Here we propose a method for extracting line-of-sight ionospheric observables from GPS data using precise point positioning(PPP).The PPP-derived ionospheric observables(PIOs) have identical form with their counterpart...Here we propose a method for extracting line-of-sight ionospheric observables from GPS data using precise point positioning(PPP).The PPP-derived ionospheric observables(PIOs) have identical form with their counterparts obtained from leveling the geometry-free GPS carrier-phase to code(leveling ionospheric observables,LIOs),and are affected by the satellite and receiver inter-frequency biases(IFBs).Based on the co-location experiments,the effects of extracting error arising from the observational noise and multipath on the PIOs and the LIOs are comparatively assessed,and the considerably reduced effects ranging from 70% to 75% on the PIOs with respect to the LIOs can be verified in our case.In addition,based on 26 consecutive days' GPS observations from two international GNSS service(IGS) sites(COCO,DAEJ) during disturbed ionosphere period,the extracted PIOs and LIOs are respectively used as the input of single-layer ionospheric model to retrieve daily satellite IFBs station-by-station.The minor extracting errors underlying the PIOs in contrast to the LIOs can also be proven by reducing day-to-day scatter and improving between-receiver consistency in the retrieved satellite IFBs values.展开更多
Traffic count is the fundamental data source for transportation planning, management, design, and effectiveness evaluation. Recording traffic flow and counting from the recorded videos are increasingly used due to con...Traffic count is the fundamental data source for transportation planning, management, design, and effectiveness evaluation. Recording traffic flow and counting from the recorded videos are increasingly used due to convenience, high accuracy, and cost-effectiveness. Manual counting from pre-recorded video footage can be prone to inconsistencies and errors, leading to inaccurate counts. Besides, there are no standard guidelines for collecting video data and conducting manual counts from the recorded videos. This paper aims to comprehensively assess the accuracy of manual counts from pre-recorded videos and introduces guidelines for efficiently collecting video data and conducting manual counts by trained individuals. The accuracy assessment of the manual counts was conducted based on repeated counts, and the guidelines were provided from the experience of conducting a traffic survey on forty strip mall access points in Baton Rouge, Louisiana, USA. The percentage of total error, classification error, and interval error were found to be 1.05 percent, 1.08 percent, and 1.29 percent, respectively. Besides, the percent root mean square errors (RMSE) were found to be 1.13 percent, 1.21 percent, and 1.48 percent, respectively. Guidelines were provided for selecting survey sites, instruments and timeframe, fieldwork, and manual counts for an efficient traffic data collection survey.展开更多
基金supported by National Basic Research Program of China(Grant No. 2012CB82560X)National Natural Science Foundation of China (Grant Nos. 41174015 and 41074013)
文摘Here we propose a method for extracting line-of-sight ionospheric observables from GPS data using precise point positioning(PPP).The PPP-derived ionospheric observables(PIOs) have identical form with their counterparts obtained from leveling the geometry-free GPS carrier-phase to code(leveling ionospheric observables,LIOs),and are affected by the satellite and receiver inter-frequency biases(IFBs).Based on the co-location experiments,the effects of extracting error arising from the observational noise and multipath on the PIOs and the LIOs are comparatively assessed,and the considerably reduced effects ranging from 70% to 75% on the PIOs with respect to the LIOs can be verified in our case.In addition,based on 26 consecutive days' GPS observations from two international GNSS service(IGS) sites(COCO,DAEJ) during disturbed ionosphere period,the extracted PIOs and LIOs are respectively used as the input of single-layer ionospheric model to retrieve daily satellite IFBs station-by-station.The minor extracting errors underlying the PIOs in contrast to the LIOs can also be proven by reducing day-to-day scatter and improving between-receiver consistency in the retrieved satellite IFBs values.
文摘Traffic count is the fundamental data source for transportation planning, management, design, and effectiveness evaluation. Recording traffic flow and counting from the recorded videos are increasingly used due to convenience, high accuracy, and cost-effectiveness. Manual counting from pre-recorded video footage can be prone to inconsistencies and errors, leading to inaccurate counts. Besides, there are no standard guidelines for collecting video data and conducting manual counts from the recorded videos. This paper aims to comprehensively assess the accuracy of manual counts from pre-recorded videos and introduces guidelines for efficiently collecting video data and conducting manual counts by trained individuals. The accuracy assessment of the manual counts was conducted based on repeated counts, and the guidelines were provided from the experience of conducting a traffic survey on forty strip mall access points in Baton Rouge, Louisiana, USA. The percentage of total error, classification error, and interval error were found to be 1.05 percent, 1.08 percent, and 1.29 percent, respectively. Besides, the percent root mean square errors (RMSE) were found to be 1.13 percent, 1.21 percent, and 1.48 percent, respectively. Guidelines were provided for selecting survey sites, instruments and timeframe, fieldwork, and manual counts for an efficient traffic data collection survey.
