Connected Vehicular Systems E-Book

Ge Guo

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch
• Veröffentlichungsjahr: 2023

Seitenzahl: 457

Beschreibung

CONNECTED VEHICULAR SYSTEMS A framework for the analysis and design of connected vehicle systems, featuring numerous simulations, experimental studies, and problem-solving approaches Connected Vehicular Systems synthesizes the research advances of the past decade to provide readers with practical tools to analyze and design all aspects of connected autonomous vehicle systems, addressing a series of major issues and challenges in autonomous connected vehicles and transportation systems, such as sensing, communication, control design, and command actuating. The text provides direct methodologies for solving important problems such as speed planning, cooperative adaptive cruise control, platooning, and string traffic flow stability, with numerous simulations and experimental studies for implementing algorithms and parameter settings. To help the reader better understand and implement the concepts discussed, the text includes a variety of worked examples, including those related to car following, vehicular platooning problem, string stability, cooperative adaptive cruise control, and vehicular communications. Written by two highly qualified academics with significant experience in the field, Connected Vehicular Systems includes information on: * Varying communication ranges, interruptions, and topologies, along with controls for event-triggered communication * Fault-tolerant and adaptive fault-tolerant controls with actuator saturation, input quantization, and dead-zone nonlinearity * Prescribed performance concurrent controls, adaptive sliding mode controls, and speed planning for various scenarios, such as to reduce inter-vehicle spacing * Control paradigms aimed at relaxing communications constraints and optimizing system performance * Detailed algorithms and parameter settings that readers can implement in their own work to drive progress in the field Connected Vehicular Systems is an essential resource on the subject for mechanical and automotive engineers and researchers involved with the design and development of self-driving cars and intelligent transportation systems, along with graduate students in courses that cover vehicle controls within the context of control systems or vehicular systems engineering.

Leseprobe

Connected Vehicular Systems

Communication, Control, and Optimization

Ge Guo

The State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University

The School of Control Engineering, Northeastern University at Qinhuangdao, China

Shixi Wen

School of Information and Engineering

The Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, China

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Library of Congress Cataloging‐in‐Publication DataNames: Guo, Ge (Of Dongbei da xue (1993)), author. | Wen, Shixi, author.Title: Connected vehicular systems : communication, control, and optimization / Ge Guo, Shixi Wen.Description: Hoboken, New Jersey : Wiley, [2024] | Includes index.Identifiers: LCCN 2023022911 (print) | LCCN 2023022912 (ebook) | ISBN 9781394205462 (cloth) | ISBN 9781394205479 (adobe pdf) | ISBN 9781394205486 (epub)Subjects: LCSH: Automated vehicles. | Intelligent transportation systems.Classification: LCC TL152.8 .G86 2024 (print) | LCC TL152.8 (ebook) | DDC 629.04/6--dc23/eng/20230601LC record available at https://lccn.loc.gov/2023022911LC ebook record available at https://lccn.loc.gov/2023022912

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Preface

With the ubiquitous application of vehicle‐to‐vehicle (V2V) and vehicle‐to‐infrastructure (V2I) communication technologies, connected and automated vehicles (CAVs) are capable of gathering and sharing road and traffic information and even vehicle states with neighboring vehicles. In particular, enabled by the information shared, CAVs allow automated vehicle motion, car following, cooperated driving and platooning, and vehicle‐traffic signal cooperative control. Therefore, CAVs are believed to be a promising technology to deliver greater safety and mobility benefits to the new generation of intelligent transportation systems (ITSs) with increased driving safety, ride comfort, traffic efficiency, and throughput, along with reduced congestion, accidents, emissions, and air pollution. However, the operation of CAVs and the associated ITSs depends heavily on timely and reliable information gathering and sharing, proper decision‐making, and effective actuation of the driving decision. However, critical challenging issues are facing CAVs from all aspects including sensing, communication, control design, and command actuating, which, if not properly addressed, can result in safety risks and losses.

This book contains our research advances in the past decade in the analysis and synthesis of CAV systems from all aspects of trajectory planning, cooperative control, and communication. The focus of this book is on the development of mathematical models and methodologies for trajectory optimization and tracking control, communications conflict resolution, cooperative control subject to communication constraints, and sensor/actuator failures/faults for CAVs from different perspectives. This book is composed of 14 chapters. The contents are divided into three parts, with Chapter 1 – Chapter 5 as Part I, Chapter 6 – Chapter 9 as Part II, and Chapter 10 – Chapter 14 as Part III, respectively, concerned with cooperative vehicular communication and control, performance guarantee under actuator limitations, and speed trajectory planning and tracking control of CAVs.

Chapter 1 studies the platoon control problem subject to varying communication range with a constant‐spacing policy. According to the connectivity status between the leader and each follower, connected vehicles control is modeled as a switched platoon control system with a connectivity‐status‐matrix‐dependent controller. By using switched system theory, a series of sufficient conditions are obtained as a criterion for the stability analysis and control synthesis of the leader following platoon. Based on the obtained conditions, a useful control algorithm is proposed for connected vehicles. For each obtained connectivity‐status‐matrix‐dependent controller, the string stability and a zero steady‐state spacing error can be guaranteed by additional conditions.

Chapter 2 investigates platooning of connected vehicles considering communication interruption and latency. For a heterogeneous platoon of vehicles, a hybrid reference model with cooperative adaptive cruise control (CACC) and adaptive cruise control (ACC) is established. Then a novel CACC‐ACC switching control method is suggested, which activates either a CACC scheme or an augmented ACC strategy depending on the status of communications. By introducing a platoon state tracking error system, a control algorithm is derived using finite‐time sliding‐mode control theory, which can robustly guarantee string stability and zero steady‐state spacing error of the connected vehicles.

Chapter 3 studies the co‐design problem of platoon controller and inter‐vehicle communication topology (IVCT) in LTE‐V2V networks. The communication assignment is achieved based on the cooperative awareness message dissemination mechanism. A sampled‐data feedback controller is proposed for connected vehicles to eliminate the effect of stochastic packet dropouts and external disturbance, where the controller gain depends on the IVCT. To guarantee the stability requirement of connected vehicles with the minimized cost function, a unified control framework is established to jointly determine the optimal IVCT from all the available ones and the associated feedback controller gain. This co‐design procedure is based on the optimal control and dynamic programming technique, where both fixed and periodic switching IVCTs are available. A useful algorithm is proposed to implement the established co‐design framework.

Chapter 4 addresses the platoon control problem in a sampled‐data setup with switching communication topology and transmission delays. A tracking error‐based sampled‐data control method is proposed, where the neighboring vehicle’s state information is transmitted via the VANET with communication delay. By representing the switching communication topology by a Markovian chain, the connected vehicular control system is modeled as a Markovian switching time‐delay system with disturbance. In the context of Markovian jumping system theory, a control methodology is obtained for connected vehicles to guarantee that the tracking errors can be stabilized mean‐square exponentially with a given disturbance attenuation level. The controllers of connected vehicles with both fixed and variable gains are suggested. The results are extended to cover partially unknown transition rates of the Markov chains.

Chapter 5 studies the co‐design problem considering a dynamic event‐triggered communication mechanism (DECM). Under the DECM, the transmissions of sampled velocity and acceleration from a preceding vehicle to the controller can be significantly reduced. A sampled‐data platoon controller is designed based on the tracking error (spacing error, velocity error, and acceleration error). Sufficient conditions for the stability of the CACC system are obtained for the DECM‐based sampled‐data feedback controller. According to the obtained conditions, parameter design criteria are established for the DECM to guarantee the stable performance of connected vehicles control systems.

Chapter 6 addresses a fault‐tolerant control problem for connected vehicles subject to actuator faults and saturation. To compensate for the effects of actuator faults and saturation, an adaptive fault‐tolerant control method is proposed based on nonlinear vehicle dynamics and a new quadratic spacing policy. The improved quadratic spacing policy is introduced to remove the assumption of zero initial spacing errors. The nonlinear vehicle dynamics is approximated by a radial basis function neural network (RBFNN). The adaptive fault‐tolerant control method is developed in the context of the PID‐type sliding‐mode control technique and proved to be capable of guaranteeing individual vehicle stability, string stability, and traffic flow stability.

Chapter 7 revisits the fault‐tolerant control problem for connected vehicles considering actuator faults, input quantization, and dead‐zone nonlinearity. The occurrence of actuator faults may cause abrupt velocity and acceleration change, which may yield a violation of the spacing policy. So, an improved quadratic spacing policy reflecting the effect of actuator fault is proposed, which removes the condition of zero initial spacing errors. Then, an adaptive fault‐tolerant control scheme is developed by employing RBFNN and PID‐type sliding‐mode control method.

Chapter 8 investigates prescribed performance concurrent control (PPCC) of connected vehicles with unknown parameters, disturbances, and actuator saturation. A closer spacing policy is introduced to achieve string stability with a virtual leader‐bidirectional information flow. Based on a new transformed tracking error function and an auxiliary system introduced to deal with actuator saturation, a distributed adaptive tracking PPCC controller is designed to achieve individual vehicle stability and string stability in the sense that all the signals in the system are uniformly ultimately bounded.

Chapter 9 revisits the prescribed performance platoon control problem in the presence of actuator saturation, uncertain parameters, and unknown disturbances. Two adaptive sliding‐mode control schemes based on leader‐predecessor and leader‐bidirectional information flows, respectively, are presented to ensure string stability and strong string stability with prescribed tracking performance. The actuator saturation nonlinearity is approximated with a smooth hyperbolic tangent function. The effects of uncertain parameters and exogenous disturbances are dealt with by introducing a set of adaptation laws.

Chapter 10 studies the speed optimization and tracking control problem for heavy‐duty truck platoons. The speed planning algorithm is derived with regard to an average vehicle based on a combined fuel‐time cost and receding dynamic programming. The idea of using an average vehicle instead of the leader for speed planning makes the speed profile more fuel‐efficient for platooning of vehicles different in weight and size. The vehicle controller, a discrete‐time back‐stepping control law, is designed on the basis of a nonlinear vehicle model considering road slope and heterogeneity of vehicles. The control algorithm is strengthened by a novel string stability criterion.

Chapter 11 is concerned with speed optimization and tracking control problems for platooning of connected vehicles. A two‐layered control architecture is presented: a set‐point optimization layer and a vehicle tracking control layer. In the first layer, a speed‐planning algorithm is derived to calculate the speed set‐point for the connected vehicles by averaging the optimal speed of each vehicle, which is obtained by solving a fuel‐time optimization problem based on Pontryagin’s minimum principle. The second layer contains a set of distributed sliding‐mode controllers for vehicle tracking control, which can guarantee string stability of the connected vehicles with the desired inter‐vehicle spacing.

Chapter 12 investigates distributed trajectory optimization and adaptive platoon control of connected vehicles. A distributed hierarchical framework is proposed for trajectory optimization and tracking control. The upper layer provides an optimal trajectory for each vehicle, which is realized by minimizing the inter‐vehicle spacing with regard to the desired values using convex optimization. The lower layer contains an adaptive sliding‐mode controller to track the optimal trajectory. To compensate for uncertain vehicle dynamics, a parameter adaptation law based on the tracking error dynamics is involved in the controller, which guarantees both individual vehicle stability and string stability.

Chapter 13 studies distributed trajectory optimization and platoon control problems for connected vehicles with a quadratic spacing policy. The quadratic spacing policy based on the expected team speed is introduced to improve the flexibility of speed planning and regulation. The trajectory optimization problem is solved using distributed convex optimization based on spacing error minimization, resulting in an algorithm to provide the optimal trajectory for all following vehicles. Then, a PID‐type sliding‐mode controller with a double high‐power reaching law is presented for speed‐tracking control of each follower. The methodology can guarantee individual vehicle stability, string stability, and traffic flow stability with ignorable turbulence of spacing and speed.

Chapter 14 extends the distributed trajectory optimization and platooning method to achieve fixed‐time tracking. The optimal trajectory for all following vehicles is obtained by minimizing the spacing errors via distributed convex optimization. The trajectory tracking controller is derived based on the tracking error dynamics in the context of fixed‐time stability and terminal sliding‐mode control. The method can robustly guarantee zero steady‐state spacing errors and individual vehicle stability and string stability simultaneously.

In this book, special attention is given to a clear presentation of the formulations, algorithms, and their implementation in numerical simulations and experimental studies. Related works and references are given at the end of each chapter to guide the readers toward further knowledge in this area. The book can be used in courses for graduate students in modeling and control of connected automated vehicles and transportation systems. Researchers and engineers can also draw upon the book in developing mathematical models and algorithms for theoretical study and application purposes.

Ge Guo, Northeastern University, Shenyang, China

Shixi Wen, Dalian University, Dalian, China

2 March 2023

Acknowledgments

Our research work has been funded by the National Natural Science Foundation of China under Grants 60974013, 61273107, 61573077, U1808205, 61803062, and 62173079, and, in part, by the Natural Science Foundation of Liaoning Province under Grant 2022‐MS‐406. We are grateful to the funders for their support in the past decade. The authors acknowledge the contributions of Dandan Li, Qiong Wang, Ping Li, Hongbo Lei, Ziwei Zhao, Dongqi Yang, Jian Kang, Ren‐Yong‐Kang Zhang, and many others for their hard work and commitment that made this monograph come to fruition. Without their effort and time in developing quality contributions in one or two of the chapters, this book would not have been possible.

Part IVehicular Platoon Communication and Control

Communication issues due to bandwidth shortage are inevitable in vehicular ad hoc networks (VANET), which may induce time delay, packet dropouts, and medium access constraints that can lead to performance degradation or even instability in connected vehicular control systems. Moreover, inter‐vehicle communication and control are two aspects that are strongly coupled. This part consists of five chapters. Chapter 1 studies the platoon control problem subject to varying communication range. Based on the connectivity status between the leader and other vehicles, the platoon control system is modeled as a switching system. Then a set of sufficient conditions for stability analysis and control synthesis are given, yielding a platoon control algorithm that guarantees string stability and zero steady‐state spacing errors. Chapter 2 revisits the problem subject to communication interruption and latency. Based on a hybrid reference model of cooperative adaptive cruise control (CACC) and adaptive cruise control (ACC), a CACC‐ACC switching control method is suggested. To ensure string stability and zero steady‐state spacing errors with a finite time, a finite‐time sliding‐mode control algorithm is derived. Chapter 3 studies the co‐design problem of platoon controller and inter‐vehicle communication topology. A unified co‐design framework is presented to jointly determine the optimal communication topology and the sampled‐data controller gains in association with the topology. The co‐design algorithm is derived based on the stability requirement and minimization of the cost function via dynamic programming. Chapter 4 studies the platoon control problem with a switching communication topology and transmission delays. The switching communication topology is described as a Markov chain, and the connected vehicular control system is modeled as a Markovian jumping system with delay. The resulting control method can guarantee exponential convergence of the tracking errors in the mean‐square sense. Chapter 5 revisits the co‐design problem of the CACC controller and event‐triggered communication mechanism. Sufficient conditions for the sampled‐data controller and the event‐triggered communication mechanism are obtained to guarantee system stability.