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State Estimation of Multi-Agent Vehicle-Road Interaction Systems (eBook)

eBook Download: PDF
2025
323 Seiten
Wiley-IEEE Press (Verlag)
978-1-394-29339-1 (ISBN)

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State Estimation of Multi-Agent Vehicle-Road Interaction Systems - Yan Wang, Guodong Yin, Chao Huang
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Up-to-date discussions of the challenges and solutions in state estimation of vehicle neighborhood systems

In State Estimation of Multi-Agent Vehicle-Road Interaction Systems, a team of distinguished researchers introduces a novel conceptual framework that defines a system comprising vehicles and local road segments within a connected vehicle (V2X) environment-referred to as the vehicle neighborhood system. Creative estimation methods for both states and parameters within this system have been proposed and potential applications of these methods have been discussed. The book places particular emphasis on estimating and analyzing the motion states of the ego vehicle and the preceding vehicle, as well as the tire road friction coefficient.

The book covers a wide range of topics in the area of vehicle neighborhood systems, including sensor technologies, data fusion, filtering algorithms, engineering applications, and practical implementations of autonomous driving systems. It also explores common challenges in state and parameter estimation for related nonlinear systems, such as sensor data loss, unknown measurement noise, and model parameter perturbations. Corresponding solutions to these issues are proposed and discussed in detail.

The book also includes:

  • A thorough introduction to ego-vehicle state estimation with sensor data loss
  • Comprehensive explorations of unknown noise and parameter perturbations in ego-vehicle state estimation
  • Practical discussions of tire-road friction coefficient estimation with parameter mismatch and data loss
  • Complete treatments of preceding vehicle state estimation

Perfect for engineers and professionals with an interest in vehicle state estimation, State Estimation of Multi-Agent Vehicle-Road Interaction Systems will also benefit academics, scientists, and graduate students in areas like robotics, control systems, and autonomous systems.

Yan Wang, PhD, is currently a Research Fellow at the Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University.

Guodong Yin, PhD, is a Professor with the School of Mechanical Engineering, Southeast University. His research is focused on vehicle dynamics and control, automated vehicles, and connected vehicles.

Chao Huang, PhD, is currently a Senior Lecturer at The University of Adelaide, Australia.


Up-to-date discussions of the challenges and solutions in state estimation of vehicle neighborhood systems In State Estimation of Multi-Agent Vehicle-Road Interaction Systems, a team of distinguished researchers introduces a novel conceptual framework that defines a system comprising vehicles and local road segments within a connected vehicle (V2X) environment referred to as the vehicle neighborhood system. Creative estimation methods for both states and parameters within this system have been proposed and potential applications of these methods have been discussed. The book places particular emphasis on estimating and analyzing the motion states of the ego vehicle and the preceding vehicle, as well as the tire road friction coefficient. The book covers a wide range of topics in the area of vehicle neighborhood systems, including sensor technologies, data fusion, filtering algorithms, engineering applications, and practical implementations of autonomous driving systems. It also explores common challenges in state and parameter estimation for related nonlinear systems, such as sensor data loss, unknown measurement noise, and model parameter perturbations. Corresponding solutions to these issues are proposed and discussed in detail. The book also includes: A thorough introduction to ego-vehicle state estimation with sensor data loss Comprehensive explorations of unknown noise and parameter perturbations in ego-vehicle state estimation Practical discussions of tire-road friction coefficient estimation with parameter mismatch and data loss Complete treatments of preceding vehicle state estimation Perfect for engineers and professionals with an interest in vehicle state estimation, State Estimation of Multi-Agent Vehicle-Road Interaction Systems will also benefit academics, scientists, and graduate students in areas like robotics, control systems, and autonomous systems.
Erscheint lt. Verlag 16.10.2025
Sprache englisch
Themenwelt Technik Elektrotechnik / Energietechnik
Schlagworte Event-triggered Estimation • fault- tolerant estimation • model-based learning estimation • sensor data loss • State Estimation • tire road friction coefficient • Vehicle Neighborhood System • vehicle state estimation
ISBN-10 1-394-29339-9 / 1394293399
ISBN-13 978-1-394-29339-1 / 9781394293391
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