Blockchain for a Trust Network Among Intelligent Vehicles

2018 ◽  
pp. 43-68 ◽  
Author(s):  
Shiho Kim
Keyword(s):  
Intelligent Vehicles ◽  
Trust Network

Blockchain-Autonomous Driving Systems

2021 ◽  
pp. 87-114
Author(s):  
P. Lalitha Surya Kumari
Keyword(s):  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Autonomous Driving ◽  
Intelligent Vehicles ◽  
Intelligent Vehicle ◽  
Privacy And Security ◽  
Trust Network ◽  
Vehicle Communication ◽  
Blockchain Technology ◽  
Vehicle Data

Blockchain is the upcoming new information technology that could have quite a lot of significant future applications. In this chapter, the communication network for the reliable environment of intelligent vehicle systems is considered along with how the blockchain technology generates trust network among intelligent vehicles. It also discusses different factors that are effecting or motivating automotive industry, data-driven intelligent transportation system (D2ITS), structure of VANET, framework of intelligent vehicle data sharing based on blockchain used for intelligent vehicle communication and decentralized autonomous vehicles (DAV) network. It also talks about the different ways the autonomous vehicles use blockchain. Block-VN distributed architecture is discussed in detail. The different challenges of research and privacy and security of vehicular network are discussed.

A Fast Method for Defogging of Outdoor Visual Images

2019 ◽  
Vol 12 ◽  
Author(s):  
Tannistha Pal
Keyword(s):  
Intelligent Vehicles ◽  
Visual Surveillance ◽  
Qualitative Assessment ◽  
Computational Time ◽  
Data Sets ◽  
Fast Method ◽  
Time Data ◽  
Image Defogging ◽  
Clear Vision ◽  
Dark Channel

Images captured in severe atmospheric catastrophe especially in fog critically degrade the quality of an image and thereby reduces the visibility of an image which in turn affects several computer vision applications like visual surveillance detection, intelligent vehicles, remote sensing, etc. Thus acquiring clear vision is the prime requirement of any image. In the last few years, many approaches have been made towards solving this problem. In this article, a comparative analysis has been made on different existing image defogging algorithms and then a technique has been proposed for image defogging based on dark channel prior strategy. Experimental results show that the proposed method shows efficient results by significantly improving the visual effects of images in foggy weather. Also computational time of the existing techniques are much higher which has been overcame in this paper by using the proposed method. Qualitative assessment evaluation is performed on both benchmark and real time data sets for determining theefficacy of the technique used. Finally, the whole work is concluded with its relative advantages and shortcomings.

scholarly journals Estimation of Road Boundary for Intelligent Vehicles Based on DeepLabV3+ Architecture

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 121060-121075
Author(s):  
Sunanda Das ◽  
Awal Ahmed Fime ◽  
Nazmul Siddique ◽  
M. M. A. Hashem
Keyword(s):  
Intelligent Vehicles
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