http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
enabling technologies and future developments
Intelligent Road Vehicles examines specific aspects of intelligent vehicles such as enabling technologies, human factors and an analysis of social and economic impacts. The book is an invaluable resource for those pursuing deeper knowledge in the intelligent vehicles field, providing readers with an idea of current and future technologies, current projects and developments and the future of intelligent vehicles. Intelligent road vehicles are becoming a challenging area of research worldwide. Apart from the final applications and systems in vehicles, there are many enabling technologies that should be introduced. Communications and automation are two key areas for future automobiles. This book benefits from collaboration on the Thematic Network on Intelligent Vehicles led by Felipe Jimenez.
Front Cover; Intelligent Vehicles; Copyright Page; Contents; List of Contributors; Preface; 1 Introduction; 1.1 Intelligent Transport Systems (ITS); 1.2 Early Initiatives; 1.2.1 Europe; 1.2.2 United States; 1.2.3 Japan; 1.3 Services; 1.3.1 Provision of Information to the User; 1.3.2 Traffic Management; 1.3.3 Freight Transportation Operation; 1.3.4 Public Transport Operation; 1.3.5 Electronic Payment; 1.3.6 Emergencies; 1.4 Intelligent Vehicles; 1.5 Book Structure; References; Further Reading; I. Enabling Technologies; 2 Environmental Perception for Intelligent Vehicles.
2.1 Vision-Based Road Information2.1.1 Environmental Variability; 2.1.2 Lane Detection; 2.1.2.1 Preprocessing; 2.1.2.2 Postprocessing; 2.1.3 Traffic Signs Recognition; 2.1.3.1 Sign Detection; 2.1.3.2 Sign Classification; 2.1.4 Commercial Systems; 2.2 Vision-Based Perception; 2.2.1 Vision-Based Object Detection and Semantic Segmentation; 2.2.2 Onboard Vision-Based Object Detection; 2.2.3 Onboard Vision-Based Semantic Segmentation; 2.2.4 Onboard Vision Based on Deep Learning; 2.3 Lidar-Based Perception; 2.3.1 Surroundings Recognition; 2.3.1.1 Obstacles Detection.
2.3.1.2 Path Boundaries Detection2.4 Sensing From the Infrastructure; 2.4.1 Autonomous Traffic Sensors; 2.4.1.1 Intrusive Sensors; 2.4.1.1.1 Magnetic Loops; 2.4.1.1.2 Pneumatic Tubes; 2.4.1.1.3 Piezoelectric Sensors; 2.4.1.1.4 Fiber Optic Sensors; 2.4.1.1.5 Geomagnetic Sensors; 2.4.1.1.6 Wireless Sensor Networks (Motes); 2.4.1.2 Nonintrusive Sensors; 2.4.1.2.1 Microwave Radars; 2.4.1.2.2 Laser Sensors (Active Infrareds); 2.4.1.2.3 Ultrasonic Sensors; 2.4.1.2.4 Passive Infrared Sensors; 2.4.1.2.5 Acoustic Sensors; 2.4.1.2.6 Video Cameras.
2.4.1.3 Summary of Strengths and Weaknesses of Autonomous Traffic Sensors2.4.2 Dependant Traffic Sensors; 2.4.2.1 Vehicle Identification by RFID (RFID Radio Frequency Identification); 2.4.2.1.1 Onboard Equipment (Tag); 2.4.2.1.2 Equipment in the Infrastructure (TRX); 2.4.2.2 Bluetooth Sensing; 2.4.3 Conclusions and Recommendations; 2.5 Data Fusion; 2.5.1 Data Fusion Levels; 2.5.1.1 Data Fusion Definition; 2.5.2 Architectures; 2.5.3 Data Fusion in Intelligent Transport Systems; 2.5.3.1 Other Approaches; References; Further Reading; 3 Vehicular Communications.
3.1 Standardization in Vehicular Communications3.1.1 Introduction; 3.1.2 The ISO CALM Framework; 3.1.2.1 The ISO CALM Communications Reference Architecture; 3.1.2.2 The ISO CALM Access Media; 3.1.2.2.1 IEEE WAVE; 3.1.2.2.2 CEN DSRC; 3.1.2.2.3 ETSI ITS G5; 3.1.2.2.4 ISO CALM M5; 3.1.2.2.5 IEEE 802.11; 3.1.2.2.6 IEEE 802.11p; 3.1.2.2.7 IEEE 802.16 WiMAX; 3.1.2.3 The ISO CALM Network Layer; 3.1.2.3.1 IETF IPv4; 3.1.2.3.2 IETF/ISO IPv6 Networking and Mobility; 3.1.2.3.3 Mobility in IPv6 Networks; 3.1.2.3.4 IEEE 1609.3 WAVE WSMP; 3.1.2.3.5 GeoNetworking.
Includes bibliographical references and index.