Contributions to road safety: from abstractions and control theory to real solutions, discussion and evaluation

This manuscript aims to describe my career in the transportation domain, putting in evidence my contributions in different levels, as for example thesis advising, teaching, research animation and coordination, projects construction and participation in expert committees, among others, besides my scientific research itself. The goal, besides the HDR diploma itself, is to show very clearly, including to myself, this 'pack' of contributions in order to look for better contributions to the transportation and control communities or to other communities in the future, and also which research directions I will define to work on in the following. I obtained my PhD degree in the Laboratoire des Signaux et Systèmes - L2S 1 in collaboration with MIT, in 2001, having worked in a purely theoretical automatic control topic scarcely known in the literature - the adaptive control of systems with nonlinear parameterization problem. Arriving in 2002 as a permanent researcher to the former LCPC (Laboratoire Central des Ponts et haussées), now called IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux), I have been faced to real problems to solve in practice, and faced to the new community of transportation, with a completely different philosophy of work. I have nowadays this double vision - of the very applied transportation domain with concrete problems to be solved that touch the citizen every day, and the vision of a very rich high-level theoretical research in automatic control with powerful tools to solve the real problems, or on the other hand, with control problems that appear because of the need for new tools to solve the real problems. I consider this as an important characteristic for my future contributions. Besides the knowledge in Transportation itself, my eleven years of career in IFSTTAR gave me as well the following new features : 1. From the individual research, I have learned also how to coordinate work (in projects for example, as in the PReVAL sub-project of the European PReVENT project, in which I co-leaded one workpackage, or for research teams, as the control team of LIVIC, coordinated by myself from 2006 to 2009). I have also learned how to animate research (by coordinating research working groups or organizing scientific events and workshops - see for example the working group RSEI and the related scientific event below that I have organized in June 2012) and how to advise students. 2. Besides the double vision I have described above, the experience gave me also the acquisition of a quite multidisciplinary view of the problems in the domain. Firstly, arriving in LIVIC, in the frame of the French consortium ARCOS, I have worked for two years in close cooperation with experts in cognitive sciences (the PsyCoTech group from IRCCyN, Nantes) on designing driving assistance systems to a human driver. After this work, I have continued the collaboration with experts in human sciences within the PReVAL subproject of PReVENT on driving assistance systems evaluation and within the French ANR PARTAGE project, that I have constructed together with the PsyCoTec team of IRCCyN and leaded the IFSTTAR partner for one year. In a dition, through my participation in PReVENT at dirent levels (in two meetings of the Core Group, in PReVAL by co-leading the workpackage 3 on Technical Evaluation of ADAS - ADAS is the shortcut for Advanced Driving Assistance Systems - and in the SAFELANE subproject), I have learned many different aspects of ITS systems. I consider this as an add-on value for my 'pack of knowledge'. 3. What I call "from abstractions to real problems : coming back and forth to solve these real problems" has been matured in my mind, and I am very grateful to my students, with whom I have learned and that helped me in this maturing process. By this sentence, I mean, with a problem to solve in hands, and after building an abstraction, or a simplified view of the problem, and the design of a solution, how to apply it, and to come back again to the theory to change it and to come back to the practice, and so on. This is exactly one of the pillars of the NoE HYCON2, for making interact the theory with the application domains. 4. Considering a problem inserted into the societal context, or inserted within its related context, has been another maturing for myself that I consider very important, notably in the transportation domain, that represents a very complex context containing many different parameters, scenarios and objectives and in addition all the uncertainties linked to the human behavior. I think that it is very important to have a very large view of the context in which the specific problem we are treating is placed. Without this, one cannot say in most of the cases, from my point of view, that the problem is solved. This point will be discussed in Chapter 9.5. 5. Another point that I consider important and where I have been contributing recently is the road mapping work. The acquisition of the multidisciplinary knowledge and a larger view of the domain that I have mentioned in the preceding items, together with my theoretical knowledge in automatic control, allowed myself to start contributing to theroad mapping work in Transportation (through my participation in the imobility forum, in HYCON2 and the in the support action T-Area-SoS on Systems of Systems - all these actions to give advice to the European Commission on the priority areas to be considered in the new Calls, notably in the frame of the H2020 program). I had also the pleasure of opening again books and thesis that I had studied in my PhD work, this time now for advising students in the frame of other very different problems. The very beautiful thesis of Mikael Johansson, Lund University, on piecewise linear systems stability theory is an example. My previous study on switched systems, and the implication of switched Lyapunov functions on stability helped me also in advising my students (Post-Docs, PhD, and M.Sc. students), this time for real applications, with very interesting results blooming up from their work. I realize also that the experience that I have described in the five items above must be put in favor of students since this kind of knowledge cannot be found in the books. Concluding, in these last eleven years, from 2002 to 2013, I could bring to the scientic community and to my students a set of contributions of different kinds. I will try to make clear these contributions for the reader in the next two chapters (written in English and in French). This document is organized in the following way : Part II contains my complete curriculum vitae (in french) where all these contributions will be described in detail. Part III contains then the scientific contributions of the manuscript. What I aim in this chapter is to describe, but further, to analyze them with a distanced look and providing a critical view, announcing perspectives, and placing and discussing the obtained results in the societal context. This is in straight relation with item 4 above. Also, I prefer to adopt, as far as possible, a form comprehensible to the non-automatic control expert, with, as far as possible as well, qualitative explanations and then appropriated references containing the theorems and the definitions corresponding to the qualitative explanations will be provided. In the case it is necessary, they are provided within the text. The Part III is structured in the following chapters. Chapter 8 contains an overview of the global transportation scenario with the associated challenges and a description of the driving assistance systems context. Chapter 9 contains my scientific contributions. These include my research results, my contributions in students advising, in the coordination of research groups, and the collaborative works. It is structured in 3 sections : Section 9.1 introduces what will be the greed for a part of the main contributions, that are described in Sections 9.2 and 9.3. Section 9.1 is also dedicated to showing to the reader how theory and abstractions can be very important for solving real problems. Chapter 9.4 describes other contributions that are the result of collaborative works. A discussion from a multidisciplinary view is provided in Chapter 9.5 based on a survey paper of myself. Chapter 10 will be finally dedicated to the perspectives and the general conclusions. Then last Part contains as annexes a selection of the publications that I consider the most illustrative of my contributions described in Chapter 9. Finally, since the described work is in the intersection of two communities - the transportation and the control theory communities - I decided to write a part of the document dedicated to the non control experts readers. This is Part VI of the document whose aim is to provide some fundamental notions on control theory in a very simple qualitative description whose understanding will help the different readers to understand the contributions

Model-Based Threat Assessment in Semi-Autonomous Vehicles with Model Parameter Uncertainties

In this paper, we consider model-based threat assessment methods which rely on vehicle and driver mathematical models and are based on reachability analysis tools and set invariance theory. We focus on the parametric uncertainties of the driver mathematical model and show how these can be accounted for in the threat assessment. The novelty of the proposed methods lies in the inclusion of the driver model uncertainties in the threat assessment problem formulation and in their validation through experimental data. We show how different ways of accounting for the model uncertainties impact the capabilities and the effectiveness of the proposed algorithms in detecting hazardous driving situations

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

차량간 통신을 이용한 지능형 자동차의 전방차량 위험판단 기법

학위논문 (박사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 이경수.In recent years, advanced driver assistance systems or highly automated driving systems are expected to enhance road traffic safety, transport efficiency, and driver comfort. Practical applications have become possible due to recent advances in vehicle local sensors and inter vehicle communications. These advances have opened up many possibilities for active safety systems to be more intelligent and robust. The further enhancement of these technologies can be utilized as a risk assessment system of automated drive. This dissertation presents a risk assessment for improved vehicle safety using Front Vehicle Dynamic States through vehicle-to-vehicle wireless communication. A vehicle-to-vehicle wireless communication (V2V communication) has been implemented and fused with a radar sensor to obtain the prediction of remote vehicles motion. Based on the predicted behavior of remote vehicles, a collision risk and a human reaction time are determined for a better driver acceptance and active safety control intervention. A human-centered risk assessment using the V2V communication has been incorporated into a collision avoidance algorithm to monitor threat vehicles ahead and to find the best intervention point. The performance of the proposed algorithm has been investigated via computer simulations and vehicle tests for application to urban and highway driving situation. It has been shown from both simulations and vehicle tests that the proposed integrated risk assessment algorithm with the V2V communication can be beneficial to active safety systems in decision of controller intervention moment and in control of automated drive for the guaranteed safety.Chapter 1 Introduction 1 1.1 Background and Motivations 1 1.2 Previous Researches 5 1.3 Thesis Objectives 9 1.4 Thesis Outline 11 Chapter 2 Vehicular Communication 12 2.1. Literature Review 14 2.1.1 An Empirical Model for V2V communication 14 2.1.2 Position based Sampling and Distance based Interpolation 17 2.2. Communication Delay and Packet Loss Ratio 21 2.2.1 Compensation of V2V Communication Delay 21 Chapter 3 Human Factor Considerations 27 3.1. Driver Acceptance 30 3.1.1 Driver inattention and distraction 31 3.1.2 Mode Confusion 31 3.1.3 Motion Sickness 32 3.2. Sight Distance 33 3.2.1 Stopping Sight Distance 35 3.2.2 Decision Sight Distance 35 Chapter 4 Human-Centered Risk Assessment using Vehicular Wireless Communication 37 4.1. Human-Centered Design 41 4.2. Convergence 43 4.2.1. Sensor-Based Solutions 44 4.2.2. The Benefits to Convergence 45 4.2.3. V2V/Radar Information Fusion 45 4.3. Related Work 46 4.3.1. Radar Sensing Characteristics 47 4.3.2. Probabilistic Threat Assessment 50 4.3.3. Human-Centered Vehicle Control 52 4.3.4. High-Level Information Fusion 54 4.3.5. Target Vehicle State Estimation Performance 58 4.4 Remote Vehicle States Prediction 64 4.5. Collision Risk Analysis 67 4.6. Predicted Collision Distance 70 4.7. Active Safety Intervention Moment Decision 72 Chapter 5 Performance Evaluations 77 5.1. Simulations: MPC based Automated Vehicle Control 78 5.1.1. Effects of V2V Communication on the Controller 78 5.2. Simulations : Human-Centered Risk Assessment 84 5.2.1. Scenarios 84 5.2.2. Effects of V2V Communication: Host vehicle perception only 86 5.2.3. Effects of V2V Communication: Controlled host vehicle 90 5.3. Vehicle Tests 94 5.3.1. Test Vehicle Configuration and Scenario 94 5.3.2. Implementation and Evaluation 96 Chapter 6 Conclusion 99 Bibliography 100 국문초록 110Docto

레이저 스캐너 기반 자율주행용 교차로 내 주변 차량 인지 알고리즘 개발

학위논문 (석사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 이경수.The aim of this study is designing surrounding vehicle movement perception algorithm in urban condition. In recent autonomous vehicle industry, many researchers are focusing on three major topics which is called environment perception, localization and designing controller for autonomous vehicle these days. Especially for the perception technology, the design of the algorithm follows the characteristics of the target environment or objects. In Urban condition, to design safe drivable path for autonomous vehicle, the objects position is much important than high way conditions. Also, various objects appear which cannot be detected with RADAR or yield fault case with camera. Because of these reasons, many research are trying to fuse different sensors including camera, RADAR and LiDAR to overcome the challenges that can occur in urban conditions, therefore, laser scanner based target detecting technology is needed to perceive in city road. The tracking filter consists of two parts, shape estimation and tracking filter. To fuse with other sensors or designing target filter, there should be a step for compressing point cloud group information into some representative point or state. Thus in shape estimation parts, we transform the laser scanners point cloud data into vehicle position state measurement value. Vehicle shape estimation also consists of two parts, clustering and shape extraction. Clustering classify the total point cloud into object level and shape extraction estimates the vehicle liked objects position information. The clustering part works based on Euclidean Minimum Spanning Tree (EMST), and for the shape extraction, Random Sample Consensus (RANSAC) method is used to estimate the target objects rear and side edge. The second part, tracking filter, has two different filters. Particle filter estimates the target vehicles position including heading angle. To improve the tracking performance of the particle filter, Kalman filter is also designed to estimate the velocity and yaw rate recursively to update the process model of the particle filter. The performance of the proposed algorithm has been verified with several stages. To check quantitative error level, off-line simulation is held for profile based motion tracking case and designed intersection simulator with simple path tracking algorithm for the target vehicle. In these conditions, the exact target vehicles position information was known, thus we verified the error level of the lateral/longitudinal direction of target vehicles local coordinate which is important information when designing driving path or controller. For the second step, simulation with point cloud data which is collected from the test vehicle was held to verify its performance for actual vehicle condition. As a final stage, for integrating into autonomous vehicle, the proposed algorithm evaluated into the test vehicle for guaranteeing on-line performance.Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Research Overview 3 Chapter 2 Target Vehicle Tracking Filter 4 2.1 Laser scanner Data Post-processing 6 2.2 Vehicle Tracking with Particle Filter 9 2.3 Process model Input Update with Kalman Filter 11 Chapter 3 Simulation 14 3.1 Pre-defined Profile based Simulation 14 3.2 Intersection Environment based Simulation 22 Chapter 4 Vehicle Experiment Data Test 28 4.1 Test Vehicle Configuration 28 4.2 Vehicle Experiment data based Simulation 30 4.3 Actual Vehicle Test 40 Chapter 5 Conclusion 45 Bibliography 46 국문초록 49Maste

Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands

Book of abstract

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Driver steering assistance for lane departure avoidance based on hybrid automata and composite Lyapunov function

International audienceThis paper presents the design and the practical implementation of vehicle steering assistance that helps the driver avoid unintended lane departure. A switching strategy is built to govern the driver-assistance interaction, and the resulting hybrid system is formalized as an input/output (I/O) hybrid automaton. Composite Lyapunov functions, polyhedral-like invariant sets, and linear matrix inequality (LMI) methods constitute the heart of the approach used to design the lane-departure avoidance (LDA) system. The practical implementation of this steering assistance in a prototype vehicle confirms the effectiveness of this approach

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space