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The impact of inter-vehicle communication on vehicular traffic

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ISBN: 9783866444454 Year: Pages: XVI, 160 p. DOI: 10.5445/KSP/1000013827 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:01:58
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The work addresses communication networks established over radio equipped vehicles in our everyday road traffic, so called Vehicular Ad Hoc Networks (VANETs), and discusses their impact on two major goals, namely traffic safety and traffic efficiency. For both objectives, the thesis proposes an appropriate modeling of the essential building blocks Traffic, Communication and Application and enables impact assessment studies by means of implemented simulation tools.

Inter-vehicle communications - achieving safety in a distributed wireless environment. Challenges, systems and protocols

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ISBN: 9783866441750 Year: Pages: XVI, 142 p. DOI: 10.5445/KSP/1000007058 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:01:59
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This thesis contributes to the development of inter-vehicle communications with the goal of enhancing vehicular active safety. The wireless technology IEEE 802.11p is analyzed with an extended network simulator. As a result, challenges and design criteria for vehicular communication systems are defined. Finally, strategies for channel congestion avoidance and information dissemination are proposed, constituting a robust design to cope with unreliable and saturated wireless channel conditions.

Cooperative Connected and Automated Mobility (CCAM): Technologies and Applications

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ISBN: 9783039281589 9783039281596 Year: Pages: 128 DOI: 10.3390/books978-3-03928-159-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering --- Technology (General)
Added to DOAB on : 2020-04-07 23:07:08
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Cooperative connected and automated mobility (CCAM) has the potential to reshape the transportation ecosystem in a revolutionary way. Transportation systems will be safer, more efficient and more comfortable. Cars are going to be the third living space, as passengers will have the freedom to use their car to live, work and travel. Despite the massive effort devoted, both by academia and industry, to developing connected and automated vehicles, there are still many issues to be addressed, including not only scientific and technological, but also regulatory and political issues. This book, mostly centered on the scientific and technological aspects of CCAMs, features seven articles highlighting recent advances of the state of the art in different CCAM technologies. Two papers address vehicular platooning, a key application for day-1 automated driving, other presents a scheme to improve the resource utilization of vehicular networks, while another paper addresses critical train communications, proposing an architecture based on 5G, SDN and MPTCP to provide path diversity and end-to-end redundancy. One paper describes the status of roadside deployment activities and analyzes the policies and practices of cooperative driving in the European Union. Finally, two review papers, one on congestion control techniques for VANETs and the other on fault tolerance techniques for vehicular networks, conclude the book.

Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

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ISBN: 9783039213757 9783039213764 Year: Pages: 344 DOI: 10.3390/books978-3-03921-376-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR

Keywords

Vehicle-to-X communications --- Intelligent Transport Systems --- VANET --- DSRC --- Geobroadcast --- multi-sensor --- fusion --- deep learning --- LiDAR --- camera --- ADAS --- object tracking --- kernel based MIL algorithm --- Gaussian kernel --- adaptive classifier updating --- perception in challenging conditions --- obstacle detection and classification --- dynamic path-planning algorithms --- joystick --- two-wheeled --- terrestrial vehicle --- path planning --- infinity norm --- p-norm --- kinematic control --- navigation --- actuation systems --- maneuver algorithm --- automated driving --- cooperative systems --- communications --- interface --- automated-manual transition --- driver monitoring --- visual tracking --- discriminative correlation filter bank --- occlusion --- sub-region --- global region --- autonomous vehicles --- driving decision-making model --- the emergency situations --- red light-running behaviors --- ethical and legal factors --- T-S fuzzy neural network --- road lane detection --- map generation --- driving assistance --- autonomous driving --- real-time object detection --- autonomous driving assistance system --- urban object detector --- convolutional neural networks --- machine vision --- biological vision --- deep learning --- convolutional neural network --- Gabor convolution kernel --- recurrent neural network --- enhanced learning --- autonomous vehicle --- crash injury severity prediction --- support vector machine model --- emergency decisions --- relative speed --- total vehicle mass of the front vehicle --- perception in challenging conditions --- obstacle detection and classification --- dynamic path-planning algorithms --- drowsiness detection --- smart band --- electrocardiogram (ECG) --- photoplethysmogram (PPG) --- recurrence plot (RP) --- convolutional neural network (CNN) --- squeeze-and-excitation --- residual learning --- depthwise separable convolution --- blind spot detection --- machine learning --- neural networks --- predictive --- vehicle dynamics --- electric vehicles --- FPGA --- GPU --- parallel architectures --- optimization --- panoramic image dataset --- road scene --- object detection --- deep learning --- convolutional neural network --- driverless --- autopilot --- deep leaning --- object detection --- generative adversarial nets --- image inpainting --- n/a

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