交通運輸對于全球經(jīng)濟發(fā)展和人口流動至關重要,交通事故的發(fā)生不僅導致大量人員傷亡,還會造成巨大的經(jīng)濟損失。據(jù)世界衛(wèi)生組織報道,每年約有125萬人死于道路交通事故,上千萬人受傷,道路交通事故已經(jīng)成為全球第七大死亡原因。在美國,2012年由于交通擁堵造成的經(jīng)濟損失(包括燃油消耗和交通延誤)估計為1210億美元,預計2020年將損失1990億美元。為了解決以上問題,交通系統(tǒng)必須足夠智能以輔助駕駛員,并對潛在的交通事故進行預判。智慧交通系統(tǒng)的研究不僅可以為我們的出行帶來極大便利,提高經(jīng)濟效益,提升駕駛安全,還可以縮短出行時間、減少不必要的燃油消耗。交通運輸系統(tǒng)面臨的主要問題是駕駛安全和交通堵塞,研究人員和汽車制造商在如何減少碰撞、緩解道路交通擁堵方面已有很多研究。這些研究雖然可以解決當前面臨的一些問題,但是大多數(shù)現(xiàn)有的交通控制系統(tǒng)都存在一些不足和挑戰(zhàn),高成本、缺乏對駕駛員安全行為及其他導致安全事故因素的考慮等。高成本是目前最主要的問題,對于交通擁堵現(xiàn)象嚴重的發(fā)展中國家和大城市而言,建立通信基礎設施和交通控制系統(tǒng)將耗費大量成本。駕駛員的行為對于道路交通安全也至關重要,但大多數(shù)現(xiàn)代化系統(tǒng)都忽略了這些...

【文章頁數(shù)】：120 頁

【學位級別】：博士

【文章目錄】：
Acknowledgment
摘要
Abstract
Chapter 1. Introduction
    1.1 Vehicular Ad hoc Networks
    1.2 VANET Architecture
        1.2.1 Communication Architecture
        1.2.2 Network Stack Layers
        1.2.3 Components of VANET
    1.3 VANET Applications
        1.3.1 Information Exchanging System
        1.3.2 Intelligent Traffic Management System
        1.3.3 Entertainment applications
        1.3.4 Platooning System
    1.4 Characteristics of VANET
    1.5 Routing in VANET
        1.5.1 Proactive Routing Protocols
        1.5.2 Reactive Routing Protocols
        1.5.3 Hybrid Routing Protocol
    1.6 VANET security
    1.7 VANET Challenges and open issues
    1.8 Research Background
    1.9 Thesis Structure
Chapter 2. Literature Review
    2.1 Traffic optimization systems and Limitations
    2.2 Accident Prediction Systems and their challenges
        2.2.1 Velocity Based Approaches
        2.2.2 Traffic Density-Based Approaches
        2.2.3 Driver Fatigue Based Approaches
        2.2.4 Weather Based Approaches
    2.3 Traffic congestion pricing systems
    2.4 Research contributions
        2.4.1 Motivations and contributions of DIFTOS
        2.4.2 HMM-based accident prediction system's motivation andcontribution
        2.4.3 Motivations and contributions of T-Coin: dynamic traffic pricingsystem
    2.5 Comparative analysis
Chapter 3: DIFTOS:A Distributed Infrastructure-Free Traffic OptimizationSystem Based on Vehicular Ad Hoc Networks for Urban Environments
    3.1 Introduction
    3.2 System components and architecture
        3.2.1 DIFTOS Client
        3.2.2 DIFTOS Server
        3.2.3 Virtual Server Hierarchy
        3.2.4 Server Selection
        3.2.5 Path Request
        3.2.6 Path Reply
        3.2.7 Path Update
    3.3 System Modeling and Formulation
    3.4 Simulation
        3.4.1 Simulation details
        3.4.2 Map Extraction
        3.4.3 Network Simulation
    3.5 Performance Evaluation
        3.5.1 Baseline
        3.5.2 Metrics
        3.5.3 Evaluation Parameters
        3.5.4 Results Analysis
    3.6 Conclusions and future directions
4 Chapter 4. Accident Prediction System Based on Hidden Markov Model forVehicular Ad-hoc Network in Urban Environments
    4.1 Introduction
    4.2 Preliminaries
        4.2.1 Forward Procedure
        4.2.2 Backward procedure
    4.3 System Modeling
        4.3.1 Probability fusion
        4.3.2 Training HMM
    4.4 Simulation details
        4.4.1 Training Dataset
        4.4.2 Simulation map
        4.4.3 Model Training
        4.4.4 Weights Optimization
        4.4.5 Traffic Simulation
    4.5 Performance Evaluation
        4.5.1 Metrics
        4.5.2 Baselines
        4.5.3 Simulation Results
    4.6 Conclusions and future directions
5 Chapter 5.T-Coin: Traffic Congestion Pricing System Based on Tender andReward-Punishment for intelligent transportation in smart cities
    5.1 Introduction
    5.2 System Policies
        5.2.1 Vehicular Navigation Architecture
        5.2.2 T-Coin Balance
        5.2.3 Road Reservation Policy
        5.2.4 Reward and Punishment Policy
        5.2.5 Traffic Tender
        5.2.6 Misbehaviors Punishment
    5.3 System Model
        5.3.1 Map Modeling
        5.3.2 Traffic Flow and Travel Delay
        5.3.3 Road Reservation Matrix
        5.3.4 Traffic Quota Management
        5.3.5 Dynamic Congestion Pricing
    5.4 Performance Evaluation
        5.4.1 Baselines
        5.4.2 Performance Metrics
        5.4.3 Evolution Parameters
        5.4.4 Simulation Environment
    5.5 Results Discussion
    5.6 Conclusions
Chapter 6.Conclusion
References
作者簡歷及在學研究成果
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