請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8167
標題: | 使用動態視覺影像進行相對車速估測 Vehicle Relative Speed Estimation with Dynamic Vision Sensor |
作者: | Hao-Jen Hsiao 蕭皓仁 |
指導教授: | 蔡欣穆(Hsin-Mu Tsai) |
關鍵字: | 相對車速估算,動態視覺感測器,卷積神經網路, vehicle speed estimation,dynamic vision sensor,convolutional neural network, |
出版年 : | 2020 |
學位: | 碩士 |
摘要: | 自近期智慧車輛的蓬勃發展以來,主動巡航控制系統(ACC)一直都是最受歡迎的先進駕駛輔助系統(ADAS)之一。近期許多研究想利用相機及電腦視覺技術來實現ACC,主要原因是可以擴展該相機去實現車上其他視覺相關的智能功能,此外價格也比光達低廉許多。然而常規相機只有較低的時間分辨率且缺乏計算相對車速的能力,這極大的限制了系統的效能。本論文提出了一相對車速估算模型,該模型基於動態視覺感測器及卷積神經網路。使用動態視覺感測器能解決常規相機字在高速行駛下遇到的許多問題,並且能夠進行縱向的運動估算。本系統的FPS達到40Hz,超越了一般車用都卜勒雷達。實驗結果顯示,相對車速估算的平均誤差低於1.4 km/h。 Since the recent flourish development of intelligent vehicles, Adaptive Cruise Control (ACC) has always been one of the most popular Advanced Driver Assistance System (ADAS). Many recent studies want to use single-camera and computer vision technology to implement ACC. The reason is that a camera can be expanded to implement other visual intelligent functions. Also, the expense of the camera is much lower than LiDAR. However,conventional camera lacks the ability to estimate relative speed and only has a low time resolution, which greatly limits the performance of the system.This thesis presents a vehicle relative speed estimation model based on Dynamic Vision Sensor (DVS) and convolutional neural network (CNN) for Adaptive Cruise Control. Also a visual sensor, DVS is an asynchronous cam-era with high temporal resolution and overcome many problems of conventional cameras in high-speed driving conditions. The key innovation of this work is that we use visual sensors for longitudinal motion estimation. More-over, we design two novel data augmentation methods specifically for DVS streaming data. The speed estimation FPS of our system can reach 40 Hz, surpassing Doppler radar-based systems. Experimental results show that error of speed estimation is less than 1.4 km/h. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8167 |
DOI: | 10.6342/NTU202003725 |
全文授權: | 同意授權(全球公開) |
顯示於系所單位: | 資訊工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
U0001-1708202012595000.pdf | 2.82 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。