本文選題：無線傳感器網(wǎng)絡 + 交通監(jiān)控系統(tǒng)�。� 參考：《西南交通大學》2014年博士論文

【摘要】：汽車為人類的出行帶來了極大便利,但隨著汽車數(shù)量的快速增加,交通擁堵問題越來越嚴重。雖然政府不斷地修建高速公路、城市快速路,但是道路地增長速度遠低于汽車數(shù)量地增長。為了解決這個問題,政府近年來投入越來越多的資金和精力用于開發(fā)智能交通系統(tǒng),希望通過提高信息化水平和管理水平來提高道路的通行效率,緩解交通擁堵。智能交通系統(tǒng)的首要任務就是對道路道路交通情況進行實時地監(jiān)控和數(shù)據(jù)采集,然后在收集到的數(shù)據(jù)信息基礎上,及時作出高效、合理的控制決策。目前常用的交通監(jiān)測技術主要包括電磁感應線圈回路檢測、雷達檢測和圖像處理技術等,但這些技術均因受其本身或特定環(huán)境因素的限制,存在著一些不足。這些缺點主要包括：構建成本高昂、惡劣天氣識別度低、組網(wǎng)結構復雜等缺點。而無線傳感器網(wǎng)絡(Wireless Sensor Networks, WSN)作為一種全新的信息獲取和處理技術,能較好解決上述問題。WSN結合了傳感器、微機電系統(tǒng)(Micro-Electro-Mechanical System, MEMS)和網(wǎng)絡通信等技術,具有網(wǎng)絡自組織、自適應性等特點。WSN由大量傳感器節(jié)點組成,每個節(jié)點都可以收發(fā)無線電信號信息,并將這些信息在網(wǎng)絡中進行傳輸,最后將信息交給數(shù)據(jù)處理能力強的一些節(jié)點處理。由于無線傳感器網(wǎng)絡中的傳感器個體結構簡單、成本低廉,網(wǎng)絡具有自組織性等顯著優(yōu)點�？紤]將WSN技術作為新一代智能交通監(jiān)控系統(tǒng)的關鍵技術,構建基于WSN的分布式自適應交通監(jiān)控系統(tǒng),但要將無線傳感器網(wǎng)絡應用于交通監(jiān)控系統(tǒng)必須解決一系列技術問題。本論文反映的研究工作以基于WSN的分布式自適應交通監(jiān)控系統(tǒng)為對象,重點研究了傳感器網(wǎng)絡能量管理,底層結構布局及密度優(yōu)化,節(jié)點定位等問題。本論文的主要貢獻如下：(1)本文結合高速公路自身交通流量及物理上的特性,再充分對WSN路由協(xié)議及傳感器節(jié)點兩方面進行改進,提出一種針對高速公路監(jiān)控系統(tǒng)的能量管理策略——基于TTL(Timeout Threshold LEACH)的交通監(jiān)控系統(tǒng)最小能耗模型。該模型基于低功耗自適應分層路由協(xié)議(Low Energy Adaptive Clustering Hierarchy, LEACH),可以從整體上提升網(wǎng)絡的生命周期。在此基礎上,進一步對每一個傳感器節(jié)點的超時閡值(Timeout Threshold, TT)進行計算,并動態(tài)設置節(jié)點的功率可管理部件(Power Manageable Component, PMC),將空閑時間的累計值與超時閾值比較而進入到不同深度的休眠狀態(tài),達到進一步降低傳感器節(jié)點能耗的目的。上述方式中,一個是降低網(wǎng)絡整體的能量消耗,一個是降低網(wǎng)絡中單個節(jié)點的能量消耗,通過以上點面結合的方式,爭取最大程度降低高速公路交通監(jiān)控系統(tǒng)的能量消耗,提升網(wǎng)絡的生命周期。(2)通過優(yōu)化無線傳感器網(wǎng)絡中各傳感器節(jié)點的位置使得由節(jié)點組成的網(wǎng)絡的覆蓋和連通性能達到最優(yōu)。根據(jù)高速公路的物理特性,并考慮高速公路中傳感器節(jié)點(Sensor Node)的感知覆蓋和通信能力對信號采集的影響,建立面向交通信息采集的多目標約束優(yōu)化問題模型,使用幾何加權法將其轉(zhuǎn)化為單一約束優(yōu)化問題。最后采用化學反應優(yōu)化算法(Chemical Reaction Optimization, CRO)求解該問題。無線傳感器網(wǎng)絡節(jié)點合理布局使得系統(tǒng)的信號采集,后期維護擴展以及成本節(jié)省等都有較大提高。(3)在基于WSN的分布式自適應監(jiān)控系統(tǒng)中,常用DV-Hop算法來對網(wǎng)絡中的未知節(jié)點進行定位,但定位出來的未知節(jié)點精度較低,誤差較大,因此我們在原有的定位模型上,提出了一種采用粒子群優(yōu)化(Particle Swarm Optimization, PSO)和模擬退火(Simulated Annealing, SA)對DV-Hop進行改進的混合智能算法,實現(xiàn)更高的定位精度,并能大大降低未知節(jié)點的定位誤差。該算法更加適用于高速公路監(jiān)控系統(tǒng)的定位操作。(4)該文提出了基于WSN的分布式自適應高速公路交通監(jiān)控系統(tǒng)的設計方案,并結合路面能見度、交通流量等具體數(shù)據(jù)構建了車間間距監(jiān)控模型。該模型能夠利用WSN的優(yōu)勢,實時將天氣、車流量等參數(shù)信息導入系統(tǒng),計算出合適的汽車間安全行車距離,當汽車間行車距離小于安全距離時,就將通過車載廣播、車載GPS或RFID等智能設備向駕駛人員提出警示,避免交通事故和追尾的發(fā)生。本文的相關研究成果對于構建基于WSN的分布式自適應高速公路交通監(jiān)控系統(tǒng)具有參考意義和實際應用價值,特別是對提高無線傳感器網(wǎng)絡在高速公路環(huán)境下的生命周期,提高傳感器網(wǎng)絡結構布局和密度優(yōu)化,提高車輛定位精度等方面具有重要的應用價值和經(jīng)濟價值。
[Abstract]:Cars have brought great convenience to human travel, but with the rapid increase of the number of cars, traffic congestion is becoming more and more serious. Although the government has continuously built the freeway and urban expressway, the growth rate of the road is far below the number of cars. In order to solve this problem, the government has invested more and more funds in recent years. The first task of the intelligent transportation system is to monitor and collect the traffic in the road in real time. Then, on the basis of the collected data and information, the first task of the intelligent transportation system is to make the high level of the traffic in the road. The current commonly used traffic monitoring techniques include electromagnetic induction coil circuit detection, radar detection and image processing technology, but these technologies are limited by their own or specific environmental factors. These shortcomings include high cost, low weather recognition, and a group of disadvantages. Wireless Sensor Networks (WSN), as a new information acquisition and processing technology, can better solve the above problems,.WSN combined with sensors, microelectromechanical systems (Micro-Electro-Mechanical System, MEMS) and network communication technology, with network self-organization, self-adaptive and so on. The point.WSN is composed of a large number of sensor nodes. Each node can send and receive radio signal information and transmit the information in the network. Finally, the information is delivered to some nodes with strong ability of data processing. Because of the simple structure, low cost, and self-organization of the sensor in wireless sensor network, the sensor has a simple structure and low cost. Considering the WSN technology as the key technology of the new generation of intelligent traffic monitoring and control system, a distributed adaptive traffic monitoring system based on WSN is constructed, but a series of technical problems must be solved to apply the wireless sensor network to the traffic monitoring system. The research work in this paper is based on the distributed adaptive traffic based on WSN. The main contributions of this paper are as follows: (1) in this paper, the main contributions of this paper are as follows: (1) in this paper, the traffic flow and physical characteristics of the freeway are combined, and the two aspects of the WSN routing protocol and sensor nodes are improved. The energy management strategy for the expressway monitoring system - the minimum energy consumption model of the traffic monitoring system based on the TTL (Timeout Threshold LEACH). Based on the low power adaptive hierarchical routing protocol (Low Energy Adaptive Clustering Hierarchy, LEACH), the life cycle of the network can be improved on the whole. On this basis, Furthermore, the Timeout Threshold (TT) of each sensor node is calculated, and the power manageable component (Power Manageable Component, PMC) of the node is dynamically set, and the cumulative value of idle time is compared with the timeout threshold to enter the dormant state of different depths to further reduce the energy consumption of sensor nodes. Objective. One is to reduce the energy consumption of the network as a whole, one is to reduce the energy consumption of a single node in the network. Through the combination of the above points, the energy consumption of the highway traffic monitoring system is reduced to the maximum degree and the life cycle of the network is improved. (2) by optimizing the sensors in the wireless sensor network The location of the node makes the network coverage and connectivity of the network optimal. According to the physical characteristics of the expressway, and considering the impact of the sensing coverage and communication ability of the sensor node (Sensor Node) on the expressway, a multi target constrained optimization model for traffic information acquisition is established. The geometric weighting method is transformed into a single constraint optimization problem. Finally, the Chemical Reaction Optimization (CRO) is used to solve the problem. The rational layout of the wireless sensor network nodes makes the system signal acquisition, the later maintenance extension and the cost saving and so on. (3) distributed self based on WSN. In the adaptive monitoring system, the DV-Hop algorithm is used to locate the unknown nodes in the network, but the unknown nodes have low precision and large error. Therefore, we put forward a kind of Particle Swarm Optimization (PSO) and simulated annealing (Simulated Annealing, SA) to DV-Hop on the original location model. The improved hybrid intelligent algorithm can achieve higher positioning accuracy and greatly reduce the location error of the unknown nodes. The algorithm is more suitable for the positioning operation of the expressway monitoring system. (4) the design of the distributed adaptive highway traffic monitoring system based on WSN is proposed in this paper, and the traffic visibility and traffic are combined with the road traffic. This model can make use of the advantages of WSN to import parameters such as weather and traffic flow into the system in real time, and calculate the appropriate distance of vehicle safe driving. When the distance of the vehicle is less than the safe distance, it will pass through the vehicle broadcasting, the vehicle GPS or RFID and other intelligent equipment to drive. The research results of this paper have reference significance and practical application value for the construction of distributed adaptive highway traffic monitoring system based on WSN, especially to improve the life cycle of wireless sensor network in the expressway environment, and improve the sensor network node. The layout and density optimization have important application value and economic value in improving vehicle positioning accuracy.
【學位授予單位】：西南交通大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：U495;TP212.9;TN929.5

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