Pedestrian-Safety-Aware Traffic Light Control Strategy for Urban Traffic Congestion Alleviation

Author(s):  
Yi Zhang ◽  
Yicheng Zhang ◽  
Rong Su
2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231

Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).


2019 ◽  
Vol 3 (1) ◽  
pp. 1-10
Author(s):  
Paula Juniana ◽  
Lukman Hakim

Traffic congestion is a common occurrence in Indonesia. Traffic congestion is increasing from year to year, causing many things to happen, such as longer travel time, increased transportation costs, serious disruptions to transporting products, decreasing levels of work productivity, and wasteful use of labor energy. Congestion is also caused by a traffic light control system that is made with a fixed time so it can not detect the density of certain paths. Traffic lights in Indonesia, frequent damage that makes the density and the flow of his road vehicles can not be controlled. From these problems, conducted research to reduce the density of vehicles using infrared sensors and see the waiting time of the vehicle when the red light. The traffic light control system will use Fuzzy Logic Mamdani method. In Mamdani method by applying fuzzy into each variable and will be done matching between rule with condition which fulfilled to determine contents of output to be executed by prototype. This congestion detection will help the system in controlling the green light time by looking at stable, medium, and traffic jams. When the bottleneck starts to detect, the prototype will add a green light time according to the condition that is 0 seconds, 5 seconds, 10 seconds, and 15 seconds. However, when the streets are not detected by traffic jams, the green light will be back to normal at 15 seconds without additional time


KOMTEKINFO ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 176-185
Author(s):  
Dentik Karyaningsih ◽  
Robby Rizky

Traffic jams are a common sight that can be seen in almost all major cities in Indonesia. One of them is in Rangkasbitung City, Lebak Regency. This happens because the number of vehicles continues to increase. The traffic light control system implemented in Indonesia is a static preset time because the time of each phase is predetermined. This type of control system is still not effective in overcoming traffic congestion, especially at certain peak traffic jams. By using the Mamdani fuzzy logic system, it is possible to implement the human mindset into a system. Some rules can be set out in the fuzzy logic controller. The purpose of this study is to design a traffic light control system using fuzzy inference that regulates traffic based on its density. The data used are observations made at the research site. The conclusion of this study is to explain that the fuzzy mamdani method can solve existing problems in traffic congestion in Rangkasbitung City, Lebak Regency, Banten Province


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