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系統識別號 U0002-3112201915324500
中文論文名稱 智慧交通系統Krauss Model改良-考慮換車道之情形
英文論文名稱 Smart Transportation System Krauss Model Improvement - Considering Lane Changing
校院名稱 淡江大學
系所名稱(中) 資訊工程學系碩士班
系所名稱(英) Department of Computer Science and Information Engineering
學年度 108
學期 1
出版年 109
研究生中文姓名 龐婉齡
研究生英文姓名 Wan-Ling Pang
學號 606410016
學位類別 碩士
語文別 中文
口試日期 2019-12-25
論文頁數 68頁
口試委員 指導教授-洪智傑
指導教授-劉寅春
委員-邱謙松
委員-江東昇
中文關鍵字 SUMO  車輛跟車模型  KraussModel  智慧交通系統  變換車道 
英文關鍵字 SUMO  Car-Following Model  Krauss Model  Smart Transportation System  Lane Changing 
學科別分類 學科別應用科學資訊工程
中文摘要 本論文提出針對智慧交通系統所需要之車輛流量評估的跟車理論改良,LCM跟車理論,由於傳統跟車模型提出之理論只探討單車道中車輛的跟車行為,但本論文認為傳統之環境定義與實際現實環境狀況不符,因此本論文提出以傳統跟車模型之Krauss Model為基礎,加入考慮車輛變換車道的情況,來建立以運動學分析車輛行駛之行車安全的數學模型。
並且本論文將利用交通模擬軟體SUMO來驗證所提出之LCM跟車理論,模擬的分析數據可以證明車輛能夠用比Krauss Model更短的時間以及更快速度到達目的地。
英文摘要 This paper proposes a car-following model LCM. Car-following model is an important theory when observing the vehicle flow for the intelligent transportation system. The traditional car-following model only discusses the follow-up behavior of vehicles in a single lane. However, vehicles drive in a single lane is inconsistent in the actual environmental conditions. So we propose a car-following model that considers lane-changing to make the model more realistic and form a mathematical theory based on the Krauss Model. And this paper will use the traffic simulation software SUMO to verify the proposed car-following model LCM.
Therefore, this paper proposes to build a mathematical model based on the Krauss Model of the traditional car-following model and consider the vehicle lane changing situation to analyze the driving safety of the vehicle. The simulation analysis data can prove that the vehicle can reach the destination in a shorter time and faster than Krauss Model.
論文目次 第一章 緒論 1
1.1 車輛跟車理論 2
1.2 研究動機 4
1.3 本文大綱 5
第二章 前置知識與相關研究 6
2.1 Gipps Model跟車模型介紹 6
2.2 Krauss Model跟車模型介紹 9
第三章 本論文之方法LCM模型 12
3.1 模型設計方法之步驟 12
3.2 換車道情況之定義 13
3.3 LCM數學模型 14
第四章 模擬架構流程介紹與模擬結果分析 17
4.1 模擬軟體SUMO之介紹 17
4.1.1 SUMO操作簡介 19
4.1.2 TraCI介面應用之介紹 30
4.2 SUMO模擬與結果 32
4.2.1 SUMO模擬架構 32
4.2.2 SUMO模擬數據與分析 35
第五章 結論與未來展望 39
參考文獻 40
附錄一英文論文 43


圖目錄
圖 1 1單車道內之跟車行為 3
圖 1 2實際道路情況之跟車行為 3
圖 2 1 Gipps計算最小安全距離的原理 7
圖 3 1變換車道情況示意圖 13
圖 3 2 LCM變換車道計算安全距離的原理 14
圖 4 1 SUMO的交通模擬 17
圖 4 2 SUMO模擬過程示意圖 19
圖 4 3模擬分析環境圖示 20
圖 4 4模擬環境步驟1 22
圖 4 5模擬環境步驟2 22
圖 4 6模擬環境步驟3 23
圖 4 7模擬環境步驟4 24
圖 4 8模擬環境步驟5 25
圖 4 9模擬環境步驟6 28
圖 4 10 TraCI與SUMO建立連結示意圖 30
圖 4 11道路環境模擬圖 32
圖 4 12車輛模擬圖 33
圖 4 13車輛變換車道之判斷部分程式碼 34
圖 4 14 LCM數學公式的應用操作部分程式碼 34
圖 4 15車輛模擬情形1 35
圖 4 16車輛模擬情形2 36
圖 4 17車輛模擬情形3 36
圖 4 18車輛模擬情形4 37
圖 4 19平均車速散佈圖 37


表目錄
表2-1 Gipps模型參數定義 7
表2-2 Krauss模型參數定義 10
表4-1模擬道路的座標數據 21
表4-2模擬道路的座標數據 26
表4-3車輛參數設定 28
表4-4車輛屬性設定參數 29
表4-5 TraCI所提供的命令種類 31
參考文獻 [1] Wikipedia, Intelligent Transport System, https://zh.wikipedia.org/wiki/%E6%99%BA%E6%85%A7%E5%9E%8B%E9%81%8B%E8%BC%B8%E7%B3%BB%E7%B5%B1
[2] Brackstone, M., and Mcdonald, M., “Car-following: a historical review,” Transportation Research Part F: Traffic Psychology and Behavior, vol.2, pp.181-196, 1999
[3] Kanagaraj, G., Asaithambi, C.H., and Kumar, “Evaluation of Different Vehicle Following Models under Mixed Traffic Conditions,” Procedia-Social and Behavioral Sciences 104, pp.390-401, 2013, http:// www.sciencedirect.com
[4] Krauss, S., “Microscopic modeling of traffic flow: investigation of collision free vehicle dynamics,” Koln: PhD thesis, Mathematisches Institut, Universitat zu Koln, Germany: Hauptabteilung Mobilitat und Systemtechnik des DLR., 1998
[5] TraCI, SUMO Documentation, https://sumo.dlr.de/docs/TraCI.html
[6] Denos, C., Robert ,H., and Renfrey, B., “Car-Following Theory of Steady-State Traffic Flow,” Operations Research, 1959, https://doi.org/10.1287/opre.7.4.499
[7] Chandler, R. E., Herman, R., and Montroll, E. W., “Traffic dynamics: Studies in car following,” Operations Research, vol. 6, pp. 165-184, 1958
[8] Greenberg, H., “An analysis of traffic flow,” Operations Research, vol. 7, pp. 79-85, 1959
[9] Balescu, R.I., Prigogine, R., Herman, R., and Anderson, “Statistical hydrodynamics of traffic flow,” Proc. 3rd International Symp. on the Theory of Traffic Flow, pp. 72-94, 1967
[10] Hillier, J. A., “Traffic Engrg. Control”, vol. 7, pp. 569, 1966
[11] Aycin, M.F., and Benekohal, R.F., “A Linear Acceleration Car-Following Algorithm for Autonomous Intelligent Cruise Control Systems,” Proc. 5th International Conference on Applications of Advanced Technologies in Transportation Engineering, 1998
[12] Kikuchi, C., and Chakroborty, P., “Car following model based on a fuzzy inference system,” Transportation Research Record, vol. 1365, pp. 82-91, 1992
[13] Gipps, P.G., “A Behavioural Car-Following Model for Computer Simulation,” Transportation Research Part B, vol. 15, no. 2, pp. 105–111, 1981
[14] Treiber, M., Hennecke, A., and Helbing, D., “Congested traffic states in empirical observations and microscopic simulations,” Review E, vol. 62, pp. 1805-1824, 2000
[15] Krauss, S., Wagner, P., and Gawron, C., “Metastable states in a microscopic model of traffic flow,” Physic Review E, vol. 55, pp. 5597–5602, 1997
[16] Cao, B., and Yang, Z., “Car-Following Models Study Progress,” KAM Proc. 2nd International Symposium on Knowledge Acquisition and Modeling, IEEE Computer Society, Washington, D.C., 2009
[17] Fritzsche, H.-Th., “A Model for Traffic Simulation,” Traffic Engineering and Control, vol. 35, no. 5, pp. 317–321, 1994
[18] Behrisch, and Krajzewicz, “SUMO – Simulation of Urban MObility: An Overview,” SIMUL Proc. 3rd International Conference on Advances in System Simulation, ThinkMind SIMUL 2011, Barcelona, 2011,
[19] Haddouch, S., Hachimi, H., and Hmina, N., “Modeling the flow of road traffic with the SUMO simulator,” 2018 4th International Conference on Optimization and Applications (ICOA), pp. 1-5, 2018
[20] Fiore, M., Olariu, S., and Weigle, M., “Vehicular Mobility Models,” Vehicular Networks: From Theory to Practice Chapman & Hall/CRC, 2009
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