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研究生:賴岳廷
研究生(外文):Lai, Yueh-Ting
論文名稱:一個使用手機網路資料預估交通路況的演算法系統
論文名稱(外文):A Traffic Estimation Algorithm Using Cellular Network Data
指導教授:張明峰張明峰引用關係
指導教授(外文):Chang, Ming-Feng
學位類別:碩士
校院名稱:國立交通大學
系所名稱:網路工程研究所
學門:教育學門
學類:教育科技學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:英文
論文頁數:37
中文關鍵詞:手機網路交通路況
外文關鍵詞:Traffic Estimation AlgorithmCellular Network
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即時交通資訊服務系統的建置屬於智慧型運輸系(Intelligent Transportation System, ITS)重要的一環,對於用路人而言,獲得完整且充足的交通資訊,不論是行前路況資訊以及行進中的路況資訊,大眾運輸轉乘資訊等等,都能提供用路人在不同路徑以及運具的選擇上,具有更加的彈性。
近年來,隨著科技的發展,手機已經廣泛為大眾所使用,有鑑於此,我們將利用手機的換手(Handover)行為,求出道路中行進手機換手位置,並利用無線電信網路追蹤使用者手機位置的方式,產生即時道路交通路況資訊。這個機制不需要花費龐大的經費來架設及維護道路上的車輛偵測裝置(Stationary Vehicle Detector (SVD).)。而且手機幾乎是無所不在的,因此我們以追蹤手機位置所得到的交通資訊是非常即時且全面的。不過在研究當中,我們發現在擁塞的交通路況下,手機使用者因為移動的限制造成過少甚至沒有換手的行為發生,以至於此種機制在擁塞的交通條件下無法準確的評估交通路況。因此我提出了利用手機來電(Call Arrival)與掛斷(Call Complete)的行為,配合車輛偵測裝置的歷史資料來預測交通密度。結合了這兩者的機制,設計出一個能利用電信業者網路端的手機資訊來評估完整交通路況的方法,來達到對於擁塞的交通狀況更準確的預測。

The construction of real-time traffic information service is an important part of Intelligent Transportation System (ITS). For a road user, knowing real-time traffic information would help him in choosing better roads avoid congestion areas. ITS has become more and more popular in recent years. Traffic monitoring based on cellular network data can be more cost-effective, traditional approaches, such as roadside sensors, because no field installation or maintenance is needed. Double handover events from the Cellular Floating Vehicle Data (CFVD) can be used to estimate traffic speed. However, when the traffic is congested, due to the slow movements of the traffic, there could be very double handover events and thus very few effective speed reports of CFVD. In this paper, we propose a novel algorithm that studies the relationship between call arrival rate, call complete rate and the traffic density to estimate the traffic conditions. In addition, we combine this mechanism with the CFVD to estimate the traffic speed, especially in the condition of traffic congestion, with more accuracy and real-timeliness. Computer simulations have also been conducted to evaluate the effectiveness of our algorithm.
Contents
摘要 i
Abstract ii
誌謝 iii
List of Figures vi
Chpater 1 Introduction 1
1.1 Motivation 1
1.2 Traffic Information 1
1.3 Objective 3
1.4 Summary 4
Chpater 2 Related Works 5
2.1 The Architecture of GSM and UMTS 5
2.2 Handover Concept 6
2.3 Speed and Travel Time 8
2.4 Traffic Flow 9
2.5 Accidents 10
2.6 Summary 11
Chpater 3 System Design and Algorithms 12
3.1 Speed Estimation by Handover Events 12
3.2 TMS, SMS and Three-phase Traffic theory 13
3.3 The Basic Idea of Our Algorithms 15
3.4 The estimation of N 16
3.5 Traffic State Determination Algorithm 17
3.6 Correction from SMS to TMS 19
3.7 Vehicle Speed Estimation from N 22
3.8 Our System design and Algorithms 24
Chpater 4 Simulation Result and Performance 26
4.1 Simulation Environment 26
4.2 Simulation Results 28
Chpater 5 Conclusion and Future Work 34
References 35


References
[1] Martin, P. T., Feng, Y., and Wang, X., 2003. Detector technology evaluation. Department of Civil Environmental Engineering, University of Utah-Traffic Lab, Salt Lake City, UT.
[2] Leo, G.D., Pietrosanto, A., Sommella, P., 2009. Metrological performance of traffic detection systems. IEEE Transactions on Instrumentation and Measurement, Vol. 58, No. 9, pp. 3199-3206.
[3] Logghe, S., Maerivoet, S., 2007. Validation of travel times based on cellular floating vehicle data. Proceedings of the 6th European Congress and Exhibition on Intelligent Transportation Systems, Aalborg, Denmark.
[4] Bar-Gera, H., 2007, Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: A case study from Israel. Transportation Research Part C, No. 15, pp. 380-391.
[5] Caceres, N., Wideberg, J.P., Benitez, F.G., 2008. Review of traffic data estimations extracted from cellular networks. IET Intelligent Transport Systems, Vol. 2, No. 3, pp. 179-192.
[6] Fontaine, M.D., Smith, B.L., 2005. Probe-based traffic monitoring systems with wireless location technology: an investigation of the relationship between system design and effectiveness. Transportation Research Record: Journal of the Transportation Research Board, No. 1925, pp. 3-11.
[7] Gundlegard, D., Karlsson, J.M., 2009, Handover location accuracy for travel time estimation in GSM and UMTS. IET Intelligent Transport Systems, Vol. 3, No. 1, pp. 87-94.
[8] Ygnace, J., Drane, C., Yim, Y.B. de Lacvivier, R., 2000. Travel time estimation on the San-Francisco bay area network using cellular phones as probes. University of California, Berkeley, PATH Working Paper UCB-ITS-PWP-2000-18.
[9] Thiessenhusen K.U., Schafer R.P., Lang T., 2003. Traffic data from cell phones: a comparison with loops and probe vehicle data. Institute of Transport Research German Aerospace Center, Germany.
[10] Danilo Valerio, “Road Traffic Information from Cellular Network Signaling”, Technical Report, FTW-TR-2009-003, 2009.
[11] Hesham Rakha and Wang Zhang, Estimating Traffic Stream Space-Mean Speed And Reliability From Dual And Single Loop Detectors, TRB Paper: 05-0850
[12] Soriguera, F. ,Robuste, F., Estimation of traffic stream space mean speed from time aggregations of double loop detector data, Center for Innovation in Transport, Technical University of Catalonia, Jordi Girona 29, 2-A, 08034 Barcelona, Spain
[13] Kerner, B. S., Three-phase Traffic Theory and Highway Capacity[J]. Physica A:Statistical Mechanics and Its Applications, 2004,333:379-400


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