Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment
In this paper, a self-adaptive, two-stage fuzzy controller is established to realize the real-time online optimization of traffic signal timing plan, which takes multimodels of transportation as the research object to analyze the reliability of the control system at the isolated urban intersection....
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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 Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/6007485 |
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| _version_ | 1832564589553778688 |
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| author | Mingzhi Wang Xianyu Wu He Tian Jie Lin Meimei He Liuqing Ding |
| author_facet | Mingzhi Wang Xianyu Wu He Tian Jie Lin Meimei He Liuqing Ding |
| author_sort | Mingzhi Wang |
| collection | DOAJ |
| description | In this paper, a self-adaptive, two-stage fuzzy controller is established to realize the real-time online optimization of traffic signal timing plan, which takes multimodels of transportation as the research object to analyze the reliability of the control system at the isolated urban intersection. In this system, the first stage calculates traffic urgency degree for all red phases and selects the red phase with maximum traffic urgency degree as the next green phase. The second stage determines whether to extend or terminate the current signal phase. Aiming at the problems of the parameters of membership functions empirical settings and insufficient response to the real-time fluctuation in traffic flow, the controller introduces an improved hybrid genetic algorithm to solve it and enable the controller to self-learn. Finally, a microsimulation platform is constructed based on the VISSIM and Python language to evaluate the efficiency and reliability of the controller under complex actual traffic conditions. Results showed that the average delay time per vehicle is reduced by 14.59%, while the average number of stops per vehicle is reduced by 0.71% compared with the traditional control method. Results indicate that the traffic signal timing plan generated by the controller can efficiently improve the intersection traffic capacity and has good efficiency and reliability under the condition of medium saturation and unsteady flow. |
| format | Article |
| id | doaj-art-0a5d325a1d93477ab050b999d28de146 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-0a5d325a1d93477ab050b999d28de1462025-02-03T01:10:36ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/6007485Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic EnvironmentMingzhi Wang0Xianyu Wu1He Tian2Jie Lin3Meimei He4Liuqing Ding5Laboratory for Traffic and Transport Planning DigitalizationKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive TransportLaboratory for Traffic and Transport Planning DigitalizationKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive TransportKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive TransportKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive TransportIn this paper, a self-adaptive, two-stage fuzzy controller is established to realize the real-time online optimization of traffic signal timing plan, which takes multimodels of transportation as the research object to analyze the reliability of the control system at the isolated urban intersection. In this system, the first stage calculates traffic urgency degree for all red phases and selects the red phase with maximum traffic urgency degree as the next green phase. The second stage determines whether to extend or terminate the current signal phase. Aiming at the problems of the parameters of membership functions empirical settings and insufficient response to the real-time fluctuation in traffic flow, the controller introduces an improved hybrid genetic algorithm to solve it and enable the controller to self-learn. Finally, a microsimulation platform is constructed based on the VISSIM and Python language to evaluate the efficiency and reliability of the controller under complex actual traffic conditions. Results showed that the average delay time per vehicle is reduced by 14.59%, while the average number of stops per vehicle is reduced by 0.71% compared with the traditional control method. Results indicate that the traffic signal timing plan generated by the controller can efficiently improve the intersection traffic capacity and has good efficiency and reliability under the condition of medium saturation and unsteady flow.http://dx.doi.org/10.1155/2022/6007485 |
| spellingShingle | Mingzhi Wang Xianyu Wu He Tian Jie Lin Meimei He Liuqing Ding Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment Journal of Advanced Transportation |
| title | Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment |
| title_full | Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment |
| title_fullStr | Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment |
| title_full_unstemmed | Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment |
| title_short | Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment |
| title_sort | efficiency and reliability analysis of self adaptive two stage fuzzy control system in complex traffic environment |
| url | http://dx.doi.org/10.1155/2022/6007485 |
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