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
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