本文關(guān)鍵詞：基于無軌電車避撞的雷達(dá)目標(biāo)識(shí)別和跟蹤技術(shù)研究　出處：《北京交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 無軌電車 激光雷達(dá) 柵格地圖 擴(kuò)展卡爾曼濾波算法/最近鄰算法組合 信息采集軟件 實(shí)時(shí)顯示軟件

【摘要】：近年來,許多大中型城市大力建設(shè)公共交通系統(tǒng),隨著“綠色交通”理念的提出,無軌電車作為新能源公共交通工具,逐漸有復(fù)興之勢。但無軌電車有車體寬,車身長,轉(zhuǎn)彎半徑大等缺點(diǎn),導(dǎo)致車輛有很多視覺死角,容易發(fā)生交通事故。車載激光雷達(dá)可以探測車前情況,識(shí)別車前障礙物的大小并判斷障礙物的運(yùn)動(dòng)狀態(tài)。將激光雷達(dá)技術(shù)與無軌電車結(jié)合,研究無軌電車目標(biāo)識(shí)別與跟蹤技術(shù)有助于提高車輛行駛安全性。本文主要目的研究可應(yīng)用于無軌電車避撞的激光雷達(dá)目標(biāo)識(shí)別與跟蹤的技術(shù)方案,通過相關(guān)算法完成對目標(biāo)識(shí)別與跟蹤功能的實(shí)現(xiàn)。(1)本文分析了無軌電車的國內(nèi)外發(fā)展?fàn)顩r,并對障礙物目標(biāo)識(shí)別和目標(biāo)跟蹤技術(shù)分別進(jìn)行闡述。接著分析無軌電車障礙物目標(biāo)識(shí)別和目標(biāo)跟蹤的功能需求和系統(tǒng)總體設(shè)計(jì),重點(diǎn)說明了目標(biāo)的分割聚類和目標(biāo)跟蹤,分割聚類采用柵格算法,對激光雷達(dá)散點(diǎn)進(jìn)行聚類處理,建立車前目標(biāo)分類,目標(biāo)跟蹤采用擴(kuò)展卡爾曼濾波算法和最近鄰算法組合,判別聚類數(shù)據(jù)結(jié)果的狀態(tài),對其中的目標(biāo)障礙物進(jìn)行跟蹤。(2)本文闡述了無軌電車避撞系統(tǒng)的結(jié)構(gòu),并對其中的信息采集模塊、目標(biāo)識(shí)別模塊和目標(biāo)跟蹤模塊進(jìn)行了說明。對激光雷達(dá)信息采集軟件和激光雷達(dá)實(shí)時(shí)顯示軟件分別進(jìn)行軟件的功能和結(jié)構(gòu)設(shè)計(jì),采用C++編程語言完成軟件。(3)對無軌電車障礙物識(shí)別和目標(biāo)跟蹤系統(tǒng)進(jìn)行實(shí)車測試與驗(yàn)證,并對實(shí)驗(yàn)結(jié)果進(jìn)行分析。通過實(shí)車采集信息與測試方案信息對比,驗(yàn)證了柵格算法和擴(kuò)展卡爾曼濾波算法和最近鄰算法組合的有效性。通過對軟件各功能的測試,實(shí)現(xiàn)了車前環(huán)境信息采集、車前環(huán)境實(shí)時(shí)雷達(dá)顯示、車前環(huán)境實(shí)時(shí)視頻顯示,車前障礙物的聚類處理,驗(yàn)證了軟件的可用性。實(shí)驗(yàn)結(jié)果表明,論文提出的無軌電車障礙物識(shí)別和目標(biāo)跟蹤系統(tǒng)能夠準(zhǔn)確采集車前環(huán)境信息,能夠?qū)崿F(xiàn)障礙物識(shí)別和目標(biāo)跟蹤,實(shí)時(shí)準(zhǔn)確的為駕駛員提供車輛預(yù)警信息。
[Abstract]:In recent years, many large and medium-sized cities have made great efforts to build public transport system. With the concept of "green transportation", trolleybus as a new energy public transport, gradually has the potential to revive, but trolleybus has a wide body. Long body, large turning radius and other shortcomings, resulting in a lot of vehicle visual dead-angle, prone to traffic accidents. Vehicle lidar can detect the car in front of the situation. Recognize the size of the obstacle in front of the vehicle and judge the motion of the obstacle. Combine lidar technology with trolley bus. The research on target recognition and tracking technology of trolleybus is helpful to improve the safety of vehicle running. The main purpose of this paper is to study the technical scheme of lidar target recognition and tracking which can be applied to collision avoidance of trolleybus. This paper analyzes the development of trolley bus at home and abroad. Then the functional requirements and the overall system design of obstacle target recognition and target tracking for trolleybus are analyzed. The segmentation clustering and target tracking are emphasized. The raster algorithm is used to cluster the scattered points of lidar, and the target classification in front of vehicle is established. Target tracking uses extended Kalman filter algorithm and nearest neighbor algorithm to judge the status of clustering data results and track the target obstacles. 2) this paper describes the structure of trolley bus collision avoidance system. The information acquisition module, target recognition module and target tracking module are described. The function and structure of the software are designed for the laser radar information acquisition software and the laser radar real-time display software. C programming language is used to complete the software. 3) to test and verify the obstacle recognition and target tracking system of trolley bus. The results of the experiment are analyzed. The information collected by the real vehicle is compared with the information of the test scheme. The validity of the combination of grid algorithm and extended Kalman filter algorithm and nearest neighbor algorithm is verified. Through testing the functions of the software, the acquisition of environment information in front of vehicle and the real-time radar display in front of vehicle environment are realized. Real time video display in front of vehicle environment and clustering processing of obstacles in front of vehicle verify the usability of the software. The experimental results show that. The obstacle recognition and target tracking system of trolley bus proposed in this paper can accurately collect the environment information in front of vehicle, realize obstacle recognition and target tracking, and provide early warning information for driver in real time.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U482.2;TN958.98

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本文編號(hào)：1406378