Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data
Signal coordination is an effective measure to improve the traffic efficiency of urban road networks, and network partition is an important part of it. Existing studies have proposed indicators based on the characteristics of arterial geometry and traffic flow to determine adjacent intersections tha...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/atr/6594290 |
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| _version_ | 1849336613137547264 |
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| author | Yuxuan Sun Chunhui Yu Wanjing Ma |
| author_facet | Yuxuan Sun Chunhui Yu Wanjing Ma |
| author_sort | Yuxuan Sun |
| collection | DOAJ |
| description | Signal coordination is an effective measure to improve the traffic efficiency of urban road networks, and network partition is an important part of it. Existing studies have proposed indicators based on the characteristics of arterial geometry and traffic flow to determine adjacent intersections that are suitable for signal coordination. However, it is difficult to explicitly identify the benefits and thus the necessity of signal coordination with these indirect indicators. This study defines Intersection Coordination Index (ICI) to evaluate the potential effectiveness of arterial signal coordination. ICI explicitly considers signal timing plans at each intersection and implicitly considers the impacts of the characteristics of arterial geometry and traffic flow. An offset optimization model is formulated to calculate ICI based on sampled trajectories of connected vehicles (CVs). It is a MILP model and can be efficiently solved by existing solvers. To cope with the low penetration rate of CVs, sampled trajectories are aggregated during the same period across multiple cycles. Numerical studies show: the proposed model is adapted to the low penetration rate trajectory environment; the dispersion of arriving vehicles at the downstream intersection reduces the benefits of signal coordination; and ICI outperforms the benchmark indicators in terms of the average cost of delay. |
| format | Article |
| id | doaj-art-0642852f936e4738ab2bc75843cd28d9 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-0642852f936e4738ab2bc75843cd28d92025-08-20T03:44:55ZengWileyJournal of Advanced Transportation2042-31952025-01-01202510.1155/atr/6594290Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory DataYuxuan Sun0Chunhui Yu1Wanjing Ma2The Key Laboratory of Road and Traffic Engineering of the Ministry of EducationThe Key Laboratory of Road and Traffic Engineering of the Ministry of EducationThe Key Laboratory of Road and Traffic Engineering of the Ministry of EducationSignal coordination is an effective measure to improve the traffic efficiency of urban road networks, and network partition is an important part of it. Existing studies have proposed indicators based on the characteristics of arterial geometry and traffic flow to determine adjacent intersections that are suitable for signal coordination. However, it is difficult to explicitly identify the benefits and thus the necessity of signal coordination with these indirect indicators. This study defines Intersection Coordination Index (ICI) to evaluate the potential effectiveness of arterial signal coordination. ICI explicitly considers signal timing plans at each intersection and implicitly considers the impacts of the characteristics of arterial geometry and traffic flow. An offset optimization model is formulated to calculate ICI based on sampled trajectories of connected vehicles (CVs). It is a MILP model and can be efficiently solved by existing solvers. To cope with the low penetration rate of CVs, sampled trajectories are aggregated during the same period across multiple cycles. Numerical studies show: the proposed model is adapted to the low penetration rate trajectory environment; the dispersion of arriving vehicles at the downstream intersection reduces the benefits of signal coordination; and ICI outperforms the benchmark indicators in terms of the average cost of delay.http://dx.doi.org/10.1155/atr/6594290 |
| spellingShingle | Yuxuan Sun Chunhui Yu Wanjing Ma Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data Journal of Advanced Transportation |
| title | Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data |
| title_full | Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data |
| title_fullStr | Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data |
| title_full_unstemmed | Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data |
| title_short | Effectiveness Evaluation of Signal Coordination Based on Spatially Sparse Trajectory Data |
| title_sort | effectiveness evaluation of signal coordination based on spatially sparse trajectory data |
| url | http://dx.doi.org/10.1155/atr/6594290 |
| work_keys_str_mv | AT yuxuansun effectivenessevaluationofsignalcoordinationbasedonspatiallysparsetrajectorydata AT chunhuiyu effectivenessevaluationofsignalcoordinationbasedonspatiallysparsetrajectorydata AT wanjingma effectivenessevaluationofsignalcoordinationbasedonspatiallysparsetrajectorydata |