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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳柏華(Albert Y. Chen) | |
| dc.contributor.author | Yu-Hsuan Ho | en |
| dc.contributor.author | 何語萱 | zh_TW |
| dc.date.accessioned | 2022-11-25T05:33:13Z | - |
| dc.date.available | 2026-09-28 | |
| dc.date.copyright | 2021-11-08 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-09-29 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81963 | - |
| dc.description.abstract | 機車在東南亞地區是主要的交通工具之一，由於其低開銷、高機動性及停泊便利性，其持有率穩居高位。在我國，機車持有率約為小客車持有率的兩倍，為持有率最高之交通運具。近年來，電動機車逐漸興起，其於機車數量的佔比逐年升高。儘管先前已有關於內燃機機車汙染排放的研究，但對於電動機車的污染排放則知之甚少。本研究對電動機車的非尾氣排放進行分析，藉此評估與電動機車排放相關的污染物。本研究所提出的分析方法是基於電腦視覺的電動機車與內燃機機車分類和污染物環境濃度監測。我們也進一步評估了機車車隊電氣化對都市污染物濃度的影響。以電動機車全面取代內燃機機車將可能減少都市污染物總排放量中近一半的細顆粒物、近四分之一的二氧化碳和八分之一以上的一氧化碳，然而同時可能增加約30%的粗顆粒物和近四分之一的PM1.0。有鑑於道路揚塵為粗顆粒物的主要排放源，本研究建議對電動機車引起的道路揚塵汙染作進一步調查。這項研究可應用於交通相關排放之個人暴露及健康危害評估。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-25T05:33:13Z (GMT). No. of bitstreams: 1 U0001-2709202117174800.pdf: 2631596 bytes, checksum: 4f8f84b0ee2f63e5f5b0469cae74d5df (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 口試委員審定書 # 誌謝 i 中文摘要 iii ABSTRACT iv CONTENTS v LIST OF FIGURES viii LIST OF TABLES x Chapter 1 Introduction 1 1.1. Background and Motivation 1 1.2. Objective 3 1.3. Research Flowchart 3 1.4. Structure of the Study 4 Chapter 2 Literature Review 6 2.1. Emissions from Electric Vehicles 6 2.2. Vehicle Emission Measurement 7 2.3. Traffic Data Collection 8 2.4. Fine-Grained Vehicle Classification 9 2.5. Summary 10 Chapter 3 Methodology 11 3.1. Traffic Data Extraction 11 3.1.1. Motorcycle Powered Type Classifier Construction 11 3.1.2. Vehicle Counting by Categories 14 3.2. Data Collection 15 3.3. Emission Analysis 18 3.3.1. EM Contribution Analysis 18 3.3.2. Emission Reduction through Fleet Electrification 20 Chapter 4 Results 22 4.1. Data Description 22 4.2. Motorcycle Classification 23 4.2.1. Evaluation Indicators for Classification 23 4.2.2. Experimental Results of Motorcycle Classification 24 4.3. Vehicle Counting 26 4.4. EM Contribution Analysis 28 4.4.1. Overview of Vehicle Flow and Pollutant Concentration 29 4.4.2. Time Resolution Comparison 30 4.4.3. Contribution Separation for EMs and ICMs 33 4.4.4. Wind Direction Analysis 38 4.5. Emission Reduction through Fleet Electrification 40 Chapter 5 Discussion 42 5.1. Contribution 42 5.2. Limitations 42 5.3. Future Works 43 Chapter 6 Conclusions 45 Appendix A Motorcycle Average Body Weight 46 REFERENCES 47 | |
| dc.language.iso | en | |
| dc.subject | 車隊電氣化 | zh_TW |
| dc.subject | 電動機車 | zh_TW |
| dc.subject | 非尾氣排放 | zh_TW |
| dc.subject | 機器學習 | zh_TW |
| dc.subject | 深度學習 | zh_TW |
| dc.subject | 機車分類 | zh_TW |
| dc.subject | 交通影像資料 | zh_TW |
| dc.subject | electric two-wheeler | en |
| dc.subject | fleet electrification | en |
| dc.subject | traffic video data | en |
| dc.subject | motorcycle classification | en |
| dc.subject | deep learning | en |
| dc.subject | machine learning | en |
| dc.subject | non-exhaust emission | en |
| dc.title | 基於電腦視覺機車分類之電動機車污染排放分析 | zh_TW |
| dc.title | Electric Motorcycle Emission Analysis through Computer Vision-Based Motorcycle Classification | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.author-orcid | 0000-0002-3046-8208 | |
| dc.contributor.oralexamcommittee | 陳柏翰(Hsin-Tsai Liu),蕭大智(Chih-Yang Tseng),許聿廷 | |
| dc.subject.keyword | 電動機車,非尾氣排放,機器學習,深度學習,機車分類,交通影像資料,車隊電氣化, | zh_TW |
| dc.subject.keyword | electric two-wheeler,non-exhaust emission,machine learning,deep learning,motorcycle classification,traffic video data,fleet electrification, | en |
| dc.relation.page | 55 | |
| dc.identifier.doi | 10.6342/NTU202103404 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-09-30 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
| dc.date.embargo-lift | 2026-09-28 | - |
| 顯示於系所單位： | 土木工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-2709202117174800.pdf 未授權公開取用 | 2.57 MB | Adobe PDF | 檢視/開啟 |
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