本文選題：計(jì)算機(jī)視覺 + 交通波��； 參考：《北京工業(yè)大學(xué)》2015年碩士論文

【摘要】：隨著城市汽車保有量的持續(xù)快速增長(zhǎng),城市道路交通擁堵問題日益嚴(yán)重,迫切要求提出更為合理的交通控制策略,而交通參數(shù)的準(zhǔn)確獲取是優(yōu)化交通信號(hào)控制策略的前提。因此,采用先進(jìn)信息技術(shù)準(zhǔn)確獲取交通參數(shù)對(duì)改善城市交通具有重要意義。近年來,基于機(jī)器視覺的智能交通參數(shù)檢測(cè)算法應(yīng)運(yùn)而生,應(yīng)用計(jì)算機(jī)和圖像處理技術(shù)檢測(cè)各種交通參數(shù),分析交叉口交通流特征成為研究熱點(diǎn)。尤其是在交叉口早晚高峰時(shí)段車輛排隊(duì)嚴(yán)重,采用視頻方法如何實(shí)現(xiàn)高精度的參數(shù)提取具有挑戰(zhàn)性。對(duì)此,本文針對(duì)交叉口處基于交通波檢測(cè)的交通參數(shù)獲取進(jìn)行了研究,主要研究?jī)?nèi)容包括以下幾個(gè)方面:1.提出了一種基于人工標(biāo)定的交通參數(shù)真實(shí)數(shù)據(jù)獲取方法。該方法利用VIPER智能軟件,獲取車輛每一時(shí)刻在視頻圖像中的像素坐標(biāo)。利用攝像機(jī)模型,將像素坐標(biāo)轉(zhuǎn)化為道路平面空間坐標(biāo),根據(jù)標(biāo)定車輛的時(shí)間-位置確定排隊(duì)長(zhǎng)度及停車延誤等交通參數(shù),根據(jù)所有標(biāo)定車輛的起停變化擬合出真實(shí)的交通波到停車線距離變化曲線,獲取準(zhǔn)確的交通波位置信息。2.分析了現(xiàn)有的基于視頻的典型交通波檢測(cè)方法。對(duì)基于單攝像機(jī)的復(fù)式伸縮窗算法、基于對(duì)偶像機(jī)的決策層數(shù)據(jù)融合算法及像素層數(shù)據(jù)融合算法流程進(jìn)行了分析,并將交叉口處基于人工標(biāo)定獲取的交通波位置數(shù)據(jù)與三種典型交通波檢測(cè)算法得到的數(shù)據(jù)進(jìn)行對(duì)比,通過建立評(píng)估指標(biāo)來分析各算法性能的優(yōu)劣。3.開展了基于交通波檢測(cè)獲取交通參數(shù)的研究,包括排隊(duì)長(zhǎng)度、停車延誤、波速等交通參數(shù)的提取方法。通過將各參數(shù)與停車波和起動(dòng)波建立數(shù)學(xué)關(guān)系,推導(dǎo)出相應(yīng)參數(shù)的計(jì)算方法。其中平均停車延誤的計(jì)算要根據(jù)周期內(nèi)只存在一次排隊(duì)和存在兩次排隊(duì)分別討論。4.以實(shí)驗(yàn)為基礎(chǔ),開發(fā)并完善了人工標(biāo)定數(shù)據(jù)導(dǎo)出與參數(shù)提取系統(tǒng)軟件。針對(duì)交叉口路段早晚高峰時(shí)段不同場(chǎng)景下的交通視頻,利用相應(yīng)算法獲取排隊(duì)長(zhǎng)度與停車延誤,并將計(jì)算結(jié)果與人工記錄數(shù)據(jù)進(jìn)行對(duì)比分析,驗(yàn)證基于交通波檢測(cè)算法獲取交通參數(shù)的有效性。
[Abstract]:With the continuous and rapid growth of urban car ownership, traffic congestion in urban roads is becoming more and more serious, and a more reasonable traffic control strategy is urgently required. The accurate acquisition of traffic parameters is the premise of optimizing the traffic signal control strategy. Therefore, the use of advanced information technology to accurately obtain traffic parameters can improve urban traffic. In recent years, the intelligent traffic parameter detection algorithm based on machine vision has come into being. Using computer and image processing technology to detect all kinds of traffic parameters and analyze the characteristics of intersection traffic flow has become a hot spot. Especially in the early and late peak period of the intersection, the vehicle queuing is serious and the high precision is realized by video method. The parameters extraction is challenging. In this paper, the traffic parameters acquisition based on traffic wave detection at the intersection is studied in this paper. The main contents include the following aspects: 1. a method of obtaining real data of traffic parameters based on artificial calibration is proposed. The method uses VIPER intelligent software to obtain vehicles at every moment. Pixel coordinates in the frequency image. Using the camera model, the pixel coordinates are converted to the road plane space coordinates. The traffic parameters such as the queue length and the parking delay are determined according to the time and position of the vehicle, and the true traffic wave to the distance curve of the parking line is fitted out according to the starting and stopping changes of all the calibrated vehicles, and the accurate intersection is obtained. The current video based traffic wave detection method is analyzed by.2., which is based on a single camera based complex expansion window algorithm, based on the data fusion algorithm of idols and the process of pixel layer data fusion algorithm, and the traffic wave location data obtained by artificial calibration based on the manual calibration. Three typical traffic wave detection algorithms are compared. Through the establishment of evaluation indexes, the performance of each algorithm is analyzed and the traffic parameters are obtained based on traffic wave detection, including queuing length, parking delay, wave speed and other traffic parameters. The parameters are established by the number of parameters and parking waves and starting waves. The calculation method of the corresponding parameters is derived. The calculation of average parking delay should be based on the existence of only one queue and two queues within the cycle. Based on the experiment, the software of the artificial demarcated data derivation and parameter extraction system should be developed and perfected. In the different scenes of the early and late peak periods of the intersection section, the.4. is developed and perfected. Traffic video, using the corresponding algorithm to obtain the queue length and parking delay, and compare the calculated results with the manual data, verify the effectiveness of the traffic parameters based on the traffic wave detection algorithm.
【學(xué)位授予單位】：北京工業(yè)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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本文編號(hào)：1943863