因由車載行動網路(Vehicular Ad-hoc Network, VANET)技術車輛與車輛間（Vehicle-to-vehicle, V2V）與車輛對基礎設施（Vehicle-to-infrastructure, V2I）通信技術的出現，號控系統有新的發展空間。在近年研究中，Kartik Pandit et al.提出OAF演算法 (Pandit, Ghosal, Zhang, & Chuah, 2013)，透過即時資料的適應性號誌控制號誌系統，並計算車道中車隊大小，以決定綠燈開放順序與開放時間長度。然而，OAF之研究架構中，因幾個重要的問題點如清道損失時間、車流特性、最小綠燈限制等未被考量到，而可能造成路口績效的降低及安全議題，加上車輛分群演算法的複雜度高，達複雜度O(N!)，計算耗時，故本研究提出一改良的演算法，改進上述OAF方法的缺點，稱之為MOAF (Modified Oldest Arrival First)方法。並提出另一利用VANET技術，以窮舉方式找出即時最佳化號誌計畫之獨立路口號控演算法，稱之為TIE (Triple Iteration Enumeration)方法。
本論文應用系統模擬的方式，將所設計的模式模擬出來，並應用路口之績效評估指標車輛通過量（車輛數／單一週期）為此獨立號誌化路口進行評估。在系統績效中將本研究之模擬實驗結果，與OAF進行結果比較，另外，將Webster’s 演算法進行應用VANET的即時資訊模擬的線上即時系統，稱呼VANET-based Online – Webster’s模型(後簡稱Online – Webster’s模型)進行比較。

為了實證演算法之效能，我們針對各實驗結果，以OAF模型輸出為基線，對各項路口績效指標進行評估分析，比較結果TIE模型與MOAF模型在平均每分鐘通過路口車流量中，分別改善29.72%與29.66%。在最大等候線長度中，TIE模型平均能改善70%，而MOAF模型平均能改善40%，但兩個模型在分布VIII中都改善較少，分別從9.52%到33.33%與0%到26.09%。在平均延滯時間中，TIE模型與MOAF模型都平均能改善30%以上的平均延滯時間，其中，最多分別達154.88%與141.93%。TIE模型在平均等候線長度中，平均都能改善30%以上的平均等候線長度，最多達87.74%；而MOAF模型則平均都能改善25%以上的平均等候線長度，最多達204.70%。最後在平均碳排放量改善績效中，TIE模型能有效減少碳排放的產生比率從5.62%到62.79%；MOAF模型為減少比率10%到59.17%。

With the emerging vehicular ad-hoc network (VANET) technique, spatiotemporal coverage of traffic information collection has evolved from the minute level to the second level so that traditional adaptive traffic signal control (ATSC) strategies, based on traditional fixed and minute level vehicle detectors, may be unable to handle such large amount of real-time traffic information. Several issues are found in modern VANET-based ATSC strategies which make these works hardly applied to practical real traffic network. In this work, we take all the practical issues into consideration and propose two ATSC models including M-OAF and TIE. Experiments are designed to compare the performance of the proposed models with the related works including OAF (oldest arrival first) and Online - Webster's Model, a traditional ATSC strategies enhanced with VANET technique. Simulation results show that the overall performance of the TIE model outperforms other models in average waiting time, average queue length, and average carbon emission, where it enhance 62.79% in reducing carbon emission comparing to related works. The contribution of this work are summarized as three-fold. First, all the practical issues are considered. Second, the computing complexity of the proposed models have been largely reduced compared to related works OAF. Third, the proposed M-OAF, TIE approaches are outperformed than the related works, which indicates it can schedule better Signal Timing Plans and reduce more carbon emissions.

參考文獻
America Revealed: Nation On The Move. PBS documetary. (2012年4月18日). 擷取自 http://video.pbs.org/video/2223774770/
BangL., & Nilsson, L. E.K. (1976). Optimal control of isolated traffic signals. . In Proceedings of the International Federation of Automatic Control/International Foundation for Information Process/International Federation of Oper Research Society International Symposium: Control in Transportation Systems. Columbus, Ohio.
Barth, M., & Boriboonsomsin, K. (2009). Traffic Congestion and Greenhouse Gases. Acess, 35(Fall), pp. 2-9.
Birol, F., Kennedy, A., Hood, C., Burghgraeve, S., & Quadrelli, R. (2015). CO2 Emissions from Fuel Combustion Highlights (2015 Edition ed.). IEA Statistics.
ChangJ., & Park, G. T.H. (2013). A study on traffic signal control at signalized intersections in vehicular ad hoc networks. . Ad Hoc Networks, 11(7), 頁 2115-2124.
Dey, P., Nandal, S., & Kalyan, R. (2013). Queue discharge characteristics at signalised intersections under mixed traffic conditions. European Transport, 55(7), pp. 1-12.
EichlerS. (2007). Performance evaluation of the IEEE 802.11 p WAVE communication standard. In Vehicular Technology Conference, 2007. VTC-2007 Fall. 2007 IEEE 66th. (頁 2199-2203). Baltimore, MD, USA: IEEE.
Gartner, N. (1983). OPAC: A demand-responsive strategy for traffic signal. Transportation Research Record, 906, pp. 75-81.
Hemakumar, V., & Nazini, H. (2013). Optimized traffic signal control system at traffic intersections using VANET. International Conference on Sustainable Energy and Intelligent Systems (pp. 305-312). IET.
HenryJ., Farges, J. L., & Tuffal, J.J. (1984). The PRODYN real time traffic algorithm. In IFACIFIPIFORS conference on control in.
Highway Capacity Manual 2000. (2000). National Research, Council Washington, D.C.: Transportation Research Board (TRB).
Huang& Miller, W.X.,. (1991). A time-efficient, linear-space local similarity algorithm. . Advances in Applied Mathematics, 12(3), 頁 337-357.
Hunt, P., Roberson, D., Bretherton, R., & Winton, R. (1981). SCOOT - a traffic responsive method of coordinating signals. TRL Laboratory Report 1014.
Kartik PanditGhosal, H. Michael Zhang, and Chen-Nee ChuahDipak. (2013). Adaptive Traffic Signal Control with Vehicular Ad Hoc Network. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 62, NO. 4, 頁 1459- 1471.
Kelton, W., Sadowski, R., & Zupick, N. (2015). Simulation with Arena (6th ed ed.). McGraw-Hill.
LeeKim, Y., Kwak, Y., Zhang, J., Papasakellariou, A., Novlan, T., ... & Li, Y.J.,. (2016). LTE-advanced in 3GPP Rel-13/14: an evolution toward 5G. . IEEE Communications Magazine, 54(3), , 頁 36-42.
LeeL. C., HoC. H., & TingK. L. (1992). THE SIMULATION OF ADAPTIVE SIGNAL CONTROLS ON URBAN ARTERIAL STREETS. Managing Traffic and Transportation Conference. Amsterdam.
Li LiWen, and Danya YaoDing. (2014). A Survey of Traffic Control With Vehicular Communications. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 15, NO. 1, 頁 425-433.
LuotoBennis, M., Pirinen, P., Samarakoon, S., Horneman, K., & Latva-aho, M.P.,. (2016). System Level Performance Evaluation of LTE-V2X Network. In European Wireless 2016; 22th European Wireless Conference (頁 1-5). Oulu, Finland: VDE.
M. BesleyAkcelik, and E. ChungR. (1998). An evaluation of SCATS master isolated control. in Proc. 19th ARRB Transp. Res. Conf., (頁 1–24).
Maslekar, N., Boussedjra, M., Mouzna, J., & Labiod, H. (2011). VANET based adaptive traffic signal control. IEEE International conference on Vehicular Technology (pp. 1-5). IEEE.
Michael Li. (2009). Comments on IEEE Std P1609.3/D1.1.
Mirchandani, P., & Head, L. (2001). A real-time traffic signal control system: architecture, algorithms, and analysis. Transportation Research Part C: Emerging Technologies, 9(6), pp. 415-432.
N. HounsellLandles, R. D. Bretherton, and K. GardenerJ. (1998). project, Intelligent systems for priority at traffic signals in London: The INCOME. in Proc. 9th Int. Conf. Road Transp. Inf. Control, Number 454, (頁 90–94).
N.MASLEKARJ.MOUZNA, H.LABIODM.BOUSSEDJRA,. (2011). VANET based Adaptive Traffic Signal Control. (頁 1-5). Yokohama, Japan: IEEE.
Pandit, K., Ghosal, D., Zhang, H., & Chuah, C. (2013). Adaptive traffic signal control with vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 62(4), pp. 1459-1471.
Peterson, A., & Bergh, T. (1991). LHOVRA A traffic signal control strategy for isolated junctions. Swedish National Road Administration.
Rakha , H., Ahn, K., & Trani, A. (2004, Jan.). Development of VT-Micro model for estimating hot stabilized light duty vehicle and truck emissions. Transportation Research Part D, 9(1), pp. 49-74.
SeoLee, K. D., Yasukawa, S., Peng, Y., & Sartori, P.H.,. (2016). Lte evolution for vehicle-to-everything services. IEEE Communications Magazine, 54(6), 頁 22-28.
Shieh, J.-L., Lu, C.-Y., & Lee, W.-H. (2013). VANET-based Coordinated Signal Control in a Local Network for Minimizing CO2 Emissions and Fuel Consumption. Research Notes in Information and Service Sciences, 14, pp. 384-389.
Sims, A., & Dobinson, K. (1980). The Sydney coordinated adaptive traffic (SCAT) system philosophy and benefits. IEEE Trans. on Vehicular Technology, 29(2), pp. 130-137.
STALLARDE. OWEN AND CHARLIE M.LARRY. (‎1999). Rule-Based Approach to Real-Time Distributed Adaptive Signal Control. Transportation Research Record, VOL1683, 頁 pp. 99 - 101.
Tang, K., Ono, T., Tanaka, S., & Kuwahara, M. (2010). A proposal for the estimation of loss time of right-turn traffic at signalized intersections in Japan. the 89th Annual Meeting of the Transportation Research Board. Washington D.C.
The City of Reno Public Works Department. (2017). 擷取自 The City of Reno : http://www.reno.gov/
Tiaprasert, K., Zhang, Y., Wang, X., & Zeng, X. (2015). Queue Length Estimation Using Connected Vehicle Technology for Adaptive Signal Control. IEEE Transactions on Intelligent Transportation Systems, 16(4), pp. 2129-2140.
VincentA., & Peirce, J. R.R. (1988). 'MOVA': Traffic Responsive, Self-optimising Signal Control for Isolated Intersections (No. 70).
WangMirchandani and Fei-YuePitu. (2005). RHODES to Intelligent Transportation Systems. IEEE INTELLIGENT SYSTEMS, VOL:20, 頁 10-15.
Webster, F., & Cobbe, B. (1966). Traffic signals. London, England: Road Research Laboratory Technical Paper No. 56.
Webster.VF, & Laboratory.ResearchRoad. (1958). Traffic signal settings. London, UK: London : H.M.S.O, Road Research Laboratory, Her Majesty Stationary Office.
Younes, M., & Boukerche, A. (2016). Intelligent Traffic Light Controlling Algorithms Using Vehicular Networks. IEEE Transactions on Vehicular Technology, 65(8), pp. 5887-5899.
交通安全資訊. (104年11月4日). 擷取自 中華民國交通部臺灣區國道高速公路局: https://www.freeway.gov.tw/Publish.aspx?cnid=516&p=2230
何志宏. (2003). 獨立路口號誌時制分析與設計. 92 年度交通工程人才培訓課程.
李樑堅. (1993). 建立微觀車流模擬模式以發展交通適應性號誌控制邏輯之研究. 成功大學交通管理科學系學位博士班論文.
陳一昌、張開國、張仲杰、何志宏、邱素文、國鈞、石家豪、蔣封文、吳悅慈、莊捷媚. (2006). 都市交通號誌全動態控制邏輯模式之研究(IV)─ 網路路口實例研究. 交通部運輸研究所.
陳一昌、張開國、張仲杰、黃惠隆、黃文鑑、張景平、翁忠川、林昶禛、朱小玲. (2007). 交通號誌時制重整計畫(I)—標準作業程序建立. 交通部運輸研究所.
陸正育. (民103). 基於車載網路技術的協同式號誌控制系統用於區域路網以最佳化CO2排放與燃油消耗. 成功大學交通管理科學系學位碩士班論文.
曾惓賢、劉嘉福、李光偉、陳銘旭. (民93). 國內用路人跟車行為潛在風險性分析與前方防撞系統發展之關聯性. 九十三年道 路交通安全與執法國際研討會.
道路交通標誌標線號誌設置規則. (民104年5月14日). 道路交通標誌標線號誌設置規則.