本文關(guān)鍵詞： 交通運(yùn)輸系統(tǒng)工程 高速公路出入口 軌跡分析 改進(jìn)Hausdorff距離 聚類算法　出處：《吉林大學(xué)學(xué)報(bào)(工學(xué)版)》2017年06期 　論文類型：期刊論文

【摘要】：為了提高對高速公路出入口車輛運(yùn)動行為的理解和分析水平,根據(jù)出入口車輛運(yùn)動軌跡的時空特征,提出了一種運(yùn)動軌跡層次聚類算法。結(jié)合出入口軌跡方向一致、長短不一的特點(diǎn),提出采用改進(jìn)Hausdorff距離來衡量軌跡間的相似性。建立了改進(jìn)模糊C均值軌跡分層聚類算法,首先根據(jù)軌跡的空間幾何位置進(jìn)行路徑聚類,然后根據(jù)車輛的速度信息對已有路徑聚類進(jìn)一步聚類獲得具有時空區(qū)分度的最終結(jié)果。真實(shí)高速公路出入口的試驗(yàn)結(jié)果表明:本文提出的軌跡聚類算法對于場景固定運(yùn)動行為模式不僅具有較強(qiáng)的適用性,而且能夠保障聚類結(jié)果的準(zhǔn)確性和可靠性。
[Abstract]:In order to improve the understanding and analysis of the movement behavior of vehicles at the entrance and exit of freeway, a hierarchical clustering algorithm of motion trajectory is proposed according to the temporal and spatial characteristics of the moving track of the vehicle at the entrance and exit, and the direction of the entry and exit trajectory is the same. An improved Hausdorff distance is proposed to measure the similarity of trajectories, and an improved fuzzy C-means trajectory clustering algorithm is established. Firstly, the path clustering is carried out according to the spatial geometric position of the trajectory. Then according to the speed information of the vehicle, the existing path clustering is further clustered to obtain the final result with space-time discrimination. The experimental results of the real freeway entrance and exit show that the trajectory clustering algorithm proposed in this paper is useful to the scene. The fixed motion behavior mode is not only applicable, Moreover, it can ensure the accuracy and reliability of clustering results.
【作者單位】： 同濟(jì)大學(xué)道路與交通工程教育部重點(diǎn)試驗(yàn)室;
【基金】：“863”國家高技術(shù)研究發(fā)展計(jì)劃項(xiàng)目(2013AA12A206)
【分類號】：TP311.13;U491
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本文編號：1519475