本文選題：城市交通 + 信息技術(shù)�。� 參考：《交通運輸系統(tǒng)工程與信息》2014年06期

【摘要】：在車聯(lián)網(wǎng)應(yīng)用發(fā)展的背景下,許多城市的私家車和出租車上安裝了配備GPS設(shè)備的智能終端,產(chǎn)生著大量的時空軌跡數(shù)據(jù).為挖掘這些數(shù)據(jù)蘊含的駕駛員出行特征,本文以北京市出租車時空軌跡數(shù)據(jù)為例,基于時空GIS的視角提出并實現(xiàn)了駕駛員居住地挖掘方法和作息規(guī)律性分析方法.樣本實驗結(jié)果一方面展示了駕駛員居住地空間分布,另一方面表明作息規(guī)律性總相似度在0.6 1之間的駕駛員數(shù)量較多,占到了總數(shù)的73.75%.通過本文方法挖掘的信息可為出租車的管理提供輔助決策,方法同樣適用私家車時空軌跡數(shù)據(jù)的挖掘,對私家車出行規(guī)律的研究和掌握更有意義.
[Abstract]:Under the background of the development of the application of car networking, many private cars and taxis in many cities have installed intelligent terminals equipped with GPS equipment, which produces a large amount of space-time trajectory data. In order to mine the characteristics of drivers' travel in these data, this paper takes the spatio-temporal track data of Beijing taxi as an example, and puts forward and realizes the mining method of drivers' residence and the analysis method of the regularity of working and rest based on the perspective of spatio-temporal GIS. On the one hand, the sample results show the spatial distribution of drivers' residence, on the other hand, it shows that the number of drivers with the general similarity of work and rest regularity between 0.6 and 1 is more, accounting for 73.75% of the total. The information mined by this method can provide auxiliary decision for taxi management. The method is also applicable to the mining of private cars' space-time track data, which is more significant for the study and mastering of private car travel rules.
【作者單位】： 北京建筑大學測繪與城市空間信息學院;現(xiàn)代城市測繪國家測繪地理信息局重點實驗室;中國科學院地理科學與資源研究所資源與環(huán)境信息系統(tǒng)國家重點實驗室;
【基金】：現(xiàn)代城市測繪國家測繪地理信息局重點實驗室開放基金項目(20111216N) 北京市優(yōu)秀人才培養(yǎng)資助個人項目(2011D005017000005)
【分類號】：U495

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