This book focuses on the design of a multi-criteria automated vehicle longitudinal control system as an enhancement of the adaptive cruise control system. It analyses the effects of various parameters on the average traffic speed and the traction force of the vehicles in mixed traffic from a macroscopic point of view, and also demonstrates why research and development in speed control and predictive cruise control is important. The book also summarises the main steps of the system's robust control design, from the modelling to its synthesis, and discusses both the theoretical background and the practical computation method of the control invariant sets.

The book presents the analysis and verification of the system both in a simulation environment and under real-world conditions. By including the systematic design of the predictive cruise control using road and traffic information, it shows how optimization criteria can lead to multiobjective solutions, and the advanced optimization and control design methods required. The book focuses on a particular method by which the unfavourable effect of the traffic flow consideration can be reduced. It also includes simulation examples in which the speed design is performed, while the analysis is carried out in simulation and visualization environments.

This book is a valuable reference for researchers and control engineers working on traffic control, vehicle control and control theory. It is also of interest to students and academics as it provides an overview of the strong interaction between the traffic flow and an individual vehicle cruising from both a microscopic and a macroscopic point of view.

Explains fuel-efficient vehicle cruise control Discusses the design of individual vehicles and their interaction with the traffic environment Includes the theoretical background as well as detailing simulations of real-world vehicle/traffic interaction and the results of practical experiments

Autorentext
Balázs Németh has been a senior research fellow of the Systems and Control Laboratory (SCL) in the Institute for Computer Science and Control (SZTAKI) since 2007. He received his Ph.D. degree in Transportation Sciences from Budapest University of Technology and Economics (BME) in 2013. He is an honorary associate professor of BME, and he lectures in B.Sc., M.Sc., and Ph.D. courses on control system theory and vehicle control. He has published 102 journal papers, 4 books, and 107 papers in conference proceedings. His main research areas are analysis and synthesis of autonomous vehicle control systems, energy-optimal control of road vehicles, integration of learning and control methods, and ethics of autonomous vehicle systems. Péter Gáspár received both M.Sc. and Ph.D. degrees from the Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics (BME) in 1985 and 1997, respectively, and his D.Sc. degree in Control from the Hungarian Academy of Sciences (MTA) in 2007. Since 2022 he has been a full member of the MTA. He is head of the Systems and Control Laboratory (SCL) in the Institute for Computer Science and Control (SZTAKI) and is also a full professor at the Department of Control for Transportation and Vehicle Systems, BME. He is a member of IFAC Technical Committees on both Automotive Control and Transportation Systems. He is a co-author of 4 monographs on systems and control theory and vehicle control and the co-author of 7 university textbooks. He has published 226 journal papers, 5 book chapters, and 310 papers in conference proceedings with more than 2250 citations. His research interests include linear and nonlinear systems, robust control, system identification, and machine learning methods. His research and industrial works have involved mechanical systems, vehicle structures, and vehicle dynamics and control.

Inhalt
Chapter 1. Introduction.- Part I: Predictive Cruise Control.- Chapter 2. Design of Predictive Cruise Control Using Road Information.- Chapter 3. Design of Predictive Cruise Control Using Road and Trafc Information.- Chapter 4. Design of Predictive Cruise Control for Safety Critical Vehicle Interactions.- Part II: Analysis of the Trafc ow.- Chapter 5. Relationship Between the Trafc ow and the Cruise Control From the Microscopic Point of View.- Chapter 6. Relationship Between the Trafc ow and the Cruise Control from the Macroscopic Point of View.- Part III: Control Strategies.- Chapter 7. Control Strategy of the Ramp Metering in the Mixed Trafc ow.- Chapter 8. MPC-Based Coordinated Control Design of the Ramp Metering.- Chapter 9. Data-driven Coordination Design of Trafc Control.- Chapter 10. Cruise Control Design in the Platoon System.- Chapter 11. Simulation and Validation of Predictive Cruise Control.- Appendices.- Index.