maxime Guériau

Maxime Guériau
Institut National des Sciences Appliquées de Rouen | INSA Rouen

PhD in Computer Science

About

40
Publications
11,254
Reads
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457
Citations
Citations since 2016
35 Research Items
454 Citations
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2016201720182019202020212022020406080100120
2016201720182019202020212022020406080100120
Introduction
Maxime Guériau is now Assistant Professor at INSA Rouen Normandie. He was a Research Fellow at the School of Computer Science and Statistics, Trinity College Dublin. He obtained a Ph.D. from Lyon 1 University and an engineering degree from the University of Technology of Belfort-Montbéliard (UTBM). His research interests are distributed intelligent complex systems, machine learning, vehicular simulation, and traffic modeling for Cooperative Intelligent Transportation Systems applications.
Additional affiliations
January 2018 - October 2020
Trinity College Dublin
Position
  • Research Associate
November 2016 - November 2017
Université Gustave Eiffel
Position
  • Engineer
November 2016 - October 2017
Polytech Lyon
Position
  • Lecturer
Education
September 2013 - October 2016
Claude Bernard University Lyon 1
Field of study
  • Computer Science

Publications

Publications (40)
Article
Full-text available
Advances in Information and Communication Technologies (ICT) allow the transportation community to foresee dramatic improvements for the incoming years in terms of a more efficient, environmental friendly and safe traffic management. In that context, new ITS paradigms like Cooperative Systems (C-ITS) enable an efficient traffic state estimation and...
Conference Paper
Advances in Information and Communication Technologies (ICT) allow the transportation community to foresee relevant improvements for the incoming years in terms of a more efficient, environmental friendly and safe traffic management and operations. In that context, new ITS paradigms like Cooperative Systems (C-ITS) enable an efficient traffic state...
Article
Full-text available
Cooperative Intelligent Transportation Systems (C-ITS) are complex systems well-suited to a multi-agent modeling. We propose a multi-agent based modeling of a C-ITS, that couples 3 dynamics (physical, informational and control dynamics) in order to ensure a smooth cooperation between non cooperative and cooperative vehicles, that communicate with e...
Conference Paper
Full-text available
Testing autonomous driving algorithms on mobile systems in simulation is an essential step to validate the models and train the system for a large set of (possibly unpredictable and critical) situations. Yet, the transfer of the model from simulation to reality is challenging due to the reality gap (i.e., discrepancies between reality and simulatio...
Conference Paper
Full-text available
L'entraînement des robots mobiles à la navigation auto-nome requiert la simulation de multiples scénarios variés auxquels le robot n'est pas habitué. Par conséquent, le transfert d'algorithmes de la simulation vers la réalité peut s'avérer risqué dû à l'écart entre la réalité et la simulation. Dans cet article, nous développons une première version...
Article
Full-text available
Shared Mobility Systems (SMS) facilitate on-demand journeys using one or more transportation modes such as car-sharing, bike-sharing, or ride-sharing. As a result, SMS often face challenges such as finding suitable facility locations, efficient routing of shared vehicles, matching and re-distributing available resources with dynamic demands. Most e...
Preprint
Full-text available
Recent research has shown the potential of using available mobile fog devices (such as smartphones, drones, domestic and industrial robots) as relays to minimize communication outages between sensors and destination devices, where localized Internet-of-Things services (e.g., manufacturing process control, health and security monitoring) are deliver...
Article
Creating sustainable urban futures partly requires reducing car-use and transport induced stresses on the environment and society. New transport technologies such as autonomous vehicles are increasingly assuming prominence in debates about the transition toward sustainable urban futures. Yet, enormous uncertainties currently exist on how autonomous...
Article
Full-text available
Enabling Ride-sharing (RS) in Mobility-on-demand (MoD) systems allows reduction in vehicle fleet size while preserving the level of service. This, however, requires an efficient vehicle to request assignment, and a vehicle rebalancing strategy, which counteracts the uneven geographical spread of demand and relocates unoccupied vehicles to the areas...
Conference Paper
Full-text available
Variable Speed Limit (VSL) is a traffic control approach that optimises the mainstream traffic on motorways. Reinforcement Learning approach to VSL has been shown to achieve improvements in controlling the mainstream traffic bottleneck on motorways. However, single-agent VSL, applied to a shorter motorway segment, can produce a discontinuity in tra...
Conference Paper
Full-text available
Connected and Autonomous Vehicles (CAVs) are expected to bring major transformations to transport efficiency and safety. Studies show a range of possible impacts, from worse efficiency of CAVs at low penetration rates, to significant improvements in both efficiency and safety at high penetration rates and loads. However, these studies tend to explo...
Conference Paper
Full-text available
Mobility-on-Demand (MoD) systems offer a flexible mobility alternative to classical public transportation services in urban areas. However, a significant part of MoD vehicles operating time can be spent waiting empty or driving to reach new potential ride requests. Improving vehicle fleet operation is an extremely challenging problem, as the number...
Preprint
Variable Speed Limit (VSL) is a traffic control approach that optimises the mainstream traffic on motorways. Reinforcement Learning approach to VSL has been shown to achieve improvements in controlling the mainstream traffic bottleneck on motorways. However, single-agent VSL, applied to a shorter motorway segment, can produce a discontinuity in tra...
Conference Paper
Full-text available
Enabling Ride-sharing (RS) in existing Mobility-on-demand (MoD) systems allows to reduce the operating vehicle fleet size while achieving a similar level of service. This however requires an efficient vehicle to multiple requests assignment, which is the focus of most RS-related research, and an adaptive fleet rebalancing strategy, which counteract...
Article
Full-text available
Autonomous cars controlled by an artificial intelligence are increasingly being integrated in the transport portfolio of cities, with strong repercussions for the design and sustainability of the built environment. This paper sheds light on the urban transition to autonomous transport, in a threefold manner. First, we advance a theoretical framewor...
Article
Full-text available
Mobility-on-demand systems consisting of shared autonomous vehicles (SAVs) are expected to improve the efficiency of urban mobility through reduced vehicle ownership and parking demand. However, several issues in their implementation remain open, such as unifying the vehicle and ride-sharing assignment with rebalancing non-occupied vehicles. Furthe...
Chapter
The monitoring and the surveillance of industrial and agricultural sites have become first order tasks mainly for security or the safety reasons. The main issues of this activity is tied to the size of the sites and to their accessibility. Thus, it seems nowadays relevant to tackle with this problem with robots, which can detect potential issues wi...
Conference Paper
Full-text available
With increasing applications of reinforcement learning in real life problems, it is becoming essential that agents are able to update their knowledge continually. Lifelong learning approaches aim to enable agents to retain the knowledge they learn and to selectively transfer knowledge to new tasks. Recent techniques for lifelong reinforcement learn...
Conference Paper
Full-text available
Multi-agent Reinforcement Learning (RL) is frequently used in large-scale autonomous systems to learn the behaviours that best suit the system's operating environment. Learning can take a significant amount of time during which an RL system's performance is necessarily suboptimal. Transfer learning (TL), a method of reusing knowledge which has been...
Conference Paper
Full-text available
Reinforcement Learning (RL) is increasingly used to achieve adaptive behaviours in Internet of Things systems relying on large amounts of sensor data. To address the need for self-adaptation in such environments, techniques for detecting environment changes and re-learning behaviours appropriate to those changes have been proposed. However, with th...
Article
Full-text available
Lorsqu’un système autonome évolue dans un environnement complexe, en partie inconnu ou dynamique, il n’est pas possible de fournir une représentation exhaustive a priori facilitant son processus de prise de décision ; cette représentation étant le résultat de l’interaction du système avec son environnement. Pour illustrer ce problème, nous considér...
Poster
Full-text available
Poster presentation for the on-going research project "Surpass: how shared autonomous cars will transform cities". Presented at the launch of ENABLE- a new research programme in Ireland which aims to connect communities with smart urban environments through the Internet of Things
Conference Paper
Full-text available
Cooperative Intelligent Transportation Systems (C-ITS) are currently being widely deployed on the road network. However, the impact of such systems on traffic flow is still to be addressed, especially for advanced deployment phases (high number of connected and automated vehicles). In this context, the paper investigates the impacts assessment of C...
Article
Development of intelligent behaviors for vehicles has to cope with rigorous specifications. Many tests are performed for verification, validation and a detailed study of resulting behaviors. In this workflow, testing algorithms with real vehicles is a cornerstone step in developing new intelligent features for future transportation systems. This st...
Article
Full-text available
The monitoring and the surveillance of industrial and agricultural sites have become first order tasks mainly for security or the safety reasons. The main issues of this activity is tied to the size of the sites and to their accessibility. Thus, it seems nowadays relevant to tackle with this problem with robots, which can detect potential issues wi...
Thesis
Full-text available
Dans un proche futur, les véhicules connectés et autonomes remplaceront nos véhicules actuels, et il sera nécessaire de repenser intégralement la mobilité. Le conducteur, avec ses lacunes, sera de plus en plus assisté, et un jour détrôné par un système embarqué, capable d'agir plus rapidement, tout en ayant une représentation plus précise et fiable...
Conference Paper
Full-text available
We present a multi-agent based extension of a microscopic time continuous lane-based simulator designed to develop cooperative vehicle behaviors within a connected environment. We have chosen to extend the Multi-model Open-source Vehicular-traffic SIMulator (MovSim) which offers a complete traffic simulation platform. By integrating concepts coming...

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Projects

Projects (3)
Archived project
CAVIMAS focuses on the introduction of highly Automated Vehicles on the Irish road network. It evaluates the transition phase where CAVs will be gradually introduced on the network and will have to interact with human-driven traffic flow. This corresponds to a 5 to 20 years’ time frame were the level of automation is expected to reach levels 2 to 5. Under a set of selected case studies, chosen to represent a wide range of situation CAVs will need to overcome, CAVIMAS combines a simulation-based approach and a comprehensive literature review to lead an up-to-date impact study of CAVs deployment in Ireland.
Project
The goal of the project is to examine and quantify the impacts that shared autonomous vehicles will have on urban living and urban spatial structure, and their sustainability implications. Follow links for more information: http://research.ie/what-we-do/loveirishresearch/blog/autonomous-cars-are-driving-fast-towards-us/ Future Cities: The Trinity Centre for Smart and Sustainable Cities, Trinity College Dublin, Ireland. https://www.tcd.ie/futurecities/
Project
SCOOP@F is a the french C-ITS deployment project that involve both academic and industrial partners. The main objective is to deploy an interoperable information system based on a vehicle-to-vehicle (V2V) and vehicle-infrastructure (V2I/I2V) dedicated wireless communication protocol. Up to 2000 vehicles will be equipped with an on-board unit coupled with the vehicle navigation system to alert the driver about events occuring on his trip. In this project, we are in charge of the impact study of this C-ITS on traffic flow. The evaluation rely on a dedicated experiment that will involve 20 (connected and non-connected) vehicles on a road section where events (road works, ...) will occur. Objectives : - to model the effects of connected vehicles on driver behavior (anticipation) - to assess the impact of connected vehicles on trafic flow - to anticipate future deployments through simulation