Control, Learning, and Optimization with Applications in Connected and Autonomous Vehicles
edited by Weinan Gao, Zhong-Ping Jiang and Andreas A. Malikopoulos
The Institution of Engineering and Technology, 2026
Cloth: 978-1-83724-160-6 | eISBN: 978-1-80705-237-9 (ePub) | eISBN: 978-1-83724-161-3 (PDF)
ABOUT THIS BOOK
Connected and autonomous vehicles (CAVs) have enormous potential to shape the future of transportation. As this complex and dynamic field grows, researchers are looking for ways to improve the efficiency and performance of CAVs. Through employing predictive modeling, machine learning, and advanced sensor fusion approaches, CAVs can anticipate and respond to hazardous situations with greater precision and speed. Control algorithms coupled with real-time data analysis enable CAVs to achieve significant reductions in energy consumption without compromising performance or safety.
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