本文選題：輔助駕駛系統(tǒng)　切入點(diǎn)：車輛檢測　出處：《浙江大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,隨著汽車保有量的增加,交通事故成為一個不得不重視的話題。汽車輔助駕駛系統(tǒng)(ADAS),特別是車輛防碰撞預(yù)警系統(tǒng)和車道保持輔助系統(tǒng)也變得越來越重要。其中前車檢測和車距測量是車輛防碰撞預(yù)警系統(tǒng)的關(guān)鍵模塊。在前車檢測系統(tǒng)中,常見的傳感器有高頻雷達(dá)(毫米波)、超聲波、紅外激光雷達(dá),攝像頭等,每種傳感器適應(yīng)的場景不同,想要適應(yīng)多種場景,汽車廠商和輔助駕駛系統(tǒng)提供商一般會融合多種傳感器收集到的信息進(jìn)行決策。由于基于視覺的前車檢測系統(tǒng)成本低,信息豐富,且近年來計算機(jī)視覺領(lǐng)域的高速發(fā)展為其提供了技術(shù)基礎(chǔ),所以受到了越來越多相關(guān)領(lǐng)域研究人員的重視�；谟嬎銠C(jī)視覺的車輛檢測系統(tǒng)主要基于車輛的表面特征,比如對稱性,顏色,紋理,陰影,幾何特征,車燈等,之后通過模版匹配或者機(jī)器學(xué)習(xí)方法對圖像進(jìn)行檢測�；谝曈X的車距測量方法主要有雙目視覺測距和單目視覺測距兩種,鑒于雙目視覺測距系統(tǒng)成本較高,計算復(fù)雜,目前單目視覺測距仍然是主流。當(dāng)前的輔助駕駛系統(tǒng)生產(chǎn)廠商會定制專門的硬件設(shè)備來實(shí)現(xiàn)車輛檢測和車距測量,平臺搭建費(fèi)用很高,普及程度較低。本文的車輛檢測和車距測量系統(tǒng)基于智能手機(jī)平臺,包括Android和IOS兩大主流平臺,使用手機(jī)的攝像頭錄制的視頻進(jìn)行實(shí)時檢測,大大降低了汽車輔助駕駛系統(tǒng)的使用成本,并且改進(jìn)了車輛檢測方法,使其能夠適應(yīng)多種復(fù)雜環(huán)境,包括陰雨天、城市道路、光線突變等,并且有效降低了系統(tǒng)的誤檢率,提高了準(zhǔn)確度,使其有望得到普及。為了兼顧實(shí)時性和準(zhǔn)確度,本文系統(tǒng)采用兩步前車檢測技術(shù),即尋找車輛假設(shè)區(qū)域和驗(yàn)證車輛假設(shè)區(qū)域。具體地,通過基于車道先驗(yàn)的兩步閾值法提取車底陰影,通過篩選規(guī)則對陰影區(qū)域進(jìn)行篩選從而得到車輛假設(shè)區(qū)域,之后利用基于haar-like特征的Adaboost方法來對車輛假設(shè)區(qū)域進(jìn)行驗(yàn)證,最后通過視頻流特征對誤檢進(jìn)行剔除并對車輛進(jìn)行跟蹤。本文還結(jié)合攝像頭透視幾何關(guān)系,提出了基于車道消失點(diǎn)的單目視覺測距方法,使得只需用戶提供攝像頭高度信息即可達(dá)到對前車距離進(jìn)行準(zhǔn)確估算的目的,可以作為有效的危險預(yù)警手段。實(shí)時性也是輔助駕駛系統(tǒng)的重要需求特性,該系統(tǒng)在保證準(zhǔn)確率的同時,綜合考慮了智能手機(jī)的特性,對該系統(tǒng)進(jìn)行了優(yōu)化,保證了系統(tǒng)運(yùn)行的實(shí)時性。實(shí)驗(yàn)結(jié)果表明該系統(tǒng)具有較高的準(zhǔn)確度和較低的誤檢率,并且能夠在智能手機(jī)上實(shí)時運(yùn)行,在晴朗、陰雨以及城市道路、高速道路等多種環(huán)境下表現(xiàn)良好,能夠有效地應(yīng)用到車輛檢測和車距測量等汽車輔助駕駛系統(tǒng)中。
[Abstract]:In recent years, with the increase in car ownership, traffic accident has become an important topic. To automobile driver assistance system (ADAS), especially the vehicle anti collision warning system and lane keeping assist system has become more and more important. The front vehicle detection and distance measurement is the key module of vehicle anti collision warning system. In the front vehicle detection system, the common sensor has a high frequency radar (millimeter wave), ultrasonic, infrared laser radar, cameras, each kind of sensor to adapt to the different scenes, to adapt to a variety of scenes, car manufacturers and auxiliary driving system providers generally will integrate a variety of sensors to collect information for decision-making. Based on the vehicle in front the visual detection system of low cost, abundant information, and in recent years the rapid development in the field of computer vision which provides a technical basis, so has received more and more research in related fields Personnel attention. Computer vision based vehicle detection system is mainly based on the surface characteristics of the vehicle, such as symmetry, color, texture, shadow, geometric feature, lights, followed by template matching of image or machine learning method based on visual detection. The vehicle distance measurement includes binocular vision ranging and monocular vision two, given the cost of binocular vision ranging system of high computational complexity, the monocular vision is still the mainstream manufacturers. The auxiliary drive system will specifically customized hardware to realize vehicle detection and distance measurement platform, high cost, popularity is low. The distance of the vehicle detection and vehicle the measurement system based on intelligent mobile phone platform, including Android and IOS two mainstream platform, using a mobile phone camera to record the video in real-time detection, greatly reducing vehicle auxiliary driving The use of cost driving system, and improved the vehicle detection method, which can adapt to the complex environment, including the rainy days, city road, light changes, and effectively reduce the system error rate, improve the accuracy, which is expected to be popular. For both real time and accuracy, this paper uses the system the two step preceding vehicle detection technology, which is looking for vehicles that regional and regional specific assumptions. Verify that the vehicle, by extracting the shadows two step Lane threshold method based on prior to the shadow region so as to obtain the regional vehicle hypothesis screening by screening rules, after using the Adaboost method based on Haar-like feature to verify the hypothesis of regional vehicle finally, through the video features to remove the false detection and tracking of the vehicle. This paper also combines the X-ray camera geometry, proposed a single lane based on visual vanishing points Sleep ranging method makes users only need to provide the camera height information can achieve accurate estimation of the objective from the front of the car, can be used as the early warning method. Real time is an important demand characteristic of auxiliary driving system, the system accuracy in ensuring at the same time, considering the characteristics of Intelligent Mobile phone, the system optimized to ensure real-time operation of system. The experimental results show that the system has high accuracy and low false alarm rate, and can in the intelligent mobile phone real-time operation, in the sunny, rainy and city roads, high-speed road under a variety of environmental performance is good, can be effectively applied to vehicle detection and vehicle distance measurement in driver assistant system.

【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U495;U463.6;TP391.41

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