scholarly journals Vision-Based Two-Factor Authentication & Localization Scheme for Autonomous Vehicles

2021 ◽  
Author(s):  
Anas Alsoliman ◽  
Marco Levorato ◽  
Qi Alfred Chen
Keyword(s):  
Autonomous Vehicles ◽  
Localization Scheme

scholarly journals Efficient Object Localization Scheme Based on Vanishing Line in Road Image for Autonomous Vehicles

2021 ◽  
Vol 09 (09) ◽  
pp. 85-97
Author(s):  
Bongkyo Moon ◽  
Jiwon Choi ◽  
Juehyun Lee ◽  
Minyoung Lee
Keyword(s):  
Autonomous Vehicles ◽  
Object Localization ◽  
Localization Scheme ◽  
Vanishing Line

scholarly journals A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Md. Tanvir Hossan ◽  
Mostafa Zaman Chowdhury ◽  
Moh. Khalid Hasan ◽  
Md. Shahjalal ◽  
Trang Nguyen ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Image Sensor ◽  
Vehicle Localization ◽  
The Road ◽  
Localization Scheme ◽  
Image Area ◽  
Potential Benefits ◽  
On The Road ◽  
Vehicle Positioning ◽  
Optical Camera Communication

The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories: host vehicles (HVs) are the ones used to estimate other vehicles’ positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme.

Rural Positioning Challenges for Connected and Autonomous Vehicles

2019 ◽  
Author(s):  
Joseph G. Walters ◽  
Xiaolin Meng ◽  
Chang Xu ◽  
Hao (Julia) Jing ◽  
Stuart Marsh
Keyword(s):  
Autonomous Vehicles

An Open Multi-Sensor Fusion Toolbox for Autonomous Vehicles

2020 ◽  
Vol E103.A (1) ◽  
pp. 252-264
Author(s):  
Abraham MONRROY CANO ◽  
Eijiro TAKEUCHI ◽  
Shinpei KATO ◽  
Masato EDAHIRO
Keyword(s):  
Sensor Fusion ◽  
Autonomous Vehicles

Fundamental Imaging System Analysis for Autonomous Vehicles

2018 ◽  
Vol 2018 (17) ◽  
pp. 105-1-105-10 ◽  
Author(s):  
Robin Jenkin ◽  
Paul Kane
Keyword(s):  
Autonomous Vehicles ◽  
System Analysis ◽  
Imaging System

Autonomous vehicles and freight traffic: towards better efficiency of road, rail or urban logistics?

2018 ◽  
Vol 58 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Péter Bucsky
Keyword(s):  
Autonomous Vehicles ◽  
Road Transport ◽  
Transport Sector ◽  
Future Directions ◽  
Car Industry ◽  
Level Of Automation ◽  
Current State ◽  
Freight Traffic ◽  
Levels Of Automation ◽  
Private Car

Abstract The freight transport sector is a low profit and high competition business and therefore has less ability to invest in research and development in the field of autonomous vehicles (AV) than the private car industry. There are already different levels of automation technologies in the transport industry, but most of these are serving niche demands and answers have yet to be found about whether it would be worthwhile to industrialise these technologies. New innovations from different fields are constantly changing the freight traffic industry but these are less disruptive than on other markets. The aim of this article is to show the current state of development of freight traffic with regards to AVs and analyse which future directions of development might be viable. The level of automation is very different in the case of different transport modes and most probably the technology will favour road transport over other, less environmentally harmful traffic modes.

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