Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
Overview
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.
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Details
- ISBN-13: 9783031280153
- ISBN-10: 3031280156
- Publisher: Springer
- Publish Date: September 2023
- Dimensions: 9.21 x 6.14 x 1.69 inches
- Shipping Weight: 2.86 pounds
- Page Count: 789
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