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題名 基於eTag資料流的區段道路即時交通狀況解析機制
Detection Schemes for Segmented Realtime Traffic Conditions based on eTag Data Streams作者 洪靜誼
Hung, Ching-I貢獻者 廖峻鋒
Liao, Chun-Feng
洪靜誼
Hung, Ching-I關鍵詞 電子標籤
無線射頻辨識
旅行時間
eTag
RFID
Travel time日期 2018 上傳時間 2-八月-2018 16:39:52 (UTC+8) 摘要 交通管理單位為獲得道路交通狀況，在道路上安裝車輛偵測器(Vehicle Detector,VD)蒐集交通資料，多以線圈式偵測器、微波式偵測器或影像式偵測器形式取得，但這些方式往往會有取得單點交通資料、建置成本高或維護不易等問題，故若能以經濟的方式快速布建、維護簡便又可取得精確之交通資料，一直是交通部門所關注之議題，受惠於國道高速公路計程電子收費ETC(Electronic Toll Collection)系統實施後，在臺灣的車輛因安裝電子標籤(eTag)使用率高，其eTag內含電子產品碼(Electronic Product Code,EPC)可使用無線射頻辨識(Radio Frequency Identification,RFID)技術偵測，具有唯一碼及可追蹤之特性，本研究提出一個提供即時交通資訊的自動化架構，透過布設在市區道路eTag偵測設備，蒐集通過偵測點之車輛EPC碼、車輛數、通過時間，取得旅行時間、道路平均速率等交通特性資料，這些資訊可提供給用路人參考，亦可輔助交通管理策略擬定，經實驗結果證明此方法準確且實用。
In order to analysis traffic and road conditions, the transportation of department has utilised different types of vehicle detectors(VD) on the roads to collect traffic data, such as inductive loop, microwave radars or video image processor. However, the availability of real time traffic information suffers from the spot speed data, high construction cost and maintenance difficulty issues in the traditional data collection techniques. Therefore, rapid economic installation, easy maintenance and accurate traffic information have always been the focus of the transportation sectors. Benefiting from the implementation of the Electronic Toll Collection (ETC) system on freeways, the vehicles in Taiwan due to the high usage of eTag allow the government to gather traffic information to enable efficient traffic management.A tag containing a unique Electronic Product Code (EPC) is used for tracing and identifying. This study proposes an automated scheme that provides real time traffic information. Through the deployment of eTag detectors in the urban roads, we can collect EPC codes, traffic flow volumes and time. We can get traffic characteristics such as travel time, average road speed, etc. After being collected and extracted, useful information can be distributed to the drivers on the road. These raw traffic data also play a key role in traffic engineering analysis and policy decisions. The results of the experiments prove that our proposed methods are accurate and practical.參考文獻 [1] T. Hunter, R. Herring, P. Abbeel, and A. Bayen, "Path and travel time inference from GPS probe vehicle data," NIPS Analyzing Networks and Learning with Graphs, vol. 12, no. 1, 2009. [2] R. Russel, "How does Google maps calculate your eta," Forbes, Tech. http://www. forbes. com/sites/quora/2013/07/31/how-does-google-maps-calculateyour-eta, 2013. [3] 交通部高速公路局. (2018). 交通部高速公路局ETC利用率. Available: https://www.freeway.gov.tw/UserFiles/%E6%A5%AD%E5%8B%99%E8%A1%A801010B-etc%E5%88%A9%E7%94%A8%E7%8E%87_1070503.pdf [4] P. T. Martin, Y. Feng, and X. Wang, "Detector technology evaluation," Citeseer2003. [5] 鼎漢國際工程顧問股份有限公司, "106年度臺北市運輸走廊整合道路交通與電信資訊應用計畫期末報告書," pp. 2-11, 2018. 臺北市交通管制工程處 [6] J.-S. Oh, R. Jayakrishnan, and W. Recker, "Section travel time estimation from point detection data," pp. 5-10, 2002. [7] J. You and T. J. Kim, "Development and evaluation of a hybrid travel time forecasting model," Transportation Research Part C: Emerging Technologies, vol. 8, no. 1-6, pp. 231-256, 2000. [8] F. Zheng and H. Van Zuylen, "Urban link travel time estimation based on sparse probe vehicle data," Transportation Research Part C: Emerging Technologies, vol. 31, pp. 145-157, 2013. [9] 吳佳峰, "有GPS資訊提供下之車輛旅行時間預估模式之研究," 碩士, 運輸工程與管理系, 國立交通大學, 新竹市, 2001. [10] S. Clark, "Traffic prediction using multivariate nonparametric regression," Journal of transportation engineering, vol. 129, no. 2, pp. 161-168, 2003. [11] J. Rice and E. Van Zwet, "A simple and effective method for predicting travel times on freeways," IEEE Transactions on Intelligent Transportation Systems, vol. 5, no. 3, pp. 200-207, 2004. [12] W.-H. Lin, A. Kulkarni, and P. Mirchandani, "Short-term arterial travel time prediction for advanced traveler information systems," in Intelligent Transportation Systems, 2004, vol. 8, no. 3, pp. 143-154: Taylor & Francis. [13] L. RUIMIN, G. ROSE, and M. SARVI, "Predicting travel time and its variability in the short term," in PROCEEDINGS OF THE 14TH WORLD CONGRESS ON INTELLIGENT TRANSPORT SYSTEMS (ITS), HELD BEIJING, OCTOBER 2007, 2007. [14] C.-S. Li and M.-C. Chen, "A data mining based approach for travel time prediction in freeway with non-recurrent congestion," Neurocomputing, vol. 133, pp. 74-83, 2014. [15] H. Laura and Drotleff, "The Reality of RFID," Career and Technical Education, vol. 22, no. 3, pp. 8-9, 2004. [16] J. Emigh, "RFID and the Future of Asset Protection," Access Control& Security Systems, vol. 47, no. 2, pp. 38-39, 2004. [17] GS1, "The GS1 EPCglobal Architecture Framework," p. 42, 2015. [18] G. EPCglobal, "EPC radio-frequency identity protocols generation-2 UHF RFID; specification for RFID air interface protocol for communications at 860 MHz–960 MHz," EPCglobal Inc., November, 2013. [19] S. Leaver, T. Mendelsohn, C. S. Overby, and E. H. Yuen, "Evaluating RFID middleware," RFID Journal (September 2004), 2004. [20] "The application level events (ALE) specification, version 1.1.1 Part I: Core Specification," EPCglobal Proposed Standard, 2009. [21] 交通部高速公路局. (2017). 交通部臺灣區國道高速公路局通行量正確率. Available: https://www.freeway.gov.tw/UserFiles/%E6%A5%AD%E5%8B%99%E8%A1%A801010D-%E9%80%9A%E8%A1%8C%E9%87%8F%E6%AD%A3%E7%A2%BA%E7%8E%87_1061123.pdf [22] 交通部運輸研究所, "臺灣地區先進交通管理系統(ATMS)中都市交通號誌控制邏輯標準化與系統建置標準作業程序之研究(二)─定時式/動態式控制邏輯標準化：規劃報告," 2001. [23] Y. Liu, X. Lai, and G.-L. Chang, "Detector placement strategies for freeway travel time estimation," in Intelligent Transportation Systems Conference, 2006. ITSC`06. IEEE, 2006, pp. 499-504: IEEE. [24] M. Jo, S.-H. Cha, H. Choo, and H.-H. Chen, "Prediction of RFID tag detection for a stationary carton box," in Sensing Technology, 2008. ICST 2008. 3rd International Conference on, 2008, pp. 248-253: IEEE. [25] M. Jo and H. Youn, "Intelligent recognition of RFID tag position," Electronics Letters, vol. 44, no. 4, pp. 308-310, 2008. [26] 交通部, "都市交通控制通訊協定3.1," 2006. [27] 交通部運輸研究所, "2011年臺灣公路容量手冊," 2011. [28] L. Sydanheimo, J. Nummela, L. Ukkonen, J. McVay, A. Hoorfar, and M. Kivikoski, "Characterization of passive UHF RFID tag performance," IEEE Antennas and Propagation Magazine, vol. 50, no. 3, pp. 207-212, 2008. [29] 國家通訊傳播委員會, "低功率射頻電機技術規範," pp. 26-27, 2016 描述 碩士
國立政治大學
資訊科學系碩士在職專班
104971009資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104971009 資料類型 thesis dc.contributor.advisor 廖峻鋒 zh_TW dc.contributor.advisor Liao, Chun-Feng en_US dc.contributor.author (作者) 洪靜誼 zh_TW dc.contributor.author (作者) Hung, Ching-I en_US dc.creator (作者) 洪靜誼 zh_TW dc.creator (作者) Hung, Ching-I en_US dc.date (日期) 2018 en_US dc.date.accessioned 2-八月-2018 16:39:52 (UTC+8) - dc.date.available 2-八月-2018 16:39:52 (UTC+8) - dc.date.issued (上傳時間) 2-八月-2018 16:39:52 (UTC+8) - dc.identifier (其他 識別碼) G0104971009 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/119175 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊科學系碩士在職專班 zh_TW dc.description (描述) 104971009 zh_TW dc.description.abstract (摘要) 交通管理單位為獲得道路交通狀況，在道路上安裝車輛偵測器(Vehicle Detector,VD)蒐集交通資料，多以線圈式偵測器、微波式偵測器或影像式偵測器形式取得，但這些方式往往會有取得單點交通資料、建置成本高或維護不易等問題，故若能以經濟的方式快速布建、維護簡便又可取得精確之交通資料，一直是交通部門所關注之議題，受惠於國道高速公路計程電子收費ETC(Electronic Toll Collection)系統實施後，在臺灣的車輛因安裝電子標籤(eTag)使用率高，其eTag內含電子產品碼(Electronic Product Code,EPC)可使用無線射頻辨識(Radio Frequency Identification,RFID)技術偵測，具有唯一碼及可追蹤之特性，本研究提出一個提供即時交通資訊的自動化架構，透過布設在市區道路eTag偵測設備，蒐集通過偵測點之車輛EPC碼、車輛數、通過時間，取得旅行時間、道路平均速率等交通特性資料，這些資訊可提供給用路人參考，亦可輔助交通管理策略擬定，經實驗結果證明此方法準確且實用。 zh_TW dc.description.abstract (摘要) In order to analysis traffic and road conditions, the transportation of department has utilised different types of vehicle detectors(VD) on the roads to collect traffic data, such as inductive loop, microwave radars or video image processor. However, the availability of real time traffic information suffers from the spot speed data, high construction cost and maintenance difficulty issues in the traditional data collection techniques. Therefore, rapid economic installation, easy maintenance and accurate traffic information have always been the focus of the transportation sectors. Benefiting from the implementation of the Electronic Toll Collection (ETC) system on freeways, the vehicles in Taiwan due to the high usage of eTag allow the government to gather traffic information to enable efficient traffic management.A tag containing a unique Electronic Product Code (EPC) is used for tracing and identifying. This study proposes an automated scheme that provides real time traffic information. Through the deployment of eTag detectors in the urban roads, we can collect EPC codes, traffic flow volumes and time. We can get traffic characteristics such as travel time, average road speed, etc. After being collected and extracted, useful information can be distributed to the drivers on the road. These raw traffic data also play a key role in traffic engineering analysis and policy decisions. The results of the experiments prove that our proposed methods are accurate and practical. en_US dc.description.tableofcontents 誌謝 i 摘要 ii Abstract iii 目 錄 v 表目錄 vii 圖目錄 ix 第一章 緒論 1 1.1 研究背景與動機 1 1.2 研究貢獻 3 1.3 論文架構 3 第二章 相關研究 4 2.1 固定式交通資料蒐集 4 2.2 移動式交通資料蒐集 7 2.3 旅行時間 12 第三章 技術背景 15 3.1 無線射頻辨識(RFID) 15 3.2 EPCglobal網路架構 15 3.3 標籤的分類與格式 17 3.4 middleware 18 第四章 系統架構與設計 21 4.1 偵測器現場布設規劃 23 4.1.1 eTag偵測設備 23 4.1.2 道路布設偵測設備位置 24 4.2 通訊架構與中介軟體 25 4.3 計算旅行時間 32 第五章 實驗與討論 42 5.1 單點偵測準確率 & 二點配對率 42 5.1.1 單點偵測準確率 42 5.1.2 二點配對率 43 5.2 微波式車輛偵測器資料 vs. eTag偵測器資料 50 5.3 起點旅行時間vs.迄點旅行時間 61 5.4 討論 69 第六章 結論 72 參考文獻 74 附錄一 eTag偵測器通訊協定 77 附錄二 發表著作 92 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104971009 en_US dc.subject (關鍵詞) 電子標籤 zh_TW dc.subject (關鍵詞) 無線射頻辨識 zh_TW dc.subject (關鍵詞) 旅行時間 zh_TW dc.subject (關鍵詞) eTag en_US dc.subject (關鍵詞) RFID en_US dc.subject (關鍵詞) Travel time en_US dc.title (題名) 基於eTag資料流的區段道路即時交通狀況解析機制 zh_TW dc.title (題名) Detection Schemes for Segmented Realtime Traffic Conditions based on eTag Data Streams en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1] T. Hunter, R. Herring, P. Abbeel, and A. Bayen, "Path and travel time inference from GPS probe vehicle data," NIPS Analyzing Networks and Learning with Graphs, vol. 12, no. 1, 2009. [2] R. Russel, "How does Google maps calculate your eta," Forbes, Tech. http://www. forbes. com/sites/quora/2013/07/31/how-does-google-maps-calculateyour-eta, 2013. [3] 交通部高速公路局. (2018). 交通部高速公路局ETC利用率. Available: https://www.freeway.gov.tw/UserFiles/%E6%A5%AD%E5%8B%99%E8%A1%A801010B-etc%E5%88%A9%E7%94%A8%E7%8E%87_1070503.pdf [4] P. T. Martin, Y. Feng, and X. Wang, "Detector technology evaluation," Citeseer2003. [5] 鼎漢國際工程顧問股份有限公司, "106年度臺北市運輸走廊整合道路交通與電信資訊應用計畫期末報告書," pp. 2-11, 2018. 臺北市交通管制工程處 [6] J.-S. Oh, R. Jayakrishnan, and W. Recker, "Section travel time estimation from point detection data," pp. 5-10, 2002. [7] J. You and T. J. Kim, "Development and evaluation of a hybrid travel time forecasting model," Transportation Research Part C: Emerging Technologies, vol. 8, no. 1-6, pp. 231-256, 2000. [8] F. Zheng and H. Van Zuylen, "Urban link travel time estimation based on sparse probe vehicle data," Transportation Research Part C: Emerging Technologies, vol. 31, pp. 145-157, 2013. [9] 吳佳峰, "有GPS資訊提供下之車輛旅行時間預估模式之研究," 碩士, 運輸工程與管理系, 國立交通大學, 新竹市, 2001. [10] S. Clark, "Traffic prediction using multivariate nonparametric regression," Journal of transportation engineering, vol. 129, no. 2, pp. 161-168, 2003. [11] J. Rice and E. Van Zwet, "A simple and effective method for predicting travel times on freeways," IEEE Transactions on Intelligent Transportation Systems, vol. 5, no. 3, pp. 200-207, 2004. [12] W.-H. Lin, A. Kulkarni, and P. Mirchandani, "Short-term arterial travel time prediction for advanced traveler information systems," in Intelligent Transportation Systems, 2004, vol. 8, no. 3, pp. 143-154: Taylor & Francis. [13] L. RUIMIN, G. ROSE, and M. SARVI, "Predicting travel time and its variability in the short term," in PROCEEDINGS OF THE 14TH WORLD CONGRESS ON INTELLIGENT TRANSPORT SYSTEMS (ITS), HELD BEIJING, OCTOBER 2007, 2007. [14] C.-S. Li and M.-C. Chen, "A data mining based approach for travel time prediction in freeway with non-recurrent congestion," Neurocomputing, vol. 133, pp. 74-83, 2014. [15] H. Laura and Drotleff, "The Reality of RFID," Career and Technical Education, vol. 22, no. 3, pp. 8-9, 2004. [16] J. Emigh, "RFID and the Future of Asset Protection," Access Control& Security Systems, vol. 47, no. 2, pp. 38-39, 2004. [17] GS1, "The GS1 EPCglobal Architecture Framework," p. 42, 2015. [18] G. EPCglobal, "EPC radio-frequency identity protocols generation-2 UHF RFID; specification for RFID air interface protocol for communications at 860 MHz–960 MHz," EPCglobal Inc., November, 2013. [19] S. Leaver, T. Mendelsohn, C. S. Overby, and E. H. Yuen, "Evaluating RFID middleware," RFID Journal (September 2004), 2004. [20] "The application level events (ALE) specification, version 1.1.1 Part I: Core Specification," EPCglobal Proposed Standard, 2009. [21] 交通部高速公路局. (2017). 交通部臺灣區國道高速公路局通行量正確率. Available: https://www.freeway.gov.tw/UserFiles/%E6%A5%AD%E5%8B%99%E8%A1%A801010D-%E9%80%9A%E8%A1%8C%E9%87%8F%E6%AD%A3%E7%A2%BA%E7%8E%87_1061123.pdf [22] 交通部運輸研究所, "臺灣地區先進交通管理系統(ATMS)中都市交通號誌控制邏輯標準化與系統建置標準作業程序之研究(二)─定時式/動態式控制邏輯標準化：規劃報告," 2001. [23] Y. Liu, X. Lai, and G.-L. Chang, "Detector placement strategies for freeway travel time estimation," in Intelligent Transportation Systems Conference, 2006. ITSC`06. IEEE, 2006, pp. 499-504: IEEE. [24] M. Jo, S.-H. Cha, H. Choo, and H.-H. Chen, "Prediction of RFID tag detection for a stationary carton box," in Sensing Technology, 2008. ICST 2008. 3rd International Conference on, 2008, pp. 248-253: IEEE. [25] M. Jo and H. Youn, "Intelligent recognition of RFID tag position," Electronics Letters, vol. 44, no. 4, pp. 308-310, 2008. [26] 交通部, "都市交通控制通訊協定3.1," 2006. [27] 交通部運輸研究所, "2011年臺灣公路容量手冊," 2011. [28] L. Sydanheimo, J. Nummela, L. Ukkonen, J. McVay, A. Hoorfar, and M. Kivikoski, "Characterization of passive UHF RFID tag performance," IEEE Antennas and Propagation Magazine, vol. 50, no. 3, pp. 207-212, 2008. [29] 國家通訊傳播委員會, "低功率射頻電機技術規範," pp. 26-27, 2016 zh_TW dc.identifier.doi (DOI) 10.6814/THE.NCCU.EMCS.003.2018.B02 -
