Will the Driver Seat Ever Be Empty?

Self-driving technologies have matured and improved to the point that, in the past few years, self-driving cars have been able to safely drive an impressive number of kilometers. It should be noted though that, in all cases, the driver seat was never empty: a human driver was behind the wheel, ready to take over whenever the situation dictated it. This is an interesting paradox since the point of a self-driving car is to remove the most unreliable part of the car, namely the human driver. So, the question naturally arises: will the driver seat ever be empty? Besides legal liability issues, the answer to that question may lie in our ability to improve the self-driving technologies to the point that the human driver can safely be removed from the driving loop altogether. However, things are not that simple. Motion safety, i.e. the ability to avoid collisions, is the critical aspect concerning self-driving cars and autonomous vehicles in general. Before letting self-driving cars transport people around (and move among them) in a truly autonomous way, it is crucial to assess their ability to avoid collision, and to seek to characterize the levels of motion safety that can be achieved and the conditions under which they can be guaranteed. All these issues are explored in this article.Les technologies de conduite automatique ont mûries et se sont améliorées au point que, au cours des dernières années, les voitures automatiques ont été en mesure de conduire en toute sécurité un nombre impressionnant de kilomètres. Il convient cependant de noter que, dans tous les cas, le siège du conducteur n'était jamais vide : un conducteur humain était au volant, prêt à prendre le relais dès que la situation dictée. C'est un paradoxe intéressant car le point d'une voiture automatique est d'enlever la partie la plus sensible de la voiture, à savoir le conducteur humain. Ainsi, la question se pose naturellement: le siège du conducteur sera t'il vide un jour? Outre les questions de responsabilité juridique, la réponse à cette question réside peut-être dans notre capacité à améliorer les technologies de la conduite automatique, au point que le pilote humain peut en toute sécurité être retiré de la boucle de conduite. Toutefois, les choses ne sont pas aussi simple que cela. La sécurité de mouvement, i.e. la capacité à éviter les collisions, est l'aspect critique à l'égard de voitures automatiques et les véhicules autonomes en général. Avant de laisser les voitures automatiques transporter des personnes (et se déplacer parmi eux) d'une manière réellement autonome, il est crucial d'évaluer leur capacité à éviter la collision, et de chercher à caractériser les niveaux de sécurité de mouvement qui peuvent être atteints et les conditions dans lesquelles elles peuvent être garanties. Toutes ces questions sont examinées dans cet article

A Short Paper About Motion Safety

Motion safety for robotic systems operating in the real world is critical (especially when their size and dynamics make them potentially harmful for themselves or their environment). Motion safety is a taken-for-granted and ill-defined notion in the Robotics literature and the primary contribution of this paper is to propose three safety criteria that helps in understanding a number of key aspects related to the motion safety issue. A number of navigation schemes used by robotic systems operating in the real-world are then evaluated with respect to these safety criteria. It is established that, in all cases, they violate one or several of them. Accordingly, motion safety, especially in the presence of moving objects, cannot be guaranteed (in the sense that these robotic systems may end up in a situation where a collision inevitably occurs later in the future). Finally, it is shown that the concept of Inevitable Collision States introduced in [Fraichard, Asama, 2004] does respect the three above-mentioned safety criteria and therefore offers a theoretical answer to the motion safety issue

Will the driver Seat Ever be Empty?

International audienceSelf-driving vehicles are here and they already cause accidents. Now, should road safety be considered in a trial and error perspective or should it be addressed in a formal way? The latter option is at the heart of our research

Human-Robot Motion: Taking Attention into Account

Mobile robot companions are service robots that are mobile and designed to share our living space. For such robots, mobility is essential and their coexistence with humans adds new aspects to the mobility issue: the first one is to obtain appropriate motion and the second one is interaction through motion. We encapsulate these two aspects in the term Human-Robot Motion (HRM) with reference to Human-Robot Interaction. The long-term issue is to design robot companions whose motions, while remaining safe, are deemed appropriate from a human point of view. This is the key to the acceptance of such systems in our daily lives. The purpose of this paper is to explore how the psychological concept of attention can be taken into account in HRM. To that end, we build upon an existing model of attention that computes an attention matrix that describes how the attention of each person is distributed among the different elements, persons and objects, of the environment. Using the attention matrix, we propose the novel concept of attention field that can be viewed as an attention predictor. Using different case studies, we show how the attention matrix and the attention field can be used in HRM.Les robots compagnons mobiles sont des robots de service conçus pour partager et se déplacer dans notre espace de vie. Pour de tels robots, la mobilité est essentielle et leur coexistence avec des humains ajoute de nouveaux aspects à ce sujet de recherche: le premier est d'obtenir un mouvement approprié et le second est l'interaction au travers du mouvement. On regroupe ces deux aspects sous le terme Human-Robot Motion (HRM) en référence à Human-Robot Interaction. L'objectif à long terme est la conception de robots compagnons dont le mouvement, tout en restant sans danger, est jugé approprié d'un point de vue humain. Ceci est la clé de l'acceptation de tels systèmes dans notre vie quotidienne. L'objectif de ce papier est d'explorer comment le concept psychologique d'attention peut être prix en compte dans HRM. A cette fin, nous proposons un concept nouveau de champ attentionnel qui peut être vu comme un prédicteur attentionnel. Nos travaux se basent sur un modèle existant qui quantifie l'attention humaine et fournit une matrice attentionnelle qui décrit la distribution des ressources attentionnelles de chaque personne entre les différents éléments, personnes et objets de son environnement. Le calcul du champ attentionnel introduit découle de cette matrice attentionnelle. En considérant différents scénarios d'étude, on montre comment la matrice et le champ attentionnel(le) peuvent être utilisés en HRM

Motion Safety with People: an Open Problem

International audienceIn this presentation, we explore and question the concept of motion safety, i.e. the ability to avoid collision, for robots sharing their workspace with people. We establish that absolute motion safety, in the sense that no collision between the robot and the people will ever take place, is impossible to guarantee (hence the open nature of the motion safety problem). We then discuss the choices that are available: mere risk minimization or what we call weaker motion safety, i.e. types of motion safety that are weaker than absolute motion safety but that can actually be guaranteed. In all cases, we argue that if robots are ever to be deployed among people, it is important to characterize the level of motion safety that can be achieved and to specify the conditions under which it can be guaranteed

Human-Robot Motion: An Attention-Based Navigation Approach

International audienceMobile robot companions are service robots that are mobile and designed to share our living space. For such robots, mobility is essential and their coexistence with humans adds new aspects to the mobility issue: the first one is to obtain appropriate motion and the second one is interaction through motion. We encapsulate these two aspects in the term Human-Robot Motion (HRM) with reference to Human-Robot Interaction. The long-term issue is to design robot companions whose motions, while remaining safe, are deemed appropriate from a human point of view. This is the key to the acceptance of such systems in our daily lives. The primary purpose of this paper is to explore how the psychological concept of attention can be taken into account in HRM. To that end, we build upon an existing model of attention that computes an attention matrix that describes how the attention of each person is distributed among the different elements, persons and objects, of his/her environment. Using the attention matrix, we propose the novel concept of attention field that can be viewed as an attention predictor. Using different case studies, we show how the attention matrix and the attention field can be used in HRM

Safe Navigation of a Car-Like Robot in a Dynamic Environment

voir basilic : http://emotion.inrialpes.fr/bibemotion/2005/PF05a/ address: Ancona (IT)This paper addresses the problem of navigation of a car-like robot in dynamic environments. Such environments impose a hard real time constraint. However, computing a complete motion to the goal within a limited time is impossible to achieve in most real situations. Besides, the limited duration validity of the model used for planning requires the model and therefore the plan to be updated. In this paper, we present a Partial Motion Planning (PMP) approach as the answer to this problem. The issue of safety raised by this approach is addressed using the Inevitable Collision State formalism and effectiveness of the approach is demonstrated with several simulation examples. The quality of the generated trajectories is discussed and continuous curvature metric is integrated as a mean to improve it

Prema sigurnoj navigaciji vozila u dinamičkim urbanim scenarijima

This paper describes the deliberative part of a navigation architecture designed for safe vehicle navigation in dynamic urban environments. It comprises two key modules working together in a hierarchical fashion: (a) the Route Planner whose purpose is to compute a valid itinerary towards the a given goal. An itinerary comprises a geometric path augmented with additional information based on the structure of the environment considered and traffic regulations, and (b) the Partial Motion Planner whose purpose is to ensure the proper following of the itinerary while dealing with the moving objects present in the environment (eg other vehicles, pedestrians). In the architecture proposed, a special attention is paid to the motion safety issue, ie the ability to avoid collisions. Different safety levels are explored and their operational conditions are explicitly spelled out (something which is usually not done).Ovaj članak opisuje ciljno orijentirani dio navigacijske arhitekture za sigurnu navigaciju vozilima u dinamičkim urbanim sredinama. Sastoji se od dva važna modula, koji su hierarhijski povezani: (a) Planer puta koji je odgovoran za pronalaženje valjane globalne rute prema zadanom cilju – ta ruta se sastoji od geometrijskog puta sa dodatnim informacijama u odnosu na zadanu strukturu okoline i regulaciju prometa; (b) Parcijalni planer gibanja čiji zadatak je slijeđenje zadane globalne rute uz navigaciju u prisutnosti pokretnih objekata u okolini (npr. ostala vozila i pješaci). U predloženoj arhitekturi posebna pažnja se pridodaje sigurnosti gibanja, dakle sposobnosti izbjegavanja sudara. Razmotrene su različite razine sigurnosti uz izričiti opis njihovih zadanih režima rada (što je uobičajeno izostavljenou analizama)

An Inevitable Collision State-Checker for a Car-Like Vehicle

An Inevitable Collision State (ICS) for a robotic system is a state for which, no matter what the future trajectory followed by the system is, a collision with an obstacle eventually occurs. The ICS concept takes into account both the dynamics of the robotic system and the future motion of the moving objects of the environment. For obvious safety reasons, a robotic system should never ever end up in an ICS hence the interest of the ICS concept when it comes to safely drive robotic systems in dynamic environments. In theory, determining whether a given state is an ICS requires to check for collision all possible future trajectories of infinite duration that the robotic system can follow from this particular state! In practise, it is fortunately possible to build a conservative approximation of the ICS set by considering only a finite subset of the whole set of possible future trajectories. The primary contribution of the paper is a general principle to select the subset of trajectories based upon the concept of imitating manoeuvres, ie trajectories leading the robotic system to duplicate the behaviour of the environment objects (fixed or moving), it is shown how a good approximation of the ICS set can be obtained. The second contribution of the paper is an ICS-Checker for a car-like vehicle moving in a dynamic environment. This ICS-Checker integrates the above-mentioned selection principle. It is efficient and could be used in practise to compute truly safe motions for a car-like vehicle amidst moving objects

Fuzzy Control to Drive Car-Like Vehicles

International audienceThe reactive component of a motion control architecture (called EM) for a car-like vehicle intended to move in dynamic and partially known environments is presented in this paper. Its purpose is to generate commands for the servo-systems of the vehicle so as to follow a given nominal trajectory while reacting in real-time to unexpected events. EM is designed as a fuzzy controller. A behaviour-based approach is used to set up the fuzzy rule base: the overall behaviour of the vehicle results from the combination of several basic behaviours (trajectory following, obstacle avoidance, etc.). This approach permits an easy and incremental construction of the fuzzy rule base and also to develop and test the basic behaviours separately. EM has been implemented and tested on a real computer-controlled car equipped with sensors of limited precision and reliability. Experimental results obtained with the prototype vehicle are presented. They demonstrate the capability of EM to actually control a real vehicle and to perform trajectory following and obstacle avoidance in real outdoor environments by using simple fuzzy behaviours relying upon low-resolution sensor data