Intelligent Transportation Design Based on Iterative Learning
Most of the existing traffic optimization control methods are based on accurate mathematical models. As an uncertain and complex system, the urban traffic system faces difficulty in accurately calibrating the model parameters. Therefore, the existing methods become very difficult in the actual appli...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2022/5027412 |
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| _version_ | 1832548389867225088 |
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| author | Yinpu Ma Kai Liu |
| author_facet | Yinpu Ma Kai Liu |
| author_sort | Yinpu Ma |
| collection | DOAJ |
| description | Most of the existing traffic optimization control methods are based on accurate mathematical models. As an uncertain and complex system, the urban traffic system faces difficulty in accurately calibrating the model parameters. Therefore, the existing methods become very difficult in the actual application process. Based on the massive data contained in the urban traffic system and the repetitive characteristics of traffic flow, this paper proposes a hierarchical traffic signal control method for urban road network based on iterative learning control. The simulation results show that the algorithm can achieve better control effect and can solve the problem of urban traffic congestion more effectively than traditional traffic control methods. |
| format | Article |
| id | doaj-art-3e2c526c73ff4958866694ade3be0bc3 |
| institution | Kabale University |
| issn | 2314-4785 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-3e2c526c73ff4958866694ade3be0bc32025-02-03T06:14:11ZengWileyJournal of Mathematics2314-47852022-01-01202210.1155/2022/5027412Intelligent Transportation Design Based on Iterative LearningYinpu Ma0Kai Liu1School of Mechanical EngineeringSiemens Mobility Technologies (Beijing) Co., Ltd.Most of the existing traffic optimization control methods are based on accurate mathematical models. As an uncertain and complex system, the urban traffic system faces difficulty in accurately calibrating the model parameters. Therefore, the existing methods become very difficult in the actual application process. Based on the massive data contained in the urban traffic system and the repetitive characteristics of traffic flow, this paper proposes a hierarchical traffic signal control method for urban road network based on iterative learning control. The simulation results show that the algorithm can achieve better control effect and can solve the problem of urban traffic congestion more effectively than traditional traffic control methods.http://dx.doi.org/10.1155/2022/5027412 |
| spellingShingle | Yinpu Ma Kai Liu Intelligent Transportation Design Based on Iterative Learning Journal of Mathematics |
| title | Intelligent Transportation Design Based on Iterative Learning |
| title_full | Intelligent Transportation Design Based on Iterative Learning |
| title_fullStr | Intelligent Transportation Design Based on Iterative Learning |
| title_full_unstemmed | Intelligent Transportation Design Based on Iterative Learning |
| title_short | Intelligent Transportation Design Based on Iterative Learning |
| title_sort | intelligent transportation design based on iterative learning |
| url | http://dx.doi.org/10.1155/2022/5027412 |
| work_keys_str_mv | AT yinpuma intelligenttransportationdesignbasedoniterativelearning AT kailiu intelligenttransportationdesignbasedoniterativelearning |