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Estimating fuel consumption and emissions based on reconstructed vehicle trajectories
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| Zeitschriftentitel: | Journal of Advanced Transportation |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Journal of Advanced Transportation, 48, 2014, 6, S. 627-641 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
|
| Schlagwörter: |
| author_facet |
Chen, Zhong Yang, Chao Chen, Anthony Chen, Zhong Yang, Chao Chen, Anthony |
|---|---|
| author |
Chen, Zhong Yang, Chao Chen, Anthony |
| spellingShingle |
Chen, Zhong Yang, Chao Chen, Anthony Journal of Advanced Transportation Estimating fuel consumption and emissions based on reconstructed vehicle trajectories Strategy and Management Computer Science Applications Mechanical Engineering Economics and Econometrics Automotive Engineering |
| author_sort |
chen, zhong |
| spelling |
Chen, Zhong Yang, Chao Chen, Anthony 0197-6729 2042-3195 Wiley Strategy and Management Computer Science Applications Mechanical Engineering Economics and Econometrics Automotive Engineering http://dx.doi.org/10.1002/atr.1215 <jats:title>SUMMARY</jats:title><jats:p>Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.</jats:p> Estimating fuel consumption and emissions based on reconstructed vehicle trajectories Journal of Advanced Transportation |
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| title |
Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_unstemmed |
Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_full |
Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_fullStr |
Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_full_unstemmed |
Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_short |
Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_sort |
estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| topic |
Strategy and Management Computer Science Applications Mechanical Engineering Economics and Econometrics Automotive Engineering |
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http://dx.doi.org/10.1002/atr.1215 |
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2014 |
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<jats:title>SUMMARY</jats:title><jats:p>Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.</jats:p> |
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| author | Chen, Zhong, Yang, Chao, Chen, Anthony |
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| description | <jats:title>SUMMARY</jats:title><jats:p>Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.</jats:p> |
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| spelling | Chen, Zhong Yang, Chao Chen, Anthony 0197-6729 2042-3195 Wiley Strategy and Management Computer Science Applications Mechanical Engineering Economics and Econometrics Automotive Engineering http://dx.doi.org/10.1002/atr.1215 <jats:title>SUMMARY</jats:title><jats:p>Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.</jats:p> Estimating fuel consumption and emissions based on reconstructed vehicle trajectories Journal of Advanced Transportation |
| spellingShingle | Chen, Zhong, Yang, Chao, Chen, Anthony, Journal of Advanced Transportation, Estimating fuel consumption and emissions based on reconstructed vehicle trajectories, Strategy and Management, Computer Science Applications, Mechanical Engineering, Economics and Econometrics, Automotive Engineering |
| title | Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_full | Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_fullStr | Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_full_unstemmed | Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_short | Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_sort | estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| title_unstemmed | Estimating fuel consumption and emissions based on reconstructed vehicle trajectories |
| topic | Strategy and Management, Computer Science Applications, Mechanical Engineering, Economics and Econometrics, Automotive Engineering |
| url | http://dx.doi.org/10.1002/atr.1215 |