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Article: Traffic data interpolation method of non-detection road link based on Kriging interpolation

TitleTraffic data interpolation method of non-detection road link based on Kriging interpolation
基於Kriging插值的無檢測器路段交通數據插補方法
Authors
KeywordsFloating Car (浮動車)
Geographic Information System For Transportation (交通地理信息系統)
Intelligence Transportation System (交通數據分析)
Kriging Interpolation (Kriging插值)
Spatial Correlation (空間相關性)
Traffic Data Analysis (交通數據分析)
Issue Date2011
Citation
Journal Of Traffic And Transportation Engineering, 2011, v. 11 n. 3, p. 118-126 How to Cite?
交通運輸工程學報, 2011, v. 11 n. 3, p. 118-126 How to Cite?
AbstractFrom the diffused characteristic of traffic flow and prior knowledge, Kriging interpolation was adopted to interpolate the traffic data of non-detection road link. Based on the spatial correlation of traffic data, a spatial model of traffic data was built. The spatial distance was adopted as metric to estimate the unsampled traffic data of road link. The road link travel speeds of Nanchang's road network were used as experiment data, which were collected from urban floating car system, and the method was verified. Experiment result shows that the standard errors of speed interpolations are always lower than 8 km · h -1 in different urban traffic time periods. Downtown zone and lake zone have different road network structures, and their mean absolute errors of speed interpolations are 2-5 km · h -1. So the method has good temporal and regional portabilities.
从交通流扩散的特点和人的先验知识出发,提出采用Kriging插值法对路网中无检测器路段进行交通数据插补。基于交通数据空间相关性的特征,对交通数据进行空间建模,从而以空间距离作为度量基准对未知路段交通数据进行估计。利用南昌市浮动车系统中提取的路段行程速度作为试验数据,进行了试验验证。研究结果表明:在城市交通中各个典型时段行程速度的插补值标准差可以控制在8 km·h-1以内;在针对路网形态差异较大的中心区和湖区分别进行的试验中,行程速度的平均绝对误差都保持在2~5 km·h-1之间。可见,该方法具有良好的时态和区域移植性。
Persistent Identifierhttp://hdl.handle.net/10722/176299
ISSN
2015 SCImago Journal Rankings: 0.339
References

 

DC FieldValueLanguage
dc.contributor.authorZou, HXen_US
dc.contributor.authorYue, Yen_US
dc.contributor.authorLi, QQen_US
dc.contributor.authorYeh, AGOen_US
dc.date.accessioned2012-11-26T09:08:18Z-
dc.date.available2012-11-26T09:08:18Z-
dc.date.issued2011en_US
dc.identifier.citationJournal Of Traffic And Transportation Engineering, 2011, v. 11 n. 3, p. 118-126en_US
dc.identifier.citation交通運輸工程學報, 2011, v. 11 n. 3, p. 118-126-
dc.identifier.issn1671-1637en_US
dc.identifier.urihttp://hdl.handle.net/10722/176299-
dc.description.abstractFrom the diffused characteristic of traffic flow and prior knowledge, Kriging interpolation was adopted to interpolate the traffic data of non-detection road link. Based on the spatial correlation of traffic data, a spatial model of traffic data was built. The spatial distance was adopted as metric to estimate the unsampled traffic data of road link. The road link travel speeds of Nanchang's road network were used as experiment data, which were collected from urban floating car system, and the method was verified. Experiment result shows that the standard errors of speed interpolations are always lower than 8 km · h -1 in different urban traffic time periods. Downtown zone and lake zone have different road network structures, and their mean absolute errors of speed interpolations are 2-5 km · h -1. So the method has good temporal and regional portabilities.en_US
dc.description.abstract从交通流扩散的特点和人的先验知识出发,提出采用Kriging插值法对路网中无检测器路段进行交通数据插补。基于交通数据空间相关性的特征,对交通数据进行空间建模,从而以空间距离作为度量基准对未知路段交通数据进行估计。利用南昌市浮动车系统中提取的路段行程速度作为试验数据,进行了试验验证。研究结果表明:在城市交通中各个典型时段行程速度的插补值标准差可以控制在8 km·h-1以内;在针对路网形态差异较大的中心区和湖区分别进行的试验中,行程速度的平均绝对误差都保持在2~5 km·h-1之间。可见,该方法具有良好的时态和区域移植性。-
dc.languagechien_US
dc.relation.ispartofJournal of Traffic and Transportation Engineeringen_US
dc.relation.ispartof交通運輸工程學報-
dc.subjectFloating Car (浮動車)en_US
dc.subjectGeographic Information System For Transportation (交通地理信息系統)en_US
dc.subjectIntelligence Transportation System (交通數據分析)en_US
dc.subjectKriging Interpolation (Kriging插值)en_US
dc.subjectSpatial Correlation (空間相關性)en_US
dc.subjectTraffic Data Analysis (交通數據分析)en_US
dc.titleTraffic data interpolation method of non-detection road link based on Kriging interpolationen_US
dc.title基於Kriging插值的無檢測器路段交通數據插補方法-
dc.typeArticleen_US
dc.identifier.emailYeh, AGO: hdxugoy@hkucc.hku.hken_US
dc.identifier.authorityYeh, AGO=rp01033en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-79960408869en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79960408869&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume11en_US
dc.identifier.issue3en_US
dc.identifier.spage118en_US
dc.identifier.epage126en_US
dc.identifier.scopusauthoridZou, HX=35194951800en_US
dc.identifier.scopusauthoridYue, Y=35303739000en_US
dc.identifier.scopusauthoridLi, QQ=36141966600en_US
dc.identifier.scopusauthoridYeh, AGO=7103069369en_US

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