Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems

This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.

• Format: Hardcover
• Language: English
• ISBN: 3031280156
• ISBN13: 9783031280153
• Release Date: September 2023
• Publisher: Springer
• Length: 789 Pages
• Weight: 2.86 lbs.
• Dimensions: 1.7" x 6.1" x 9.2"