Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction
Traffic speed on freeways can be measured by two types of technologies, i.e. probe sensors and stationary sensors. Cross-validation is critical to ensure the consistency between heterogeneous measurements. A challenge lies in the mismatch of probe and stationary measurements in space and time, espec...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2019-09-01
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| Series: | International Journal of Transportation Science and Technology |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2046043019300152 |
| _version_ | 1797765755562885120 |
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| author | Jia Li Kenneth Perrine Lidong Wu C. Michael Walton |
| author_facet | Jia Li Kenneth Perrine Lidong Wu C. Michael Walton |
| author_sort | Jia Li |
| collection | DOAJ |
| description | Traffic speed on freeways can be measured by two types of technologies, i.e. probe sensors and stationary sensors. Cross-validation is critical to ensure the consistency between heterogeneous measurements. A challenge lies in the mismatch of probe and stationary measurements in space and time, especially when one of them is relatively sparse. Towards filling the gap, this paper presents a cross-validation method based on traffic state reconstruction. The proposed method is computationally simple and robust. This makes it ready to be implemented for large data sets without complicated tuning. We present analytical formulation of the proposed method and an analysis of its robustness property. We demonstrate the method using both simulation model and real-world freeway data. Results show that the method can effectively identify discrepancies between probe and stationary speed measurements. Keywords: Traffic monitoring, Traffic speed, Heterogeneous data, Cross-validation, Probe (mobile) sensing |
| first_indexed | 2024-03-12T20:15:36Z |
| format | Article |
| id | doaj.art-734fcc0deca449c0bb00197ecdfe6f28 |
| institution | Directory Open Access Journal |
| issn | 2046-0430 |
| language | English |
| last_indexed | 2024-03-12T20:15:36Z |
| publishDate | 2019-09-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | International Journal of Transportation Science and Technology |
| spelling | doaj.art-734fcc0deca449c0bb00197ecdfe6f282023-08-02T01:22:14ZengKeAi Communications Co., Ltd.International Journal of Transportation Science and Technology2046-04302019-09-0183290303Cross-validating traffic speed measurements from probe and stationary sensors through state reconstructionJia Li0Kenneth Perrine1Lidong Wu2C. Michael Walton3Department of Civil, Environmental, and Construction Engineering, Texas Tech University, United States; Corresponding author.Center for Transportation Research, University of Texas at Austin, United StatesDepartment of Computer Science, University of Texas at Tyler, United StatesDepartment of Civil, Architectural and Environmental Engineering, University of Texas at Austin, United StatesTraffic speed on freeways can be measured by two types of technologies, i.e. probe sensors and stationary sensors. Cross-validation is critical to ensure the consistency between heterogeneous measurements. A challenge lies in the mismatch of probe and stationary measurements in space and time, especially when one of them is relatively sparse. Towards filling the gap, this paper presents a cross-validation method based on traffic state reconstruction. The proposed method is computationally simple and robust. This makes it ready to be implemented for large data sets without complicated tuning. We present analytical formulation of the proposed method and an analysis of its robustness property. We demonstrate the method using both simulation model and real-world freeway data. Results show that the method can effectively identify discrepancies between probe and stationary speed measurements. Keywords: Traffic monitoring, Traffic speed, Heterogeneous data, Cross-validation, Probe (mobile) sensinghttp://www.sciencedirect.com/science/article/pii/S2046043019300152 |
| spellingShingle | Jia Li Kenneth Perrine Lidong Wu C. Michael Walton Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction International Journal of Transportation Science and Technology |
| title | Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction |
| title_full | Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction |
| title_fullStr | Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction |
| title_full_unstemmed | Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction |
| title_short | Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction |
| title_sort | cross validating traffic speed measurements from probe and stationary sensors through state reconstruction |
| url | http://www.sciencedirect.com/science/article/pii/S2046043019300152 |
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