In a variety of military operations, a convoy of autonomous followers may need to traverse the leader's path without using Global Positioning System (GPS), lane markers/magnets and/or a vision-based vehicle-following system. This can be achieved by using Visual Teach and Repeat (VT and R), which provides an effective method for autonomous repeating of a previously driven path. This thesis describes the design of a distributed control system that uses the idea behind the VT and R method to allow a convoy of inter-communicable autonomous vehicles to follow a manually-driven lead vehicle's path with a desired inter-vehicle spacing, even when the leader is not in the camera view of the followers. The longitudinal controller is designed for addressing a 1D spacing problem and then combined with a path tracker for tracking a path in a 2D environment. The designed control model is tested in simulations.

In a variety of military operations, a convoy of autonomous followers may need to traverse the leader's path without using Global Positioning System (GPS), lane markers/magnets and/or a vision-based vehicle-following system. This can be achieved by using Visual Teach and Repeat (VT and R), which provides an effective method for autonomous repeating of a previously driven path. This thesis describes the design of a distributed control system that uses the idea behind the VT and R method to allow a convoy of inter-communicable autonomous vehicles to follow a manually-driven lead vehicle's path with a desired inter-vehicle spacing, even when the leader is not in the camera view of the followers. The longitudinal controller is designed for addressing a 1D spacing problem and then combined with a path tracker for tracking a path in a 2D environment. The designed control model is tested in simulations.

The objective of this research is to explore a methodology that can be used for testing and evaluating AVCS technologies, and, in particular, automatic headway control models for trucks operating on rural highways. The emphasis is put on the realization of vehicle headway control in the real world highway systems. System dynamics has been selected as the simulation tool for developing, testing and evaluating vehicle headway control models. The following behavior of human driver in a real world highway environment is studied and simulated. An automatic headway control model, Multiple-mode Vehicle Headway Control (MVHC) model, is developed for single lane, cars and trucks mixed flow control in a rural highway system. Using safety and motorist comfort as MOE criteria and the acceleration noise as the index of motorist comfort, some selected automatic headway control models are evaluated. This study demonstrated that simulation affords a means of modeling control processes with various certain and uncertain factors, and therefore, it plays a key role in the development of automatic headway control systems. / Ph. D.

Intelligent Transportation Systems (ITS), which uses modem electronics and communications technology to guide or control the operation of vehicles holds great promise for increasing the capacity of existing roads. reducing congestion and accident losses, and contributing to the ease and convenience of travel. The most sophisticated of all the ITS technologies that may ultimately yield the largest benefits is the Automated Highway Systems (AHS). The AHS approach to enhance the performance of our highways is to apply automation techniques to vehicles and roadways to increase the capacity and efficiency of existing facilities, while retaining the advantages of individual mobility. The idea is to have a system with instrumented highways and vehicles which allows the automation of the driving function. The overall objective of this research study involves the modeling and analysis of an AHS system, using a simulation tool specifically developed for this purpose. A multi-layer control system architecture that conforms to the one developed at the University of California, Berkeley, provides a framework for the micro and macroscopic modeling of the system. The focus of the system modeling is towards the lower layers of this control system architecture, involving a comprehensive modeling of the regulation and physical layers and a simple, yet realistic modeling of the functionalities of the link layer. The regulation and physical layer design incorporates a complete power train modeling of the vehicle that includes one-wheel rotational dynamics, linear vehicle dynamics, engine dynamics and actuator dynamics. / Master of Science

Platooning concept involves a group of vehicles acting as a single unit through coordination of movements. While Platooning as an evolving trend in mobility and transportation diminishes the individual and manual driving concerns, it creates new risks. New technologies and passenger’s safety and security further complicate matters and make platooning attractive target for the malicious minds. To improve the security of the vehicular platooning, threats and their potential impacts on vehicular platooning should be identified to protect the system against security risks. Furthermore, algorithms should be proposed to detect intrusions and mitigate the effects in case of attack. This dissertation introduces a new vulnerability in vehicular platooning from the control systems perspective and presents the detection and mitigation algorithms to protect vehicles and passengers in the event of the attack.

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Driver psychology is one of the most difficult phenomena to model in the realm of traffic flow theory because mathematics often cannot capture the human factors involved with driving a car. Over the past several decades, many models have attempted to model driver aggressiveness with varied results. The recently proposed Longitudinal Control Model (LCM) makes such an attempt, and this paper offers evidence of the LCM's usefulness in modeling road dynamics by analyzing deceleration rates that are commonly associated with various levels of aggression displayed by drivers. The paper is roughly divided into three sections, one outlining the LCM's ability to quantify forces between passive and aggressive drivers on a microscopic level, one describing the LCM's ability to measure aggressiveness of platoons of drivers, and the last explaining the meaning of the model’s derivative. The paper references some attempts to capture driver aggressiveness made by classic car-following models, and endeavors to offer some new ideas in study of driver characteristics and traffic flow theory.

Ce mémoire est consacré à la mise en œuvre de commandes d'un train de véhicules intelligents sur autoroute ayant pour objectifs principaux de réduire la congestion et d’améliorer la sécurité routière. Après avoir présenté l'état de l'art sur des systèmes de conduite automatisée, des modèles de la dynamique longitudinale et latérale du véhicule sont présentés. Ensuite, des stratégies de contrôle longitudinal et latéral sont étudiées.D'abord, le contrôle longitudinal est conçu pour être hiérarchique avec un contrôleur de niveau supérieur et un contrôleur de niveau inférieur. Pour celui de niveau supérieur, une régulation d'inter-distance SSP (Safety Spacing Policy) est proposée. Nous avons constaté que la SSP peut assurer la stabilité de la chaîne et la stabilité des flux de trafic et augmenter ainsi la capacité de trafic. Puis, pour celui de niveau inférieur, une loi de commande floue coordonnée est proposée pour gérer l'accélérateur et le freinage. Ensuite, une loi de commande multi-modèle floue est conçue pour le contrôle latéral. De plus, pour réaliser des transformations lisses entre les différentes opérations latérales, une architecture de contrôle hiérarchique est proposée. Puis, l'intégration des commandes longitudinale et latérale est étudiée. Enfin, l'estimation des variables d’états du véhicule est discutée. Un filtre de Kalman-Bucy est conçu pour estimer les états du véhicule. En outre, un prototype de véhicule intelligent à échelle réduite est également présenté. Les performances des divers algorithmes de commande proposés ont été testées par simulations, et les résultats ont été confirmés par les premières expériences en utilisant le prototype / This PhD thesis is dedicated to the control strategies for intelligent vehicle platoon in highway with the main aims of alleviating traffic congestion and improving traffic safety. After a review of the different existing automated driving systems, the vehicle longitudinal and lateral dynamic models are derived. Then, the longitudinal control and lateral control strategies are studied respectively. At first, the longitudinal control system is designed to be hierarchical with an upper level controller and a lower level controller. For the upper level controller, a safety spacing policy (SSP) is proposed. It is shown that the proposed SSP can ensure string stability, traffic flow stability and improve traffic capacity. Then, a coordinated throttle and brake fuzzy controller (lower level controller) is designed, in which a logic switch is designed to coordinate the two actuators (throttle and brake pedals). Second, for the lateral control, a multi-model fuzzy controller is designed. And a hierarchical lateral control architecture is also proposed, which can effectuate flexible switch between different lateral operations. After that, the integration of the longitudinal controller and lateral controller is also studied. Finally, the estimation of vehicle states is discussed. A Kalman-Bucy filter is designed to estimate vehicle states in lateral dynamics. Moreover, a reduced scale multi-sensor intelligent vehicle prototype is also presented. The performances of the divers control algorithms proposed in this thesis have been tested in numerical simulations, and the first step experiments with the reduced scale vehicle prototype gave encouraging results

Cette thèse est consacrée à l'analyse de performance de Régulateurs de Vitesse Adaptatifs Coopératifs(CACC) pour un train de véhicules intelligents afin de réduire la congestion du trafic et améliorer la sécurité routière.Premièrement, la politique d'espacement, à Intervalles Constants de Temps (CTH) est introduite. Basé sur cette politique d'espacement, un nouveau système décentralisé de Deux-Véhicules-Devant CACC (TVACACC) est proposé, dans lequel l'accélération souhaitée de deux véhicules précédents est prise en compte. Ensuite, la stabilité de la chaîne du système proposé est analysée théoriquement. Il est démontré que grâce à l'aide de la communication multiple entre véhicules, une meilleure stabilité de la chaîne est obtenue par rapport au système conventionnel. Un train de véhicules dans le scénario Stop-and-Go est simulé avec une communication parfaite puis dégradée. Le système proposé donne un comportement stable de la chaîne, correspondant à l'analyse théorique.Deuxièmement, une technique de dégradation pour CACC est présentée comme stratégie alternative lorsque la communication sans fil est partiellement ou complètement perdue. La stratégie proposée, appelée DTVACACC, utilise le filtre de Kalman pour estimer l'accélération actuelle du véhicule précédent qui remplace l'accélération souhaitée. Il est démontré que la performance pour le DTVACACC, peut être maintenue à un niveau beaucoup plus élevé.Enfin, une approche d’Apprentissage par Renforcement (RL) pour système CACC est proposée. L' algorithme politique- gradient est introduit pour réaliser le contrôle longitudinal . Ensuite, la simulation a montré que cette nouvelle approche de RL est efficace pour CACC / This PhD thesis is dedicated to the performance analysis of Cooperative Adaptive Cruise Control (CACC) system for intelligent vehicle platoon with the main aims of alleviating traffic congestion and improving traffic safety. At first, the Constant Time Headway (CTH) spacing policy for vehicle platoon is introduced. Based on this spacing policy, a novel decentralized Two-Vehicle-Ahead CACC (TVACACC) system is proposed, in which the desired acceleration of two front vehicles is taken into account. Then the string stability of the proposed system is theoretically analyzed. It is shown that by using the multiple wireless communication among vehicles, a better string stability is obtained compared to the conventional system. Vehicle platoon in Stop-and-Go scenario is simulated with both normal and degraded communication.Secondly, a graceful degradation technique for CACC was presented, as an alternative fallback strategy when wireless communication is lost or badly degraded. The proposed strategy, which is referred to DTVACACC, uses Kalman filter to estimate the preceding vehicle’s current acceleration as a replacement of the desired acceleration. It is shown that the performance is maintained at a much higher level.Finally, a Reinforcement Learning (RL) approach of CACC system is proposed. The policy-gradient algorithm is introduced to achieve the longitudinal control. Then simulation has shown that this new RL approach results in efficient performance for CACC.

The main objective of the present thesis focuses on the integration of the in-wheel electric motors into the conception and control of road vehicles. The present thesis is the subject of the grant 186-654 (2010-2013) between the Laboratory of Signals and Systems (L2S-CNRS) and the French Institute of Petrol and New Energies (IFPEN). The thesis work has originally started from a vehicular electrification project, equipped with in-wheel electric motors at the rear axle, to obtain a full electric urban use and a standard extra-urban use with energy recovery at the rear axle in braking phases. The standard internal combustion engines have the disadvantage that complex estimation techniques are necessary to compute the instantaneous engine torque. At the same time, the actuators that control the braking system have some delays due to the hydraulic and mechanical circuits. These aspects represent the primary motivation for the introduction and study of the integration of the electric motor as unique propelling source for the vehicle. The advantages brought by the use of the electric motor are revealed and new techniques of control are set up to maximize its novelty. Control laws are constructed starting from the key feature of the electric motor, which is the fact that the torque transmitted at the wheel can be measured, depending on the current that passes through the motor. Another important feature of the electric motor is its response time, the independent control, as well as the fact that it can produce negative torques, in generator mode, to help decelerate the vehicle and store energy at the same time. Therefore, the novelty of the present work is that the in-wheel electric motor is considered to be the only control actuator signal in acceleration and deceleration phases, simplifying the architecture of the design of the vehicle and of the control laws. The control laws are focused on simplicity and rapidity in order to generate the torques which are transmitted at the wheels. To compute the adequate torques, estimation strategies are set up to produce reliable maximum friction estimation. Function of this maximum adherence available at the contact between the road and the tires, an adequate torque will be computed in order to achieve a stable wheel behavior in acceleration as well as in deceleration phases. The critical issue that was studied in this work was the non-linearity of the tire-road interaction characteristics and its complexity to estimate when it varies. The estimation strategy will have to detect all changes in the road-surface adherence and the computed control law should maintain the stability of the wheel even when the maximum friction changes. Perturbations and noise are also treated in order to test the robustness of the proposed estimation and control approaches.