Safe, Autonomous and Intelligent Vehicles

This book covers the start-of-the-art research and development for the emerging area of autonomous and intelligent systems. In particular, the authors emphasize design and validation methodologies to address the grand challenges related to safety. This book offers a holistic view of a broad range of...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Yu, Huafeng (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Li, Xin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Murray, Richard M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Ramesh, S. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Tomlin, Claire J. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Unmanned System Technologies,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Statistical Validation of In-Vehicle Machine Learning Systems
  • Cyberattack-Resilient Hybrid Switching Controller Design with Application to Unmanned Aircraft System
  • Control and Safety of Autonomous Vehicles with Learning-Enabled Components
  • AdaStress: Adaptive Stress Testing and Interpretable Analysis of Safety-Critical Systems
  • Provably-correct control synthesis for vehicle safety systems
  • Reachable Set Estimation and Verification for Neural Network Models of Nonlinear Dynamic Systems
  • Adaptation of Human Licensing Examinations to the Certification of Autonomous Systems
  • Model-based Software Synthesis for Safety-critical Cyber-Physical Systems
  • Compositional Verification for Autonomous Systems with Deep Learning Components
  • Index.