Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation
In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to suppleme...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/6628335 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832566293513895936 |
|---|---|
| author | Yun Jiang Guohua Song Zeyu Zhang Zhiqiang Zhai Lei Yu |
| author_facet | Yun Jiang Guohua Song Zeyu Zhang Zhiqiang Zhai Lei Yu |
| author_sort | Yun Jiang |
| collection | DOAJ |
| description | In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing. |
| format | Article |
| id | doaj-art-a9dab8bd8e1647bfb14db482e76fde99 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-a9dab8bd8e1647bfb14db482e76fde992025-02-03T01:04:36ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/66283356628335Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission EstimationYun Jiang0Guohua Song1Zeyu Zhang2Zhiqiang Zhai3Lei Yu4Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, ChinaKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, ChinaIn order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing.http://dx.doi.org/10.1155/2021/6628335 |
| spellingShingle | Yun Jiang Guohua Song Zeyu Zhang Zhiqiang Zhai Lei Yu Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation Journal of Advanced Transportation |
| title | Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation |
| title_full | Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation |
| title_fullStr | Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation |
| title_full_unstemmed | Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation |
| title_short | Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation |
| title_sort | estimation of hourly traffic flows from floating car data for vehicle emission estimation |
| url | http://dx.doi.org/10.1155/2021/6628335 |
| work_keys_str_mv | AT yunjiang estimationofhourlytrafficflowsfromfloatingcardataforvehicleemissionestimation AT guohuasong estimationofhourlytrafficflowsfromfloatingcardataforvehicleemissionestimation AT zeyuzhang estimationofhourlytrafficflowsfromfloatingcardataforvehicleemissionestimation AT zhiqiangzhai estimationofhourlytrafficflowsfromfloatingcardataforvehicleemissionestimation AT leiyu estimationofhourlytrafficflowsfromfloatingcardataforvehicleemissionestimation |