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研究生： 黃彥翔
Huang, Yen-hsiang
論文名稱： 用於特定短距離通訊之車用網路的安全訊息傳遞機制
A Safety Message Dissemination Mechanism for DSRC-based Vehicular Ad-hoc Networks
指導教授： 楊中平
Young, Chung-ping
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年： 2007
畢業學年度： 95
語文別： 英文
論文頁數： 102
中文關鍵詞： 車間通訊 、特定短距離通訊 、模擬 、廣播
外文關鍵詞： Broadcasting, Simulation, DSRC, Inter-Vehicle Communication
相關次數： 點閱：157  下載：3 
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    • 藉由車間通訊（Inter-Vehicle Communication，IVC）的技術以提升駕駛者與乘客之行車安全，將會成為未來車輛暨交通應用中關鍵的一環。而在車輛行動網路（VANETs）中採用廣播（Broadcasting）作為傳遞安全相關之訊息是一種最自然而然的方式。然而，在負載過重的車輛行動網路中廣播安全相關訊息會因為著名的隱藏終端點問題（Hidden Terminal Problem）而遭遇碰撞（Collisions）。故在這篇論文中我們基於特定短距離通訊（DSRC）的標準提出了一個安全相關訊息之散播方式的可行性研究。為了實現這個目標，我們的研究歷經以下三個階段：首先，為了更精確地描繪出未來的車用無線通訊環境，我們針對DSRC協定的實體層（Physical Layer）與媒介存取控制層（MAC Layer）進行與模擬相關的深入探討。至於第二階段的部份，為了反映出道路上車輛真實的移動模式，我們在實驗中採用了多種不同的移動模型（Mobility Model）進行模擬。而在第三階段中，我們透過NS-2的模擬將傳統的廣播協定與我們所提出的安全相關訊息之散播方式作效能上的比較。實驗結果顯示，我們針對DSRC上的安全相關訊息之散播所提出的方式確實是可行且成功的。

    Improving the safety of drivers and passengers by Inter-Vehicle Communication (IVC) plays the critical role in many future vehicle and traffic application. Broadcasting of safety-related messages is the nature approach in Vehicular Ad Hoc Networks (VANETs). However, a broadcast message will sustain collisions due to the well-known hidden terminal problem in a heavy loaded VANET. In this paper we present a feasibility study of safety-related message dissemination mechanism based on the emerging Dedicated Short Range Communications (DSRC) standard. Towards this purpose, the study goes through three phases. First, we conduct a detailed simulation study of the DSRC physical and MAC layers in order to model more accurately future wireless communications in vehicular environments. Second, we adopt various mobility models in our experiment to reflect realistic mobility patterns of vehicles on the roads. Third, we compare the performance of the traditional wireless broadcast protocol to our proposed safety message dissemination mechanism via simulation in NS-2. The experimental results show our mechanism is feasible and successful for vehicle safety messages in DSRC.

    CHAPTER 1 INTRODUCTION 1 1.1. OVERVIEW 2 1.2. BROADCAST STORM PROBLEM 3 1.2.1 Redundant Rebroadcasts 3 1.2.2 Contention 5 1.2.3 Collision 7 1.3. MOTIVATION 8 1.4. ORGANIZATION OF THIS THESIS 9 CHAPTER 2 RELATED WORK 10 2.1. RECENT RESEARCHES 10 2.1.1. Flooding 10 2.1.2. Probability Based Methods 11 2.1.3. Area Based Methods 12 2.1.4. Neighbor Knowledge Methods 13 2.1.5. Channel Access Based Methods 14 2.1.6. Antenna Based Methods 15 2.2. CURRENT ON-GOING PROJECTS 17 2.2.1 Car2Car 17 2.2.2 CarTALK 2000 18 2.2.3 FleetNet 18 2.2.4 InternetCAR Project 18 2.2.5 NOW: Network on Wheels 19 2.2.6 PReVENT 20 2.2.7 Vehicle Infrastructure Integration (VII) 20 2.2.8 Vehicle Safety Communications Project 21 2.2.9 NCTUns 22 2.2.10 NS-3 23 CHAPTER 3 BACKGROUND TECHNOLOGY 24 3.1 INTELLIGENT TRANSPORT SYSTEM 24 3.2 DEDICATED SHORT RANGE COMMUNICATIONS (DSRC) 25 3.2.1. DSRC Standard Structure 25 3.2.2. DSRC Operation 28 3.2.3. The Key Parameters of DSRC 30 3.3. THE IEEE P1609 STANDARD OVERVIEW 32 3.4. THE NETWORK SIMULATOR (NS-2) OVERVIEW 34 CHAPTER 4 THE HISTORICALLY ADAPTIVE DISSEMINATION CONTROL (HADC) MECHANISM 36 4.1. THE SCOREBOARD STRUCTURE IN HADC 36 4.2. HADC OPERATION 37 4.3. THE REPETITION THRESHOLD OF HADC 48 4.4. THE HOLDING TIME THRESHOLD OF HADC 52 CHAPTER 5 EXPERIMENTS 53 5.1. DSRC EXTENSIONS FOR NS-2 53 5.2. MOBILITY MODELS 55 5.2.1. Random Waypoint Model 55 5.2.2. Manhattan Grid Model 56 5.2.3. Freeway Model 57 5.2.4. Gauss-Markov Model 57 5.2.5. Reference Point Group Mobility (RPGM) Model 57 5.3. SIMULATION SCENARIOS 58 5.4. FIND THE BEST REPETITION THRESHOLD OF HADC 59 5.4.1. The Best Repetition Threshold in Random Waypoint Model 59 5.4.2. The Best Repetition Threshold in Manhattan Grid Model 63 5.4.3. The Best Repetition Threshold in Freeway Model 67 5.4.4. The Best Repetition Threshold in Gauss-Markov Model 72 5.4.5. The Best Repetition Threshold in Reference Point Group Mobility (RPGM) Model 76 5.5. PERFORMANCE EVALUATION 81 5.5.1. Performance Evaluation in Random Waypoint Model 81 5.5.2. Performance Evaluation in Manhattan Grid Model 83 5.5.3. Performance Evaluation in Freeway Model 85 5.5.4. Performance Evaluation in Gauss-Markov Model 87 5.5.5. Performance Evaluation in Reference Point Group Mobility (RPGM) Model 89 CHAPTER 6 CONCLUSIONS 92

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