【摘要】：隨著交通的飛速發(fā)展以及人們生活水平的大幅提高,車輛幾乎成為了每家每戶的必備品。然而,在車輛為我們帶來(lái)便利的同時(shí),也給交通增添了不可忽視的壓力。傳統(tǒng)的交通資源十分有限,當(dāng)面對(duì)如此飛速增長(zhǎng)的車輛數(shù)目時(shí),就不能及時(shí)高效工作,甚至造成系統(tǒng)癱瘓,由此車聯(lián)網(wǎng)應(yīng)運(yùn)而生。車聯(lián)網(wǎng)是一種特殊的無(wú)線自組織網(wǎng)絡(luò),是實(shí)現(xiàn)交通智慧化的基礎(chǔ)之一,它主要懫取車輛與車輛間,以及車輛與路邊設(shè)備間的通信模式,并承載安全控制數(shù)據(jù)與業(yè)務(wù)數(shù)據(jù)的傳輸,為駕駛者提供實(shí)時(shí)準(zhǔn)確的車況路況信息以及交通安全服務(wù)。但車聯(lián)網(wǎng)的特殊性也決定了它在通信過(guò)程中面臨的一系列挑戰(zhàn),尤其是在媒體接入控制協(xié)議(MAC)中,車輛在搶占信道時(shí)采取的退避算法,嚴(yán)重影響著信息傳輸性能。因此,本文針對(duì)車聯(lián)網(wǎng)中廣播模式下,IEEE 802.11p MAC協(xié)議的退避算法進(jìn)行研究,主要工作如下:本文分析了車聯(lián)網(wǎng)MAC協(xié)議的擴(kuò)展需求,并總結(jié)了自組織網(wǎng)絡(luò)中常用的退避算法及其缺陷,由此提出了基于改進(jìn)MARKOV模型的競(jìng)爭(zhēng)窗口調(diào)整方法。在傳統(tǒng)的MARKOV模型中引入空閑狀態(tài),使模型更加適用于車輛復(fù)雜的通信環(huán)境及場(chǎng)景,并利用車輛密度來(lái)衡量交通擁塞程度,結(jié)合平穩(wěn)分布及泰勒公式,推導(dǎo)出車輛所維護(hù)的競(jìng)爭(zhēng)窗口值及其周圍車輛密度的關(guān)系式。最終,結(jié)合IEEE 802.11p MAC協(xié)議中傳統(tǒng)的固定競(jìng)爭(zhēng)窗口值,設(shè)計(jì)出改進(jìn)的退避算法,實(shí)現(xiàn)窗口值的自適應(yīng)動(dòng)態(tài)調(diào)整,優(yōu)化了 802.11p中固定窗口值的缺陷,使車輛在搶占信道時(shí)采取更加智能準(zhǔn)確的退避方法。仿真結(jié)果表明,本方案有效地減小了廣播信息的碰撞率,并維持了較小的時(shí)延。基于車輛區(qū)別于其他通信節(jié)點(diǎn)的獨(dú)有特性,以及其多樣的通信環(huán)境,本文針對(duì)車聯(lián)網(wǎng)設(shè)計(jì)了具備更強(qiáng)自適應(yīng)性的退避方案:基于分類預(yù)測(cè)機(jī)制的退避方法。該方案首先提出分類策略,以車輛的鄰居節(jié)點(diǎn)數(shù),速度和停止時(shí)間為準(zhǔn)則,建立屬性集,對(duì)車輛狀態(tài)進(jìn)行分類,去冗余化。并引入反饋機(jī)制,使屬性集具備自適應(yīng)調(diào)整性,從而保證不同場(chǎng)景下的分類準(zhǔn)確度。然后,利用上述準(zhǔn)則,求取屬性集所對(duì)應(yīng)的綜合競(jìng)爭(zhēng)窗口值,由此生成窗口參考表。最后,利用車輛的歷史行駛狀態(tài),建立隱馬爾可夫預(yù)測(cè)機(jī)制(HMM),實(shí)現(xiàn)對(duì)車輛下一時(shí)刻競(jìng)爭(zhēng)窗口的預(yù)測(cè),從而確定退避時(shí)間。該方案充分考慮了車輛獨(dú)有的特點(diǎn)及其復(fù)雜且受限的通信環(huán)境,建立了具備自適應(yīng)調(diào)整及預(yù)測(cè)機(jī)制的退避方法,并通過(guò)仿真證明,該方案能使信息實(shí)時(shí)高效地傳輸,優(yōu)化了車聯(lián)網(wǎng)廣播模式下的性能。
[Abstract]:With the rapid development of traffic and the improvement of people's living standards, vehicles have become a must for every household. However, while the vehicle brings convenience to us, it also adds the pressure that can not be ignored to the traffic. The traditional transportation resources are very limited, when faced with such a rapid increase in the number of vehicles, it can not work in time and efficiently, or even lead to system paralysis, so the vehicle network came into being. Vehicle networking is a special wireless ad hoc network, which is one of the bases of realizing traffic intelligence. It mainly takes the communication mode between vehicle and roadside equipment, and carries the transmission of safety control data and service data. Provide drivers with real-time and accurate traffic information and traffic safety services. However, the particularity of vehicle networking also determines a series of challenges it faces in the communication process, especially in the media access control protocol (MAC), the Backoff algorithm adopted by vehicles in preempting the channel seriously affects the performance of information transmission. Therefore, this paper studies the Backoff algorithm of IEEE 802.11p MAC protocol in the broadcast mode of vehicle networking. The main work is as follows: this paper analyzes the extended requirements of MAC protocol, and summarizes the common Backoff algorithms and their defects in the Ad Hoc Network. Based on the improved MARKOV model, a competition window adjustment method is proposed. The idle state is introduced into the traditional MARKOV model, which makes the model more suitable for the complex communication environment and scene of the vehicle, and uses the vehicle density to measure the degree of traffic congestion, combined with the stationary distribution and Taylor formula. The relation between the competing window value maintained by the vehicle and the density of the surrounding vehicle is derived. Finally, combined with the traditional fixed contention window value in IEEE 802.11p MAC protocol, an improved Backoff algorithm is designed to realize the adaptive dynamic adjustment of window value, and the defect of fixed window value in 802.11p is optimized. Make the vehicle take more intelligent and accurate Backoff method when preempting the channel. Simulation results show that the scheme can effectively reduce the collision rate of broadcast information and maintain a small delay. Based on the unique characteristics of vehicle which is different from other communication nodes and its diverse communication environment, this paper designs a more adaptive Backoff scheme for vehicle networking: a Backoff method based on classification prediction mechanism. In this scheme, a classification strategy is proposed, which takes the number of neighbor nodes, speed and stopping time as criteria, establishes attribute set, classifies vehicle status and deredundancy. A feedback mechanism is introduced to make the attribute set adaptive to ensure the classification accuracy in different scenarios. Then, the comprehensive competing window value corresponding to the attribute set is obtained by using the above criteria, and the window reference table is generated. Finally, the hidden Markov prediction mechanism (HMM),) is established to predict the next competitive window of the vehicle by using the historical driving state of the vehicle, so as to determine the Backoff time. In this scheme, the unique characteristics of the vehicle and its complex and limited communication environment are fully considered, and a Backoff method with adaptive adjustment and prediction mechanism is established. The simulation results show that the scheme can transmit information in real time and efficiently. The performance of vehicle network broadcast mode is optimized.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5;U495

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 孫偉;張和生;潘成;楊軍;白U，

本文編號(hào)：2233734