本文選題：智能汽車 + 環(huán)境感知系統(tǒng)　； 參考：《南昌航空大學》2017年碩士論文

【摘要】：隨著汽車產業(yè)高速發(fā)展過程中,智能汽車逐漸成為汽車領域和各大汽車廠商關注的新方向。智能汽車主要有感知、決策、控制和路徑規(guī)劃等系統(tǒng)構成,其中感知系統(tǒng)是汽車實現(xiàn)智能駕駛的基礎。感知系統(tǒng)是通過環(huán)境感知傳感器收集車輛周圍的環(huán)境信息,包括車道線、行人和車輛等識別對象。本文的主要研究內容:(1)搭建基于多傳感器的智能清掃實驗車輛平臺,并設計相應的環(huán)境感知系統(tǒng)算法,初步實現(xiàn)環(huán)境感知系統(tǒng)功能。在智能清掃實驗車輛安裝相機、長距離毫米波雷達、短距離毫米波雷達和超聲波雷達環(huán)境感知傳感器,實現(xiàn)實驗車輛周圍360°范圍內目標物的檢測和對前方車道線識別功能;(2)研究基于通過車輛CAN總線技術獲取毫米波雷達檢測到障礙物的原始數據,并設計數據預處理的冒泡篩選和時域濾波算法,實現(xiàn)穩(wěn)定檢測和跟蹤目標物,其中數據預處理算法也是多傳感器數據融合算法的基礎;(3)研究基于多傳感器數據融合結構的前方目標物檢測算法,并設計適用于結構化道路中傳感器級和中央級數據融合結構算法,通過設計的數據融合算法提高前方目標物被檢測概率和目標物的物理信息可信度;然后對融合后的目標物進行卡爾曼濾波跟蹤,實現(xiàn)對車輛前方目標物被穩(wěn)定檢測跟蹤的功能;最后,對智能清掃實驗車輛進行環(huán)境感知系統(tǒng)測試。在結構化道路中,實驗車輛前方分別設置行人、車輛和自行車為被檢測對象,測試結果表明本文設計的多傳感器數據融合算法能夠穩(wěn)定識別跟蹤目標物和提高目標物的物理信息可信度;在實驗車輛左右二側和后方分別設置自行車靠近的運動場景,測試結果表明本文設計的數據預處理算法能夠穩(wěn)定識別跟蹤自行車目標對象;另外實驗車輛前方相機傳感器識別車道線;從而初步實現(xiàn)智能清掃實驗車的環(huán)境感知系統(tǒng)功能,為整車控制器提供車輛全方位的環(huán)境信息,保障車輛的安全行駛。
[Abstract]:With the rapid development of automobile industry, intelligent automobile has gradually become a new direction of attention in automobile field and major automobile manufacturers. Intelligent vehicle is composed of perception, decision making, control and path planning, among which the perceptual system is the basis of realizing intelligent driving. The sensing system collects the environmental information around the vehicle through the environment sensing sensor, including lane line, pedestrian and vehicle identification object. The main research content of this paper is to build a multi-sensor intelligent cleaning experimental vehicle platform and design the corresponding environment awareness system algorithm to realize the function of environment sensing system. Installation of cameras, long-range millimeter-wave radar, short-range millimeter-wave radar and ultrasonic radar environment sensing sensors in intelligent cleaning experimental vehicles, The object detection around the vehicle around 360 擄and the recognition function of the front lane are realized. Based on the CAN bus technology of the vehicle, the original data of the obstacle detected by the millimeter wave radar is obtained. The bubbling filtering and time domain filtering algorithms for data preprocessing are designed to realize the stable detection and tracking of the target. Data preprocessing algorithm is also the basis of multi-sensor data fusion algorithm. The algorithm is designed for sensor level and center level data fusion structure in structured road. The data fusion algorithm is designed to improve the detection probability and the reliability of physical information of the object. Then the fusion object is tracked by Kalman filter to realize the function of detecting and tracking the object in front of the vehicle. Finally, the environment sensing system of the intelligent cleaning experimental vehicle is tested. In structured roads, pedestrians, vehicles and bicycles were placed in front of the experimental vehicles. The test results show that the multi-sensor data fusion algorithm designed in this paper can stably identify the tracking object and improve the reliability of the physical information of the object. The test results show that the data preprocessing algorithm designed in this paper can stably identify and track the bicycle target object; in addition, the camera sensor in front of the experimental vehicle can recognize the lane line, thus realizing the environment sensing system function of the intelligent cleaning experimental vehicle. Provide all-round environmental information for the vehicle controller to ensure the safe driving of the vehicle.
【學位授予單位】：南昌航空大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U463.6;TP212

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本文編號：1840269