Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions Development, Testing and Verification /

This book describes different methods that are relevant to the development and testing of control algorithms for advanced driver assistance systems (ADAS) and automated driving functions (ADF). These control algorithms need to respond safely, reliably and optimally in varying operating conditions. A...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Waschl, Harald (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Kolmanovsky, Ilya (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Willems, Frank (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:Lecture Notes in Control and Information Sciences, 476
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Chapter 1. Introduction - Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions: Development, Testing and Verification
  • Chapter 2. Cooperation and the Role of Autonomy in Automated Driving
  • Chapter 3. Robust, Real-world Emissions by Integrated ADF and Powertrain Control Development
  • Chapter 4. Gaining Knowledge on Automated Driving's Safety - The risk-free VAAFO Tool
  • Chapter 5. Statistical Model Checking for Scenario-based Verification of ADAS
  • Chapter 6. Game Theory Based Traffic Modeling for Calibration of Automated Driving Algorithms
  • Chapter 7. A Virtual Development and Evaluation Framework for ADAS - Case Study of a P-ACC in a Connected Environment
  • Chapter 8. A Vehicle-in-the-Loop Emulation Platform for Demonstrating Intelligent Transportation Systems
  • Chapter 9. Virtual Concept Development on the Example of a Motorway Chauffeur
  • Chapter 10. Automation of Road Intersections Using Distributed Model Predictive Control
  • Chapter 11. MPDM: Multi-policy Decision-making from Autonomous Driving to Social Robot Navigation.