Enhancement and Application of Image Signal Identification in Vehicle-to-vehicle Visible Light Communication

碩士 === 國立臺灣大學 === 光電工程學研究所 === 105 === Artificial Intelligence (A.I.) and technologies of machine learning had made significant success in recent years. Many of things that are known as “human-operating-only” can be done well by A.I. Although self-driving cars are not widespread now, it’s can be ant...

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Bibliographic Details
Main Authors: Yuan-Chiao Cheng, 鄭元僑
Other Authors: 黃定洧
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/qb4v89
Description
Summary:碩士 === 國立臺灣大學 === 光電工程學研究所 === 105 === Artificial Intelligence (A.I.) and technologies of machine learning had made significant success in recent years. Many of things that are known as “human-operating-only” can be done well by A.I. Although self-driving cars are not widespread now, it’s can be anticipated that self-driving will become more popular as the technology is improved in the future. Vehicle-to-vehicle (V2V) communication is one of the important parts of self-driving. The positions and velocities of nearby cars can be detected by V2V communication, and the information can be further used to prevent collisions. Visible light communication (VLC) has high potential in this field. One of the reasons is that most of cars are using light-emitting-diodes (LEDs) for illumination and LEDs are easily modulated and have high efficiency, which is a perfect transmitter for VLC. The other reason is that visible light can be blocked easily and has high directivity. So that only nearby signals generated in proper orientations are detected, which is an important benefit in V2V communication. In this thesis, an Arduino board was used to modulate arrays of LEDs, and use smart phone camera as the receiver to build a VLC system. This device is used to simulate the actual situation of VLC between the tail-light of a car and a dash cam. In this thesis, rolling-shutter effect and image processing are used to identify difference between normal light source and the modulated tail-light of car. After this, boundary detection is used to decode message and estimate the distance between cars. For image processing, adaptive the histogram equalization and the two-dimensional convolution are used to strengthen the ability of the system to identifying modulated tail-light. On-off keying is used for modulation, and run-length limited (RLL) coding prevents too many continuous zeros affecting illumination and decoding signal. In the end, limited by the frame rate of camera, this device can only send 16 bits per second, which is designed to transmit velocity information of car.