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A Hybrid Geostatistical Method for Estimating Citywide Traffic Volumes - A Case Study of Edmonton, Canada
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作者 mingjian wu Tae J.Kwon Karim El-Basyouny 《Journal of Geographical Research》 2022年第2期52-68,共17页
Traffic volume information has long played an important role in many transportation related works,such as traffic operations,roadway design,air quality control,and policy making.However,monitoring traffic volumes over... Traffic volume information has long played an important role in many transportation related works,such as traffic operations,roadway design,air quality control,and policy making.However,monitoring traffic volumes over a large spatial area is not an easy task due to the significant amount of time and manpower required to collect such large-scale datasets.In this study,a hybrid geostatistical approach,named Network Regression Kriging,has been developed to estimate urban traffic volumes by incorporating auxiliary variables such as road type,speed limit,and network accessibility.Since standard kriging is based on Euclidean distances,this study implements road network distances to improve traffic volumes estimations.A case study using 10-year of traffic volume data collected within the city of Edmonton was conducted to demonstrate the robustness of the model developed herein.Results suggest that the proposed hybrid model significantly outperforms the standard kriging method in terms of accuracy by 4.0%overall,especially for a large-scale network.It was also found that the necessary stationarity assumption for kriging did not hold true for a large network whereby separate estimations for each road type performed significantly better than a general estimation for the overall network by 4.12%. 展开更多
关键词 Traffic volume Geographical information system Spatial modelling Hybrid geostatistics Network regression kriging
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Flight trajectory optimization of sun-tracking solar aircraft under the constraint of mission region 被引量:1
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作者 mingjian wu Zhiwei SHI +1 位作者 Tianhang XIAO Haisong ANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2021年第11期140-153,共14页
The optimal yawing angle of sun-tracking solar aircraft is tightly related to the solar azimuth angle,which results in a large arc flight path to dynamically track the sun position.However,the limited detection range ... The optimal yawing angle of sun-tracking solar aircraft is tightly related to the solar azimuth angle,which results in a large arc flight path to dynamically track the sun position.However,the limited detection range of payload usually requires solar aircraft to loiter over areas of interest for persistent surveillance missions.The large arc sun-tracking flight may cause the target area on the ground to be outside the maximum coverage area of payload.The present study therefore develops an optimal flight control approach for planning the flight path of sun-tracking solar aircraft within a mission region.The proposed method enables sun-tracking solar aircraft to maintain the optimal yawing angle most of the time during daylight flight,except when the aircraft reverses its direction by turning flight.For a circular region with a mission radius of 50km,the optimal flight trajectory and controls of an example K-shaped sun-tracking solar aircraft are investigated theoretically.Results demonstrate the effectiveness of the proposed approach to optimize the flight path of the sun-tracking aircraft under the given circular region while maximizing the battery input power.Furthermore,the effects of varying the mission radius on energy performance are explored numerically.It has been proved that both net energy and energy balance remain nearly constant as the radius constraint varies,which enables the solar aircraft to achieve perpetual flight at almost the same latitude as the large arc flight.The method and results presented in this paper can provide reference for the persistent operation of sun-tracking solar aircraft within specific mission areas. 展开更多
关键词 Energy performance Mission region Optimal yawing angle Perpetual operation Sun-tracking solar aircraft Trajectory optimization
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