【摘要】：目前城市交通擁堵問題成了阻礙世界經(jīng)濟(jì)發(fā)展以及城市現(xiàn)代化建設(shè)的難題之一。而我國更是由于經(jīng)濟(jì)發(fā)展速度過快,導(dǎo)致城市建設(shè)與道路網(wǎng)絡(luò)構(gòu)建無法跟上國家發(fā)展的腳步,由此所造成的社會問題、環(huán)境問題尤為嚴(yán)重。實(shí)時(shí)快速的城市交通擁堵檢測,成為目前解決城市交通擁堵問題的一個(gè)主要手段。利用現(xiàn)在技術(shù)手段實(shí)時(shí)收集交通數(shù)據(jù),構(gòu)建交通擁堵檢測模型,從而檢測出城市交通擁堵的發(fā)生,為城市交通處理系統(tǒng)提供處理依據(jù),方便交通擁堵問題得到及時(shí)的解決。近年來對于城市交通擁堵檢測方案的研究發(fā)展迅速,依靠現(xiàn)代先進(jìn)的交通檢測、監(jiān)測設(shè)備,能夠快速的收集相關(guān)交通數(shù)據(jù),利用各種特征提取算法來提取交通車輛速度變化等擁堵特征,從而設(shè)計(jì)各種擁堵檢測方案,但是面對越來越多的交通原始數(shù)據(jù)以及低效的數(shù)據(jù)收集手段,僅僅的依靠車輛速度等少數(shù)交通數(shù)據(jù)特征已經(jīng)無法得到及時(shí)準(zhǔn)確的交通擁堵檢測結(jié)果。為了能夠更及時(shí)準(zhǔn)確的檢測出城市交通擁堵的發(fā)生,本文提出了基于交通流數(shù)據(jù)的城市交通擁堵檢測方案。通過對交通流數(shù)據(jù)進(jìn)行分類,提取多維擁堵特征,構(gòu)建出三層擁堵檢測模型,采用觸發(fā)式的擁堵檢測過程,減少檢測過程的時(shí)間消耗,并對擁堵程度進(jìn)行估計(jì),更準(zhǔn)確的檢測過交通擁堵的發(fā)生。同時(shí)本文還介紹了另外一種目前快速發(fā)展的城市交通擁堵檢測技術(shù)——VANET(車輛自組織網(wǎng)絡(luò)),通過對該技術(shù)的研究探索未來解決城市交通擁堵問題的方向。最后利用模擬仿真實(shí)驗(yàn)評估了兩種擁堵檢測方案的性能,并對以后城市交通擁堵檢測研究方向進(jìn)行了闡述。
[Abstract]:At present, the problem of urban traffic congestion has become one of the problems hindering the development of world economy and the construction of urban modernization. Because of the rapid economic development in China, urban construction and road network construction can not keep up with the pace of national development, resulting in social problems, environmental problems are particularly serious. Real-time and fast detection of urban traffic congestion has become a major means to solve the problem of urban traffic congestion. In order to detect the occurrence of urban traffic congestion and provide the basis for urban traffic processing system, it is convenient to solve the traffic congestion problem in time by collecting traffic data in real time and constructing a traffic congestion detection model. In recent years, the research on urban traffic congestion detection schemes has developed rapidly. Relying on modern and advanced traffic detection and monitoring equipment, it can quickly collect relevant traffic data. Various feature extraction algorithms are used to extract traffic congestion features such as vehicle speed change, so as to design a variety of congestion detection schemes, but in the face of more and more traffic raw data and inefficient data collection means, Only relying on the vehicle speed and other few traffic data features can not get a timely and accurate traffic congestion detection results. In order to detect urban traffic congestion more timely and accurately, this paper proposes a traffic congestion detection scheme based on traffic flow data. By classifying the traffic flow data, extracting the multi-dimensional congestion characteristics, constructing a three-layer congestion detection model, adopting the trigger congestion detection process, reducing the time consumption of the detection process, and estimating the congestion degree. More accurate detection of traffic jams. At the same time, this paper also introduces another rapid development of urban traffic congestion detection technology-VANET (vehicle Ad Hoc Network), through the research of this technology to explore the future direction of solving urban traffic congestion problem. Finally, the performance of two traffic congestion detection schemes is evaluated by simulation experiments, and the future research direction of urban traffic congestion detection is described.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U491

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