Up-to-date discussions of the challenges and solutions in multi-agent vehicle-road interaction 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:
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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
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:
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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