A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment
Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajector...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/9945398 |
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| _version_ | 1832550481133568000 |
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| author | Yangsheng Jiang Bin Zhao Meng Liu Zhihong Yao |
| author_facet | Yangsheng Jiang Bin Zhao Meng Liu Zhihong Yao |
| author_sort | Yangsheng Jiang |
| collection | DOAJ |
| description | Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption. |
| format | Article |
| id | doaj-art-4536d12358934fdcba5b0e2a0d8b0b91 |
| 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-4536d12358934fdcba5b0e2a0d8b0b912025-02-03T06:06:39ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/99453989945398A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random EnvironmentYangsheng Jiang0Bin Zhao1Meng Liu2Zhihong Yao3School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, ChinaSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, ChinaSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, ChinaSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, ChinaConnected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption.http://dx.doi.org/10.1155/2021/9945398 |
| spellingShingle | Yangsheng Jiang Bin Zhao Meng Liu Zhihong Yao A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment Journal of Advanced Transportation |
| title | A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment |
| title_full | A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment |
| title_fullStr | A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment |
| title_full_unstemmed | A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment |
| title_short | A Two-Level Model for Traffic Signal Timing and Trajectories Planning of Multiple CAVs in a Random Environment |
| title_sort | two level model for traffic signal timing and trajectories planning of multiple cavs in a random environment |
| url | http://dx.doi.org/10.1155/2021/9945398 |
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