Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment
Day-long origin-destination (OD) demand estimation for transportation forecasting is advantageous in terms of accuracy and reliability because it is not affected by hourly variations in the OD distribution. In this paper, we propose a method to estimate the time coefficient of day-long OD demand to...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2017/6495861 |
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| author | Motohiro Fujita Shinji Yamada Shintaro Murakami |
| author_facet | Motohiro Fujita Shinji Yamada Shintaro Murakami |
| author_sort | Motohiro Fujita |
| collection | DOAJ |
| description | Day-long origin-destination (OD) demand estimation for transportation forecasting is advantageous in terms of accuracy and reliability because it is not affected by hourly variations in the OD distribution. In this paper, we propose a method to estimate the time coefficient of day-long OD demand to estimate hourly OD demand and to predict hourly traffic for urban transportation planning of a large-scale road network that lacks discrete-time rich traffic data. The model proposed estimates the time coefficients from observed link flows given a proven day-long OD demand based on a bilevel formulation of the generalized least square and semidynamic traffic assignment (OD-modification approach). The OD-modification approach is formulated as a static user-equilibrium assignment with elastic demand, based on the residual demand at the end of each period. Our model does not require setting many parameters regarding the OD demand matrices and the discrete-time dynamic traffic assignments. Applying the model to large-scale road network demonstrates that it efficiently improves estimation accuracy because the 24-hour time coefficients of survey data are slightly biased and may be modified properly. In addition, the methods that partially relax the assumption of OD-modification approach and transform the estimated demand into demand based on departure time are examined. |
| format | Article |
| id | doaj-art-6f47d8c28fd44694a40143eeee51a8fc |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-6f47d8c28fd44694a40143eeee51a8fc2025-02-03T05:50:32ZengWileyJournal of Advanced Transportation0197-67292042-31952017-01-01201710.1155/2017/64958616495861Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic AssignmentMotohiro Fujita0Shinji Yamada1Shintaro Murakami2Department of Civil Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555, JapanNagoya Expressway Public Corporation, Nagoya, JapanNagoya Institute of Technology, Nagoya, Aichi, JapanDay-long origin-destination (OD) demand estimation for transportation forecasting is advantageous in terms of accuracy and reliability because it is not affected by hourly variations in the OD distribution. In this paper, we propose a method to estimate the time coefficient of day-long OD demand to estimate hourly OD demand and to predict hourly traffic for urban transportation planning of a large-scale road network that lacks discrete-time rich traffic data. The model proposed estimates the time coefficients from observed link flows given a proven day-long OD demand based on a bilevel formulation of the generalized least square and semidynamic traffic assignment (OD-modification approach). The OD-modification approach is formulated as a static user-equilibrium assignment with elastic demand, based on the residual demand at the end of each period. Our model does not require setting many parameters regarding the OD demand matrices and the discrete-time dynamic traffic assignments. Applying the model to large-scale road network demonstrates that it efficiently improves estimation accuracy because the 24-hour time coefficients of survey data are slightly biased and may be modified properly. In addition, the methods that partially relax the assumption of OD-modification approach and transform the estimated demand into demand based on departure time are examined.http://dx.doi.org/10.1155/2017/6495861 |
| spellingShingle | Motohiro Fujita Shinji Yamada Shintaro Murakami Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment Journal of Advanced Transportation |
| title | Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment |
| title_full | Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment |
| title_fullStr | Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment |
| title_full_unstemmed | Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment |
| title_short | Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment |
| title_sort | time coefficient estimation for hourly origin destination demand from observed link flow based on semidynamic traffic assignment |
| url | http://dx.doi.org/10.1155/2017/6495861 |
| work_keys_str_mv | AT motohirofujita timecoefficientestimationforhourlyorigindestinationdemandfromobservedlinkflowbasedonsemidynamictrafficassignment AT shinjiyamada timecoefficientestimationforhourlyorigindestinationdemandfromobservedlinkflowbasedonsemidynamictrafficassignment AT shintaromurakami timecoefficientestimationforhourlyorigindestinationdemandfromobservedlinkflowbasedonsemidynamictrafficassignment |