Smart Mobile In-Vehicle Systems

Next Generation Advancements
2014
ISBN: 978-1-4614-9119-4
Verlag: Springer

Buch, Englisch, 292 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 635 g

This is an edited collection by world-class experts, from diverse fields, focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. The book presents developments on road safety, in-vehicle technologies and state-of-the art systems. Includes coverage of DSP technologies in adaptive automobiles, algorithms and evaluation of in-car communication systems, driver-status monitoring and stress detection, in-vehicle dialogue systems and human-machine interfaces, challenges in video and audio processing for in-vehicle products, multi-sensor fusion for driver identification and vehicle to infrastructure wireless technologies.

Zielgruppe

Research

Autoren/Hrsg.

Schmidt, Gerhard

Hansen, John H. L.

Abut, Huseyin

Takeda, Kazuya

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Elektronische Baugruppen, Elektronische Materialien
• Technische Wissenschaften Verkehrstechnik | Transportgewerbe Fahrzeugtechnik

Inhaltsverzeichnis

Part I: Sensor and Data Fusion.- Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar.- Dense 3D Motion Field Estimation from a Moving Observer in Real-Time.- Intelligence in the Automobile of the Future.- Unmanned Ground Vehicle Otonobil: Design, Perception, and Decision Algorithms.- Part II: Speech and Audio Processing.- Car Hands-Free Testing and Optimization - An Overview.- A Wideband Automotive Hands-free System for Mobile HD Voice Services.- In-Car Communication.- Room in a Room: A Neglected Concept for Auralization.- Refinement and Temporal Interpolation of Short-Term Spectra – Theory and Applications.- Part III: Driver Distraction.- Effects of Multi-Tasking on Drivability through CAN-Bus Analysis.- Using Perceptual Evaluation to Quantify Cognitive and Visual Driver Distractions.- Part IV: Driving Behavior and User Profiling.- Evaluation Method for Safe Driving Skill Based on Driving Behavior Analysis and Situational Information at Intersections.- Pre- and Post-Accident Emotion Analysis on Driving Behaviour.- Part V: Driving Scene Analysis.- Content-Based Driving Scene Retrieval Using Driving Behavior and Environmental Driving Signals.- Driving Event Detection by Low-Complexity Analysis of Video Encoding Features.- Target Shape Estimation Using an Automotive Radar.