计算机与现代化
計算機與現代化
계산궤여현대화
COMPUTER AND MODERNIZATION
2014年
2期
124-128
,共5页
欧阳鸿%刘建勋%刘毅志%廖祝华%陈佘喜
歐暘鴻%劉建勛%劉毅誌%廖祝華%陳佘喜
구양홍%류건훈%류의지%료축화%진사희
路网提取%步行轨迹%小路提取%聚类算法%曲线拟合
路網提取%步行軌跡%小路提取%聚類算法%麯線擬閤
로망제취%보행궤적%소로제취%취류산법%곡선의합
road network extraction%walking trajectories%pathway extraction%clustering algorithm%curve fitting
准确提取和及时更新路网信息,对于道路规划和车辆导航等方面至关重要。目前,基于GPS轨迹的路网提取方法一般是从浮动车或出租车的GPS轨迹中挖掘城市主干路网。然而,现有方法忽略了小路的自动提取,它对于抗震救灾、小区导航或乡村游览等场合非常重要。因此,本文提出基于步行GPS轨迹的路网提取方法,分为数据预处理、道路中心线生成和路网精度评价3个部分。其中,先后采用轨迹点聚类、聚类点分割和中心线拟合等方法生成道路中心线。通过自行采集的步行GPS数据进行实验,结果表明,本文方法能够准确提取路网,覆盖率可达96.21%,而误检率仅3.26%;并且能够提取小路和更新路网。
準確提取和及時更新路網信息,對于道路規劃和車輛導航等方麵至關重要。目前,基于GPS軌跡的路網提取方法一般是從浮動車或齣租車的GPS軌跡中挖掘城市主榦路網。然而,現有方法忽略瞭小路的自動提取,它對于抗震救災、小區導航或鄉村遊覽等場閤非常重要。因此,本文提齣基于步行GPS軌跡的路網提取方法,分為數據預處理、道路中心線生成和路網精度評價3箇部分。其中,先後採用軌跡點聚類、聚類點分割和中心線擬閤等方法生成道路中心線。通過自行採集的步行GPS數據進行實驗,結果錶明,本文方法能夠準確提取路網,覆蓋率可達96.21%,而誤檢率僅3.26%;併且能夠提取小路和更新路網。
준학제취화급시경신로망신식,대우도로규화화차량도항등방면지관중요。목전,기우GPS궤적적로망제취방법일반시종부동차혹출조차적GPS궤적중알굴성시주간로망。연이,현유방법홀략료소로적자동제취,타대우항진구재、소구도항혹향촌유람등장합비상중요。인차,본문제출기우보행GPS궤적적로망제취방법,분위수거예처리、도로중심선생성화로망정도평개3개부분。기중,선후채용궤적점취류、취류점분할화중심선의합등방법생성도로중심선。통과자행채집적보행GPS수거진행실험,결과표명,본문방법능구준학제취로망,복개솔가체96.21%,이오검솔부3.26%;병차능구제취소로화경신로망。
Accurately extracting and timely updating the information of road network is vital to road planning and vehicle naviga -tion.Currently, the road network’s extraction method for mining urban trunk roads , based on GPS trajectories, commonly uses floating car or taxi .However , the existing methods ignore the automatic extraction of pathway , which is very important for earth-quake relief , community navigation and village tour and other occasions .Therefore , this paper proposes a new method of road network extraction , based on walking GPS trajectories , which consists of three parts:data preprocessing , road centerline genera-tion and road network accuracy evaluation .In this paper , three methods are adopted to generate road centerlines successively , such as trajectories clustering , cluster center segmentation and centerline fitting .Making experiment with self-collected walking GPS data, the results show that the proposed method not only is able to accurately extract the road network , coverage rate can reach 96.21%while error detection rate was 3.26%, but also can extract pathway and update road network .