Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
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Beschreibung
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.
- The book describes state-of-the-art solutions to design secure, robust, and time-critical automotive systems;
- Various approaches are discussed that will impact the design of emerging autonomous vehicle systems;
- The content is relevant to researchers and industry practitioners interested in future automotive platforms.
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.
The book describes state-of-the-art solutions to design, secure, robust, and time critical automotive systems Various approaches are discussed that will impact the design of the emerging autonomous vehicle systems The content is relevant to researchers and industry practioners interested in future automotive platforms
Autor*in
Vipin Kumar Kukkala
Themen in »Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems«
Automotive embedded systems Machine learning Intrusion detection systems Reliable automotive networks Automotive cybersecurity Automotive Scheduling