本文選題：交通狀態(tài)判別　切入點(diǎn)：射頻識(shí)別技術(shù)(RFID)　出處：《東南大學(xué)》2015年碩士論文

【摘要】：實(shí)時(shí)、準(zhǔn)確的交通狀態(tài)判別是交通管理、交通誘導(dǎo)和交通控制實(shí)現(xiàn)的前提和基礎(chǔ)。城市交通狀態(tài)的判別,必須依賴于交通信息采集技術(shù)和數(shù)據(jù)處理技術(shù)的發(fā)展�；谏漕l識(shí)別技術(shù)(RFID, Radio Frequency Identification Technology)和視頻檢測(cè)技術(shù)的綜合交通數(shù)據(jù)采集可以獲得地點(diǎn)速度和路段行程時(shí)間,基于上述數(shù)據(jù),本文城市道路交通狀態(tài)判別方法進(jìn)行研究,主要研究?jī)?nèi)容如下。首先,在進(jìn)行交通狀態(tài)判別文獻(xiàn)研究的基礎(chǔ)上,根據(jù)基于RFID技術(shù)的交通數(shù)據(jù)采集原理和特點(diǎn),提出了通過(guò)建立基站網(wǎng)絡(luò)、匹配起終點(diǎn)基站過(guò)車數(shù)據(jù)和數(shù)據(jù)匯集得到平均行程時(shí)間的數(shù)據(jù)處理方法；介紹了基于視頻檢測(cè)技術(shù)的交通數(shù)據(jù)采集原理和根據(jù)采集到的原始數(shù)據(jù)獲得平均地點(diǎn)速度的方法。并將交通狀態(tài)劃分為暢通、緩行和擁堵三種狀態(tài),研究了通過(guò)多人觀看各基站的實(shí)時(shí)視頻獲得道路上實(shí)際交通狀態(tài)的方法。其次,論文選擇了特定的城市路網(wǎng),包括43個(gè)基站,建立了61個(gè)基站對(duì),采集了6個(gè)月的RFID數(shù)據(jù),進(jìn)行行程時(shí)間的計(jì)算,并對(duì)行程時(shí)間進(jìn)行了多方面的分析,結(jié)果表明,基于RFID技術(shù)獲得的行程時(shí)間數(shù)據(jù)可以很好的反映交通運(yùn)行情況,可作為交通狀態(tài)判別指標(biāo)。再次,研究了以視頻采集技術(shù)獲得的平均地點(diǎn)速度為指標(biāo),結(jié)合實(shí)際交通狀態(tài),考慮到不同基站的具體情況,確定各基站的交通狀態(tài)判別閡值的方法,并以南京市100個(gè)基站為實(shí)例對(duì)判別效果進(jìn)行評(píng)價(jià)。最后,提出了以基于視頻技術(shù)獲取的起點(diǎn)基站平均地點(diǎn)速度和終點(diǎn)基站平均地點(diǎn)速度以及基于RFID技術(shù)獲取的基站對(duì)平均行程時(shí)間為指標(biāo),基于模糊評(píng)判的交通狀態(tài)判別方法,并以南京市某基站對(duì)為實(shí)例,將交通狀態(tài)判別結(jié)果與實(shí)際交通狀態(tài)進(jìn)行對(duì)比,評(píng)價(jià)判別效果。將綜合交通數(shù)據(jù)采集技術(shù)應(yīng)用于交通狀態(tài)判別是智能交通重要發(fā)展方向之一,在本文的研究基礎(chǔ)上,對(duì)未來(lái)的研究方向進(jìn)行了展望。
[Abstract]:Real-time and accurate identification of traffic state is the premise and foundation of traffic management, traffic guidance and traffic control. It must depend on the development of traffic information acquisition technology and data processing technology. The integrated traffic data acquisition based on RFID (Radio Frequency Identification Technology) and video detection technology can obtain the location speed and section travel time, based on the above data, The main contents of this paper are as follows: firstly, based on the research of traffic status discrimination literature, according to the principle and characteristics of traffic data collection based on RFID technology, A data processing method is proposed to get the average travel time by setting up the base station network and matching the traffic passing data and data collection of the terminal base station. This paper introduces the principle of traffic data acquisition based on video detection technology and the method of getting average location speed according to the original data collected. The traffic state is divided into three states: smooth, slow and congested. This paper studies the method of obtaining the actual traffic state on the road by watching the real-time video of each base station by many people. Secondly, the paper selects a specific urban network, including 43 base stations, establishes 61 base station pairs, and collects RFID data for 6 months. The results show that the travel time data based on RFID technology can well reflect the traffic situation, and can be used as a traffic state discrimination index. This paper studies the method of determining the threshold value of traffic state of each base station according to the actual traffic state and considering the specific conditions of different base stations, taking the average site speed obtained by video capture technology as the index, and considering the specific conditions of different base stations. And take 100 base stations in Nanjing as an example to evaluate the discriminant effect. Finally, Based on the average location speed of the base station and the average location speed of the terminal base station obtained by video technology and the average travel time of the base station acquired by RFID technology, the traffic state discrimination method based on fuzzy evaluation is proposed. Taking a base station pair in Nanjing as an example, the result of traffic condition discrimination is compared with the actual traffic state, and the discriminant effect is evaluated. It is one of the important development directions of intelligent transportation to apply comprehensive traffic data acquisition technology to traffic condition discrimination. Based on the research in this paper, the future research direction is prospected.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491

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