本文關(guān)鍵詞： 線激光雷達 DBSCAN算法 加權(quán)歐式距離 可行駛區(qū)域　出處：《汽車技術(shù)》2016年02期 　論文類型：期刊論文

【摘要】：通過分析大量激光雷達數(shù)據(jù),提出了改進的DBSCAN算法對雷達數(shù)據(jù)進行聚類,以使智能汽車獲得前方道路和障礙物信息。根據(jù)不同的密度參數(shù),多次調(diào)用該算法完成多密度聚類。結(jié)合提出的道路邊沿、路面和障礙物等信息提取方法,在結(jié)構(gòu)化或半結(jié)構(gòu)化的城市道路中對提出的方法進行實車試驗,結(jié)果表明該算法可實時準確的提取智能汽車的可行駛區(qū)域信息。
[Abstract]:Through the analysis of a large number of laser radar data, an improved DBSCAN algorithm is proposed to cluster the radar data, in order to make the smart car road ahead and obstacle information. According to the density of different parameters, calls the completion of the algorithm of multi density clustering. In combination with the proposed edge extraction method, pavement and obstacle information, vehicle test the proposed method is in a structured or semi-structured road in the city. The results show that the algorithm can real-time and accurate extraction of the intelligent vehicle driving region information.

【作者單位】： 北京工業(yè)大學(xué)北京市交通工程重點實驗室;
【基金】：北京市屬高等學(xué)校人才強教計劃資助項目(038000543115025)
【分類號】：U463.6
【正文快照】： Preceding Drivable Area Detection Based on Four-layer Laser Radar(Beijing Key Laboratory of Traffic Engineering,Beijing University of Technology,Beijing 100124)1前言智能汽車利用可通行區(qū)域信息來保障其在道路區(qū)域內(nèi)安全行駛,防止側(cè)翻和碰撞等危險狀況發(fā)生。車輛，

本文編號：1451850