An ontology-based approach to relax traffic regulation for autonomous vehicle assistance

Traffic regulation must be respected by all vehicles, either human- or computer- driven. However, extreme traffic situations might exhibit practical cases in which a vehicle should safely and reasonably relax traffic regulation, e.g., in order not to be indefinitely blocked and to keep circulating. In this paper, we propose a high-level representation of an automated vehicle, other vehicles and their environment, which can assist drivers in taking such "illegal" but practical relaxation decisions. This high-level representation (an ontology) includes topological knowledge and inference rules, in order to compute the next high-level motion an automated vehicle should take, as assistance to a driver. Results on practical cases are presented

Framework for context analysis and planning of an assistive robot

This paper presents the developments with the SAM robot, established in the ARMEN project. We are interested in cognitive robotics. We have developed two complementary modules. The first one deals with the representation of knowledge, while the second develops the scenario generation. Indeed, the representation of knowledge tells us about the scene, the current state of the robot and the strategy to be adopted by the robot to achieve goals specified by an assisted person. The information extracted from the knowledge representation is the starting point to generate the action plan and the implementation of the scenario by the robot

Densité de trafic émergente pour des véhicules intelligents communiquants guidés par heuristique

International audienceDans cet article, nous étudions la densité et le comportement émergent du trafic, composé de plu-sieurs centaines de véhicules intelligents, en fonction de la communication véhicule-à-véhicule (V2V) (pour qu'un véhicule perçoive le trafic) et d'heuristiques de planification de chemin dynamique (pourqu'un véhicule atteigne sa destination) en environnement urbain. Les modes de communication idéale / réaliste / aucune sont croisés avec les heuristiques boussole / vers-plus-peuplé / vers-moins-peuplé pour mesurer la vitesse moyenne de trajet de chaque véhicule, modélisé par un automate à états finis. Le modèle de communication V2V, basé sur des modèles de propagation de signal et sur MAC (medium access control), est présenté. Nos expériences, des simulations comprenant jusqu'à 400 véhicules en environnement urbain réaliste, montrent que la communication et les heuristiques conduisent à une meilleur vitesse moyenne globale qu'une absence de communication ; et que, à chaque fois qu'il y a un chemin secondaire, fuir le trafic conduit à des performances globales meilleures que suivre le trafic

An Ontology-based Model to Determine the Automation Level of an Automated Vehicle for Co-Driving

International audienceFull autonomy of ground vehicles is a major goal of the ITS (Intelligent Transportation Systems) community. However, reaching such highest autonomy level in all situations (weather, traffic, . . . ) may seem difficult in practice, despite recent results regarding driverless cars (e.g., Google Cars). In addition, an automated vehicle should also self-assess its own perception abilities, and not only perceive its environment. In this paper, we propose an intermediate approach towards full automation, by defining a spectrum of automation layers, from fully manual (the car is driven by a driver) to fully automated (the car is driven by a computer), based on an ontological model for representing knowledge. We also propose a second ontology for situation assessment (what does the automated car perceive?), including the sensors/actuators state, environmental conditions and driver's state. Finally, we also define inference rules to link the situation assessment ontology to the automation level one. Both ontological models have been built and first results are presented.L'autonomie complète de véhicules terrestres est un but majeur de la communauté ITS (Systèmes de Transport Intelligents). Pourtant; atteindre ce niveau d'autonomie le plus élevé dans toutes les situations (temps, trafic, ...) peut sembler difficile en pratique, en dépit de résultats récents concernant les voitures sans conducteur (e.g., les voitures de Google). De plus, un véhicule automatisé devrait aussi évaluer par lui-même ses propres facultés de perception, et pas seulement percevoir son environnement. Dans cet article, nous proposons une approche intermédiaire vers l'automatisation complète, en définissant un spectre de niveaux d'automatisation, depuis manuel complet (la voiture est conduite par un conducteur) jusqu'à l'automatisation complète (la voiture est conduite par un ordinateur), basé sur une ontologie pour représenter la connaissance. Nous proposons aussi une deuxième ontologie pour l"évaluation de la situation (que perçoit le véhicule automatisé ?) qui inclut l'état des capteurs / actuateurs, les conditions environnementales et l'état du conducteur. Enfin, nous définissons aussi des règles d'inférence pour relier l'ontologie sur l'évaluation de la situation à celle sur les niveaux d'automatisation. Les deux ontologies ont été construites et des premiers résultats sont présentés

Emergent Behaviors and Traffic Density among Heuristically-Driven Intelligent Vehicles using V2V Communication

International audienceIn this paper, we study the global traffic density and emergent traffic behavior of several hundreds of intelligent vehicles, as a function of V2V communication (for the ego vehicle to perceive traffic) and path-finding heuristics (for the ego vehicle to reach its destination), in urban environments. Ideal/realistic/no V2V communication modes are crossed with straight-line/towards-most-crowded/towards-least-crowded pathfinding heuristics to measure the average trip speed of each vehicle. The behaviours of intelligent vehicles are modelled by a finite state automaton. The V2V communication model is also built based on signal propagation models in an intersection scenario and a Markov-chain based MAC model. Our experiments in simulation over up to 400 vehicles exhibit attractive insights: 1) communication's impact is positive for the performance of the emergent vehicles' behaviour, however, 2) the path-finding heuristics may not obtain their expected collective behaviour due to the communications errors in realistic road environment

Arbitration for balancing control between the driver and ADAS systems in an automated vehicle: Survey and approach

International audience— Automated functions for real scenarios have been increasing in last years in the automotive industry. Many research contributions have been done in this field. However, other problems have come to the drivers: When should they (the drivers or the new automated systems) be able to take control of the vehicle? This question has not a simple answer; it de-pends on different conditions, such as: the environment, driver condition, vehicle capabilities, fault tolerance, among others. For this reason, in this work we will analyze the acceptability to the ADAS functions available in the market, and its relation with the different control actions. In this paper a survey on arbitration and control solutions in ADAS is presented. It will allow to create the basis for future development of a generic ADAS control (the lateral and longitudinal behavior), based on the integration of the application request, the driver behavior and driving conditions in the framework of the DESERVE project (DEvelopment platform for Safe and Efficient dRiVE 1 , a ARTEMIS project 2012-2105). The main aim of this work is to allow the development of a new generation of ADAS solutions where the control could be effectively shared between the vehicle and the driver. Different solutions of shared control have been analyzed. A first approach is proposed, based on the presented solutions

Intelligent vehicles: integration and issues

International audienceIn the process of building more and more intelligent vehicles, scientists and car makers are progressively integrating new tools that make the vehicle more independent from human action. However, when can a vehicle be considered as intelligent? In this paper, we first point out the necessity of robotics and artificial intelligence (AI) to collaborate. Indeed, AI is mainly used as a tool in robotics for different tasks such as perception and control. Thus, we show the lack of a supervision level in current vehicles. Finally, we provide some implementations from Rits going towards more intelligent perception by adding a supervision level, dealing with the uncertainties, using communications and managing the resources.Afin de construire des 'véhicules intelligents, scientifiques et constructeurs automobiles intègrent progressivement de nouveaux outils libérant les véhicules de l'action humaine. Cependant à quel moment peut-on considérer un 'véhicule comme intelligent ? Dans cet article, nous parlons tout d'abord du fossé entre les domaines de la robotique et de l'intelligence artificielle (IA), l'IA étant le principalement utilisé comme boite à outils bas niveau. Finalement, nous détaillons quelques implémentations de l'équipe Rits pour concevoir une perception intelligente grâce à l'ajout d'un niveau de supervision, la gestion des incertitudes, l'utilisation des communications, ainsi que la gestion des ressources

Coping with the White Knight in Planning

Recent Tweak-based planners replace the White Knight technique of a modal truth criterion by a simple heuristic for choosing the establisher of a term in situation, empirically trading between the rigorous precision of a criterion and the computational complexity. In this paper, I argue that this WK technique does not rely on the opposition between mathematical rigour and efficiency of an implementation, but on the choice of the formal logic a planner implicitly uses. I show that the WK can be efficiently traded for a maximality condition in propositional logic. On the other hand, planners without functional terms are demonstrated not to evolve in a first order logic; in an intermediate 0 + order logic, the notion of justification subsumes usual establishers or WKs one, and allows the definition of the degree of a modal truth criterion. Correction of a plan is preserved when the strength of such a criterion is increased

A Software Architecture for Autonomous Agents

This paper presents a agent's architecture, an implementation and a task planner

Bulletin de l'AFIA No. 100 (editors)

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