In modern society, private cars have become the first choice for many families because of their convenience and versatility. The volume of vehicles on the road is the basis of traffic accident and traffic congestion. In urban sector the traffic congestion is normally high due to the green light time interval at four road intersections. The traffic light control and time setting are basically timer control operation at current traffic control management system, this shows that, the current system is not intelligent so that there is still heavy traffic congestion. It is vital to implement routinely adjusted schedule as per the real-time position of vehicles at urban cross road intersection. Now, there are various detector systems for traffic monitoring, like Inductive Loop microwave radar, laser, infrared, ultrasonic, magnetometer and video image processing. But they have relevant weakness, such as high cost and complex technology. As a more and more widely used technology, image processing plays an important role in the management and control of intelligent transportation system. Image processing systems are based on motion detection of vehicles, wherein computer vision algorithms extract vehicles from traffic video data for traffic density estimations. This paper is an analysis on scheduling of traffic light of traffic management system using Fuzzy Control Algorithm. With the increase of the number of vehicles and population, it will also improve the traffic jam and the mood of people because of the cause of jam. Rather than previous technology, it will be low cost and simple, which can be adopted in every place as far as possible. MATLAB tool was used to figure out the variables impact on scheduling of traffic light at urban traffic intersection. The vehicle number, vehicle speed, lane length and vehicle type variables are identified and tested against vehicle driving for conclusion on traffic management performance. From findings the results were identified as the vehicle number, vehicle speed, and vehicle type have significant positive relationship with vehicle driving. However, the lane length did not significantly affect the vehicle driving. This indicates that the lane length is less important in scheduling of traffic light at urban traffic intersection.
Published in | International Journal of Transportation Engineering and Technology (Volume 7, Issue 3) |
DOI | 10.11648/j.ijtet.20210703.14 |
Page(s) | 85-91 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Fuzzy Control Algorithm, Vehicle Number, Vehicle Speed, Lane Length, Vehicle Type, Vehicle Driving, Scheduling
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APA Style
Ma Wen, Burra Venkata Durga Kumar. (2021). An Analysis on Scheduling of Traffic Light at Urban Traffic Intersection Using Fuzzy Control Algorithm. International Journal of Transportation Engineering and Technology, 7(3), 85-91. https://doi.org/10.11648/j.ijtet.20210703.14
ACS Style
Ma Wen; Burra Venkata Durga Kumar. An Analysis on Scheduling of Traffic Light at Urban Traffic Intersection Using Fuzzy Control Algorithm. Int. J. Transp. Eng. Technol. 2021, 7(3), 85-91. doi: 10.11648/j.ijtet.20210703.14
AMA Style
Ma Wen, Burra Venkata Durga Kumar. An Analysis on Scheduling of Traffic Light at Urban Traffic Intersection Using Fuzzy Control Algorithm. Int J Transp Eng Technol. 2021;7(3):85-91. doi: 10.11648/j.ijtet.20210703.14
@article{10.11648/j.ijtet.20210703.14, author = {Ma Wen and Burra Venkata Durga Kumar}, title = {An Analysis on Scheduling of Traffic Light at Urban Traffic Intersection Using Fuzzy Control Algorithm}, journal = {International Journal of Transportation Engineering and Technology}, volume = {7}, number = {3}, pages = {85-91}, doi = {10.11648/j.ijtet.20210703.14}, url = {https://doi.org/10.11648/j.ijtet.20210703.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtet.20210703.14}, abstract = {In modern society, private cars have become the first choice for many families because of their convenience and versatility. The volume of vehicles on the road is the basis of traffic accident and traffic congestion. In urban sector the traffic congestion is normally high due to the green light time interval at four road intersections. The traffic light control and time setting are basically timer control operation at current traffic control management system, this shows that, the current system is not intelligent so that there is still heavy traffic congestion. It is vital to implement routinely adjusted schedule as per the real-time position of vehicles at urban cross road intersection. Now, there are various detector systems for traffic monitoring, like Inductive Loop microwave radar, laser, infrared, ultrasonic, magnetometer and video image processing. But they have relevant weakness, such as high cost and complex technology. As a more and more widely used technology, image processing plays an important role in the management and control of intelligent transportation system. Image processing systems are based on motion detection of vehicles, wherein computer vision algorithms extract vehicles from traffic video data for traffic density estimations. This paper is an analysis on scheduling of traffic light of traffic management system using Fuzzy Control Algorithm. With the increase of the number of vehicles and population, it will also improve the traffic jam and the mood of people because of the cause of jam. Rather than previous technology, it will be low cost and simple, which can be adopted in every place as far as possible. MATLAB tool was used to figure out the variables impact on scheduling of traffic light at urban traffic intersection. The vehicle number, vehicle speed, lane length and vehicle type variables are identified and tested against vehicle driving for conclusion on traffic management performance. From findings the results were identified as the vehicle number, vehicle speed, and vehicle type have significant positive relationship with vehicle driving. However, the lane length did not significantly affect the vehicle driving. This indicates that the lane length is less important in scheduling of traffic light at urban traffic intersection.}, year = {2021} }
TY - JOUR T1 - An Analysis on Scheduling of Traffic Light at Urban Traffic Intersection Using Fuzzy Control Algorithm AU - Ma Wen AU - Burra Venkata Durga Kumar Y1 - 2021/10/19 PY - 2021 N1 - https://doi.org/10.11648/j.ijtet.20210703.14 DO - 10.11648/j.ijtet.20210703.14 T2 - International Journal of Transportation Engineering and Technology JF - International Journal of Transportation Engineering and Technology JO - International Journal of Transportation Engineering and Technology SP - 85 EP - 91 PB - Science Publishing Group SN - 2575-1751 UR - https://doi.org/10.11648/j.ijtet.20210703.14 AB - In modern society, private cars have become the first choice for many families because of their convenience and versatility. The volume of vehicles on the road is the basis of traffic accident and traffic congestion. In urban sector the traffic congestion is normally high due to the green light time interval at four road intersections. The traffic light control and time setting are basically timer control operation at current traffic control management system, this shows that, the current system is not intelligent so that there is still heavy traffic congestion. It is vital to implement routinely adjusted schedule as per the real-time position of vehicles at urban cross road intersection. Now, there are various detector systems for traffic monitoring, like Inductive Loop microwave radar, laser, infrared, ultrasonic, magnetometer and video image processing. But they have relevant weakness, such as high cost and complex technology. As a more and more widely used technology, image processing plays an important role in the management and control of intelligent transportation system. Image processing systems are based on motion detection of vehicles, wherein computer vision algorithms extract vehicles from traffic video data for traffic density estimations. This paper is an analysis on scheduling of traffic light of traffic management system using Fuzzy Control Algorithm. With the increase of the number of vehicles and population, it will also improve the traffic jam and the mood of people because of the cause of jam. Rather than previous technology, it will be low cost and simple, which can be adopted in every place as far as possible. MATLAB tool was used to figure out the variables impact on scheduling of traffic light at urban traffic intersection. The vehicle number, vehicle speed, lane length and vehicle type variables are identified and tested against vehicle driving for conclusion on traffic management performance. From findings the results were identified as the vehicle number, vehicle speed, and vehicle type have significant positive relationship with vehicle driving. However, the lane length did not significantly affect the vehicle driving. This indicates that the lane length is less important in scheduling of traffic light at urban traffic intersection. VL - 7 IS - 3 ER -