Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems
Traffic congestion at a single intersection can propagate and thus affect adjacent intersections as well, potentially resulting in prolonged gridlock across an entire urban area. Despite numerous research efforts aimed at developing intelligent traffic signal control systems, urban areas continue to...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/1/124 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850072821909159936 |
|---|---|
| author | Tamrat D. Chala László T. Kóczy |
| author_facet | Tamrat D. Chala László T. Kóczy |
| author_sort | Tamrat D. Chala |
| collection | DOAJ |
| description | Traffic congestion at a single intersection can propagate and thus affect adjacent intersections as well, potentially resulting in prolonged gridlock across an entire urban area. Despite numerous research efforts aimed at developing intelligent traffic signal control systems, urban areas continue to experience traffic congestion. This paper presents a novel agent-based fuzzy traffic control system for multiple road intersections. The proposed system is designed to operate in a decentralized manner, with each intersection having its own agent (fuzzy controller) functioning concurrently. The intelligent fuzzy controller of the system can recognize emergency vehicles, assess the queue length and waiting time of vehicles, measure the distance of vehicles from intersections, and consider the cumulated waiting times of short vehicle queues. Two distinct types of agent-based intelligent fuzzy traffic control systems were implemented for comparison: one involving collaboration between an agent and its immediate neighboring agent(s) (where one intersection exchanges traffic data with its immediate neighboring intersection(s)), and the other implementing a non-collaborative agent-based intelligent fuzzy traffic control system (where the individual intersection has no direct communication). Following the experimental simulations, the results were compared with those of existing intelligent fuzzy traffic control systems that lack any module to calculate the distance of the vehicles from the intersection. The results demonstrated that the proposed agent-based system of controllers exhibited superior performance compared with the existing fuzzy controllers in terms of indicators such as average waiting time, fuel consumption, and CO<sub>2</sub> emissions. For instance, the proposed system reduced the average waiting time of vehicles at an intersection by 48.65% compared with the existing three-stage intelligent fuzzy traffic control system. In addition, a comparison was conducted between non-collaborating and collaborating agent-based intelligent fuzzy traffic control systems, where collaboration achieved better results than the non-collaborating system. In the simulation experiments, an interesting new feature emerged: despite any direct communication missing at multiple intersections, green waves evolved with time. This emergent feature suggests that fuzzy controllers have the potential to evolve and adapt to traffic complexity issues in urban environments when operating in an autonomous agent-based mode. This study demonstrates that agent-based fuzzy controllers can effectively communicate with one another to share traffic data and improve the overall system performance. |
| format | Article |
| id | doaj-art-51bcf64acacc4a2ab8a00938accbe159 |
| institution | DOAJ |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-51bcf64acacc4a2ab8a00938accbe1592025-08-20T02:47:00ZengMDPI AGMathematics2227-73902024-12-0113112410.3390/math13010124Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection SystemsTamrat D. Chala0László T. Kóczy1Department of Informatics, Széchenyi István University, Egyetem Square 1, 9026 Gyor, HungaryDepartment of Informatics, Széchenyi István University, Egyetem Square 1, 9026 Gyor, HungaryTraffic congestion at a single intersection can propagate and thus affect adjacent intersections as well, potentially resulting in prolonged gridlock across an entire urban area. Despite numerous research efforts aimed at developing intelligent traffic signal control systems, urban areas continue to experience traffic congestion. This paper presents a novel agent-based fuzzy traffic control system for multiple road intersections. The proposed system is designed to operate in a decentralized manner, with each intersection having its own agent (fuzzy controller) functioning concurrently. The intelligent fuzzy controller of the system can recognize emergency vehicles, assess the queue length and waiting time of vehicles, measure the distance of vehicles from intersections, and consider the cumulated waiting times of short vehicle queues. Two distinct types of agent-based intelligent fuzzy traffic control systems were implemented for comparison: one involving collaboration between an agent and its immediate neighboring agent(s) (where one intersection exchanges traffic data with its immediate neighboring intersection(s)), and the other implementing a non-collaborative agent-based intelligent fuzzy traffic control system (where the individual intersection has no direct communication). Following the experimental simulations, the results were compared with those of existing intelligent fuzzy traffic control systems that lack any module to calculate the distance of the vehicles from the intersection. The results demonstrated that the proposed agent-based system of controllers exhibited superior performance compared with the existing fuzzy controllers in terms of indicators such as average waiting time, fuel consumption, and CO<sub>2</sub> emissions. For instance, the proposed system reduced the average waiting time of vehicles at an intersection by 48.65% compared with the existing three-stage intelligent fuzzy traffic control system. In addition, a comparison was conducted between non-collaborating and collaborating agent-based intelligent fuzzy traffic control systems, where collaboration achieved better results than the non-collaborating system. In the simulation experiments, an interesting new feature emerged: despite any direct communication missing at multiple intersections, green waves evolved with time. This emergent feature suggests that fuzzy controllers have the potential to evolve and adapt to traffic complexity issues in urban environments when operating in an autonomous agent-based mode. This study demonstrates that agent-based fuzzy controllers can effectively communicate with one another to share traffic data and improve the overall system performance.https://www.mdpi.com/2227-7390/13/1/124autonomous agent-based systemcollaborative agent-based fuzzy controllermultiple road intersectionscalculated distance of vehiclesemerging green wave evolution |
| spellingShingle | Tamrat D. Chala László T. Kóczy Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems Mathematics autonomous agent-based system collaborative agent-based fuzzy controller multiple road intersections calculated distance of vehicles emerging green wave evolution |
| title | Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems |
| title_full | Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems |
| title_fullStr | Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems |
| title_full_unstemmed | Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems |
| title_short | Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems |
| title_sort | agent based intelligent fuzzy traffic signal control system for multiple road intersection systems |
| topic | autonomous agent-based system collaborative agent-based fuzzy controller multiple road intersections calculated distance of vehicles emerging green wave evolution |
| url | https://www.mdpi.com/2227-7390/13/1/124 |
| work_keys_str_mv | AT tamratdchala agentbasedintelligentfuzzytrafficsignalcontrolsystemformultipleroadintersectionsystems AT laszlotkoczy agentbasedintelligentfuzzytrafficsignalcontrolsystemformultipleroadintersectionsystems |