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Journal articles on the topic 'Traffic lights'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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Gregory, Richard L. "Traffic Lights." Perception 21, no. 4 (August 1992): 423–26. http://dx.doi.org/10.1068/p210423.

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Jung, Frank. "Traffic Lights." ATZ worldwide 126, no. 7-8 (July 5, 2024): 3. http://dx.doi.org/10.1007/s38311-024-1953-0.

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Ashir, Mohammed, and Karl Marlowe. "Traffic Lights." Clinical Governance: An International Journal 14, no. 3 (August 7, 2009): 226–35. http://dx.doi.org/10.1108/14777270910976166.

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Hosseinyalmdary, S., and A. Yilmaz. "TRAFFIC LIGHT DETECTION USING CONIC SECTION GEOMETRY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 191–200. http://dx.doi.org/10.5194/isprsannals-iii-1-191-2016.

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Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the pose of the traffic lights with respect to the camera. Our approach can detect multiple traffic lights in the scene, it also is able to detect the traffic lights in the absence of prior knowledge, and detect the traffics lights as far as 70 meters. The proposed approach has been evaluated for different scenarios and the results show that the use of stereo cameras significantly improves the accuracy of the traffic lights detection and pose estimation.

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Lu, Xingyu, Li Fei, Huibing Zhu, Wangjun Cheng, and Zijie Wang. "Modeling traffic flow in work zone sections considering the effect of traffic lights." International Journal of Modern Physics C 32, no. 09 (May 7, 2021): 2150113. http://dx.doi.org/10.1142/s0129183121501138.

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Based on the two-lane highway traffic model with a work zone presented previously, a new traffic model with a work zone under the control of traffic lights is proposed. The length of the waiting area for vehicles before traffic lights is recommended cautiously after numerical simulation. The relationship between the vehicles’ queuing time and the cycle of traffic lights is studied, and the cycle time of traffic lights is obtained also considering people’s endurance to the red light. It is found that the traffic lights are effective to ease the traffic congestion in the work zone when the density is medium, and help to eliminate the inducement of traffic accidents. On the other hand, the simulation results show that traffic lights are not needed in the work zone when the traffic density is small. It indicates that the traffic flow in the work zone area can be optimized by using appropriate traffic management when the traffic density varies.

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Yeh, Tien-Wen, Huei-Yung Lin, and Chin-Chen Chang. "Traffic Light and Arrow Signal Recognition Based on a Unified Network." Applied Sciences 11, no. 17 (August 31, 2021): 8066. http://dx.doi.org/10.3390/app11178066.

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We present a traffic light detection and recognition approach for traffic lights that utilizes convolutional neural networks. We also introduce a technique for identifying arrow signal lights in multiple urban traffic environments. For detection, we use map data and two different focal length cameras for traffic light detection at various distances. For recognition, we propose a new algorithm that combines object detection and classification to recognize the light state classes of traffic lights. Furthermore, we use a unified network by sharing features to decrease computation time. The results reveal that the proposed approach enables high-performance traffic light detection and recognition.

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Kawai, Satoru. "Road Traffic Lights." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 71, no. 3 (1987): 204–9. http://dx.doi.org/10.2150/jieij1980.71.3_204.

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Sinha, Roopak, Partha S. Roop, and Prakash Ranjitkar. "Virtual Traffic Lights+." Transportation Research Record: Journal of the Transportation Research Board 2381, no. 1 (January 2013): 73–80. http://dx.doi.org/10.3141/2381-09.

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Calabresi, Paolo, and Massimiliano Di Filippo. "Brain's traffic lights." Nature 466, no. 7305 (July 2010): 449. http://dx.doi.org/10.1038/466449a.

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A'isya, Nur Aulia Yusuf, Setyo Arifin Ajib, and Yuli Zulkifli Fitri. "Recent development of smart traffic lights." International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (March 1, 2021): 224–33. https://doi.org/10.11591/ijai.v10.i1.pp224-233.

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Increased traffic flow causes congestion, especially in large cities. Even though congestion is not unusual, traffic jams still result in very high economic and social losses. Several factors cause congestion, one of which is traffic lights. Therefore, a mechanism is needed so that traffic lights can intelligently and adaptively manage signal time allocation according to traffic flow conditions. A traffic light with this type of mechanism is known as a smart traffic light. Smart traffic light cycle settings can be grouped based on the traffic density, scenarios for emergency vehicles, and the interests of pedestrians. This paper analyzes the methods and technologies used in the development of smart traffic light technology from the perspective of these three situations as well as the development of smart traffic light technology in the future.

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Gui Sheng, Fang, and Zheng Gao An. "Research on a PLC Simulation Control Apparatus for Intelligent Traffic Lights." Advanced Materials Research 482-484 (February 2012): 805–11. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.805.

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In this paper an intelligent traffic light simulation control apparatus based on PLC and touch panel is developed. The device uses the touch panel as the master computer, PLC as the control kernel, the photoelectric switch and the sound sensor for vehicle detection components, to control the traffic lights and nixie tubes. Some conventional functions are realized to simulate the real road traffic lights control system, for example, alternatively working of the red lights, the yellow lights and the green lights, time countdown showing function, manual adjustment of the time, etc. Besides, the system can automatically adjust the time of traffic lights by the traffic flow in different directions, and can automatically change the working modes of the traffic lights by the current system time. The practical application shows that the device can not only promote students’ learning interests and improve students’ practical ability and creativity, but also can be used to control the real traffic lights if the traffic flow detectors are substituted by the earth inductors or the infrared cameras.

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Vidhyia, M., and S. Elayaraja. "Traffic Light Control System Using Raspberry-PI." Asian Journal of Electrical Sciences 5, no. 1 (May 5, 2016): 8–12. http://dx.doi.org/10.51983/ajes-2016.5.1.1970.

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Nowadays congestion in traffic is a serious issue. The traffic congestion can also be caused by large red light delays etc. The delay of respective light is hard coded in the traffic light and it is not dependent on traffic. In this paper we studied the optimization of traffic light controller in a city using microcontroller. The system tries to reduce possibilities of traffic jams, caused by traffic lights, to an extent. The system is based on raspberry-pi. The system contains IR transmitter and IR receiver which are mounted on either sides of roads respectively. Based on different vehicles count, the raspberrypi takes desicision and updates the traffic lights delays as a result. Thus based on vehicles count, raspberry-pi defines different ranges for traffic light delays and updates those accordingly. This recorded vehicle count data can be used in future to analyze traffic condition at respective traffic lights connected to the system. For appropriate analysis, the record data can be downloaded to the controller through communication between raspberry-pi and the computer then it will send correct signal into the LED lights . In future in this system can be used to inform people about different places traffic condition.

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Kononenko, Alla, and Liudmyla Nahrebelna. "“INTELLIGENT TRAFFIC LIGHT” – IMPACT ON ROAD TRAFFIC SAFETY." Avtoshliakhovyk Ukrayiny 3, no. 271 (December 30, 2022): 43–49. http://dx.doi.org/10.33868/0365-8392-2022-3-271-43-49.

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Road safety and measures to ensure it are a priority area of our state’s activity in view of the content of Article 3 of the Constitution of Ukraine, where a person, his life and health, safety are recognized as the highest social value in Ukraine. Reducing the number of accidents, reducing the severity of the consequences of traffic accidents, and especially reducing road accidents with fatalities to a minimum is the main task of specialists who are engaged in improving road safety. Traffic lights are one of the main components of road infrastructure, they are an optical signaling device designed to regulate traffic vehicles and pedestrians on roads and railway crossings. It is this device that regulates the movement of vehicles and pedestrians on the roadway and helps to avoid traffic accidents. Today, the traffic light has entered our lives so much that it is even difficult to imagine how it is possible to regulate traffic flows and ensure the safety of pedestrians on the roads without it. Adaptive or so-called “smart traffic lights” are considered the most modern type of traffic light regulation. Smart traffic lights are modern equipment that allows you to measure the intensity of traffic at the intersection and quickly, in real time, change regulation programs to reduce traffic jams. Artificial intelligence itself analyzes flow parameters, time and date, intensity to improve traffic. It is worth noting that despite the obvious advantages, smart traffic lights will not be able to completely solve the problem of traffic jams, but they will help to partially solve the problem of traffic accidents and support the ecological situation, since the level of emissions of harmful substances into the atmosphere is reduced thanks to the smooth movement of traffic. Keywords: street and road network, traffic jam, smart traffic light, traffic flow.

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Bali, Shweta, Tapas Kumar, and Shyam Sunder Tyagi. "Development and performance evaluation of object and traffic light recognition model by way of deep learning." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 3 (June 1, 2022): 1486. http://dx.doi.org/10.11591/ijeecs.v26.i3.pp1486-1494.

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Deep learning models have shown incredible achievement in the field of autonomous driving, covering different aspects ranging from recognizing traffic signs and traffic lighs, vehicle detection, license plate detection, pedestrian detection. Most of the algorithms perrform better when the traffic lights are bigger in size, but the performance degrades in case of small-sized traffic lights. In this paper, the main emphasis is on evaluating two most promising deep learning architectures: single shot detector (SSD) and faster region convolutinal network (Faster R-CNN) on “la route automatisée (LaRA) traffic light dataset” which contains small traffic lights as objects. The strengths and weaknesses are evaluated based on different parameters. The performance is compared in terms of mean average Precision (mAP@0.50) and average recall. The impact of data augmentation on the two architectures is also analyzed. ResNet50 V1 as feature extractor for Faster R-CNN achieved 96% mAP (mean average precision) which performed better than Original ResNet50 V1 Faster R-CNN pipeline. Also, different parameters such as batch size, learning rate and optimizer are tuned for detecting and classifying small traffic lights into different categories.

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Bali, Shweta, Tapas Kumar, and Shyam Sunder Tyagi. "Development and performance evaluation of object and traffic light recognition model by way of deep learning." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 3 (June 1, 2022): 1486–94. https://doi.org/10.11591/ijeecs.v26.i3.pp1486-1494.

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Deep learning models have shown incredible achievement in the field of autonomous driving, covering different aspects ranging from recognizing traffic signs and traffic lighs, vehicle detection, license plate detection, pedestrian detection. Most of the algorithms perrform better when the traffic lights are bigger in size, but the performance degrades in case of small-sized traffic lights. In this paper, the main emphasis is on evaluating two most promising deep learning architectures: single shot detector (SSD) and faster region convolutinal network (Faster R-CNN) on “la route automatisée (LaRA) traffic light dataset” which contains small traffic lights as objects. The strengths and weaknesses are evaluated based on different parameters. The performance is compared in terms of mean average Precision (mAP@0.50) and average recall. The impact of data augmentation on the two architectures is also analyzed. ResNet50 V1 as feature extractor for Faster R-CNN achieved 96% mAP (mean average precision) which performed better than Original ResNet50 V1 Faster R-CNN pipeline. Also, different parameters such as batch size, learning rate and optimizer are tuned for detecting and classifying small traffic lights into different categories.

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Amin, Reuel. "Traffix : Efficient Traffic Control using IoT." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (April 27, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem31872.

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This paper aims to alleviate traffic congestion brought on by antiquated, ineffective traffic management systems that are based on a predefined countdown. Long red light delays are the result of these traditional systems, which have a predefined countdown regardless of the actual traffic on a given road. Our system makes sure that time set for the traffic lights reflects the traffic density in real time, which ensures efficient use of time. In order to do this, we first compute the traffic density, which is ascertained by combining image processing methods along with the use of ultrasonic sensors. The Raspberry Pi then processes this data and then manages the time set for the traffic light. Furthermore, the use of SQL Alchemy ensures that this processed information is stored to the cloud, where it may be utilized in events of sensor failure or system malfunction. Index Terms—Image Processing, Raspberry Pi, Traffic Congestion, Ultrasonic sensors

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Faraj, Mohammed Abdulmaged, and Najmadin Wahid Boskany. "Intelligent Traffic Congestion Control System using Machine Learning and Wireless Network." UHD Journal of Science and Technology 4, no. 2 (December 10, 2020): 123–31. http://dx.doi.org/10.21928/uhdjst.v4n2y2020.pp123-131.

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Traffic congestion has become a big problem for most people because it increases noise, air pollution, and wasting time. Current normal traffic light system is not enough to manage the traffic problematic congestions because they operate on a fixed-time length plan. In recent years, internet of things led to introducing new models of intelligent traffic light systems; by utilizing different techniques such as predictive-based model, radiofrequency identification, and ultrasonic-based model. The most essential one of these techniques is depends of image processing and microcontroller communications. In this paper, we propose an intelligent, low cost, and efficient microcontroller circuit-based system for controlling cars in traffic light. This system can manage car traffics smarter than traditional approaches, it is capable to dynamically adjust timings of traffic signal. It can rapidly respond to traffic conditions to reduce traffic congestion. For implementing this system, a server, microcontroller board, cameras, as hardware and wireless network between traffic lights as infrastructure for communication are used. The system uses machine learning technique (i.e.,Yolov3 model and OpenCV) for decision depending on existence of emergency cars and number of cars. The experiment results show higher accuracy in managing traffic lights and recognizing the emergency cars.

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Aulia Yusuf, A’isya Nur, Ajib Setyo Arifin, and Fitri Yuli Zulkifli. "Recent development of smart traffic lights." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (March 1, 2021): 224. http://dx.doi.org/10.11591/ijai.v10.i1.pp224-233.

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Increased traffic flow causes congestion, especially in large cities. Even though congestion is not unusual, traffic jams still result in very high economic and social losses. Several factors cause congestion, one of which is traffic lights. Therefore, a mechanism is needed so that traffic lights can intelligently and adaptively manage signal time allocation according to traffic flow conditions. A traffic light with this type of mechanism is known as a smart traffic light. Smart traffic light cycle settings can be grouped based on the traffic density, scenarios for emergency vehicles, and the interests of pedestrians. This paper analyzes the methods and technologies used in the development of smart traffic light technology from the perspective of these three situations as well as the development of smart traffic light technology in the future.

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Asry, Asyraful Insan, Lutfi Lutfi, Asmar Umar, and Rahmat Ahmad. "Monitoring System for Traffic Light Lamp Damage using BLYNK Application Based on IOT ESP32." Jurnal Teknologi Transportasi dan Logistik 5, no. 1 (June 30, 2024): 59–66. http://dx.doi.org/10.52920/jttl.v5i1.230.

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The performance of traffic lights often encounters issues such as lights being out or other malfunctions, which can result in erratic traffic patterns and even total gridlock at the same intersection, potentially leading to accidents among drivers. Therefore, it is crucial to design a monitoring system for traffic light malfunctions using the Blynk application based on IoT ESP32. This system aims to facilitate technicians in monitoring the condition of traffic lights in case of malfunctions across all lanes. It utilizes an ESP32 microcontroller, LED lights or traffic lights, resistors as converters, and the Blynk application as a monitoring tool. From the testing of the prototype device, it was found that the average values for red light were ADC 1.367, voltage 1.10 volts, and current 5.01 mA. For yellow light, the values were ADC 1.265, voltage 1.02 volts, and current 4.63 mA. As for green light, the values were ADC 1.283, voltage 1.03 volts, and current 4.70 mA. The average delays for red, yellow, and green lights were 2 seconds, 2 seconds, and 5 seconds respectively, with the green light flashing three times for 0.5 seconds each time for all lanes.

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Wardani, Rizal Dwi. "The Application of Number Theory to Determine Congruence in Traffic Lights." BAREKENG: Jurnal Ilmu Matematika dan Terapan 13, no. 1 (March 13, 2019): 047–52. http://dx.doi.org/10.30598/barekengvol13iss1pp047-052ar697.

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In everyday life many number theories are often used to solve problems. In this paper we will discuss the application of number theory in testing the suitability of traffic lights. Testing uses the Euclidean theorem which is part of number theory. Number theory as a theoretical basis for exposure to traffic light congruence. This paper presents a calculation of traffic intersections to determine the suitability of traffic junction lights. The results in this paper show, if a traffic junction has congruence between traffic lights.

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KRISHNAN, SUREN, RAJAN THANGAVELOO, SHAPI-EE BIN ABD RAHMAN, and SIVA RAJA SINDIRAMUTTY. "Smart Ambulance Traffic Control System." Trends in Undergraduate Research 4, no. 1 (June 29, 2021): c28–34. http://dx.doi.org/10.33736/tur.2831.2021.

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The traffic lights control system is broadly implemented to track and control the flow of vehicles through the intersection of multiple roads. Nevertheless, the synchronization of traffic light system at adjacent junctions is an intricate issue given the different parameters involved. Existing traffic light control systems do not control many flows approaching the same junctions. This results in traffic jams and congestion at urban areas or major cities with high volume traffic consisting of various types of vehicles. This includes emergency ambulances travelling on the same traffic junction during peak hour traffic. Thus, an enhanced traffic light control system is imperative to provide a smooth and free flow for an ambulance on the way to its destination. The Smart Ambulance Traffic Control System proposed in this paper is an integrated system of traffic light control for emergency ambulance service. The traffic lights can be controlled in a timely and efficient manner every time an emergency ambulance is approaching. The Radio-Frequency Identification (RFID) is used as an instrument to communicate with traffic lights during traffic congestion. The emergency ambulance driver needs to activate the RFID tag to allow the detection of RFID readers to control the traffic light operation at the upcoming traffic light junctions. The traffic lights in the path of the ambulance are forced to be green to allow the emergency ambulance to pass through the junction with top priority. Immediately after the ambulance has passed the junction, the control system will reset and return to normal operations.

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Malim, Muhammad Rozi, Faridah Abdul Halim, and Sherey Sufreney Abd Rahman. "OPTIMISING TRAFFIC FLOW AT A SIGNALISED INTERSECTION USING SIMULATION." MALAYSIAN JOURNAL OF COMPUTING 4, no. 2 (October 10, 2019): 261. http://dx.doi.org/10.24191/mjoc.v4i2.6104.

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Traffic signal lights system is a signalling device located an intersection or pedestrian crossing to control the movement of traffic. The timing of traffic signal lights has attracted many researchers to study the problems involving traffic light management and looking for an inexpensive and effective solution that requires inexpensive changes in the infrastructures. A simple traffic lights system uses a pre-timed control setting based on the latest traffic data, and the setting could be manually changed. It is a common type of signal control and sometimes the setting was not correctly configured with the traffic data, thus leading to congestion at an intersection. Many mathematical strategies were applied to get an optimal setting. This study aims to model the traffic flow at Persiaran Kayangan and Persiaran Permai Intersection, Section 7, Shah Alam, as the case study, by using AnyLogic simulation software. The model was used to determine the best timings of traffic green lights that minimise the average time at the intersection and reduce traffic congestion. The findings showed that the best timings of traffic green lights for four directions at the intersection are 120 seconds, 75 seconds, 130 seconds and 100 seconds, respectively. These timings of green lights produced the lowest average time at the intersection (55.65 seconds).

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Fadyushin, Aleksey, and Anatoly Pistsov. "APPLICATION OF NEURAL NETWORK TECHNOLOGIES FOR CONTROL OF TRAFFIC LIGHTS." Transport engineering 2024, no. 4 (April 12, 2024): 57–65. http://dx.doi.org/10.30987/2782-5957-2024-4-57-65.

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The paper describes the use of an artificial neural network to determine the optimal parameters of traffic light regulation based on the intensity of traffic flow. At regulated intersections, there is an imbalance in the intensity of traffic flow, due to which one operation mode of traffic lights at an intersection may be ineffective. The study objective is to develop software for predicting the operating modes of traffic lights, taking into account the spatial and temporal unevenness of transport demand. Based on the simulation of traffic flows at one regulated intersection, the values of the average delay time were determined for different traffic light operating modes and traffic flow intensities, including turning ones. The artificial neural network was trained on data from 16 thousand simulations and tested on four thousand simulations. Using an artificial neural network to calculate the optimal operating mode of traffic lights reduces the delay time by 20-50% for two rush hours. A pre-trained artificial neural network can calculate the optimal operating mode of traffic lights for a specific regulated intersection in one second. The developed software can be used to implement an intelligent transport system in an automated traffic control system.

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Tristono, Tomi, Fardiana Karuniawati, Setiyo Daru Cahyono, Seno Aji, and Pradityo Utomo. "The Structural Complexity of Various Elements of Systems." Trends in Sciences 19, no. 4 (January 22, 2022): 2189. http://dx.doi.org/10.48048/tis.2022.2189.

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This paper is aimed to describe the structural complexity of the traffic light control system. The structural complexity represents an interrelationship indicator between the various elements functions. The traffic light control system has several additional features that are synchronized to the railway doorstop, and the time interval for the green signals is expanded. For determining the method of its structural complexity, the Petri net model is used. Three kinds of traffic lights models are explored, namely standard, Norwegian, and the Norwegian improvement. The study results indicate that the Norwegian traffic lights have the most complex structure when regular implementation. The runner up is the Norwegian improvement. The most ideal is the standard traffic lights. Norwegian improvement is the most ideal when integrated with the railway doorstop and implemented extra green signals time interval. The Norwegian traffic light is the second. The standard traffic lights structural complexity fluctuates. It means that the Norwegian traffic light and its improvement are suitably used. Adding several features improve the structural complexity approaching the ideal system while extra controllers accompany each element. HIGHLIGHTS  The Petri net model can represent the structural complexity of a system The method that can measure the structural complexity becomes ideal for actual implementation The Norwegian traffic lights structural complexities and improvements are ideal for the systems synchronized to the railway and appropriate for systems using the extra green signal time intervals or other additional features  GRAPHICAL ABSTRACT

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Pan, Zebin. "Analysis of Sidewalk Traffic Lights Setting Modes Optimization." Communications in Humanities Research 45, no. 1 (August 27, 2024): 32–39. http://dx.doi.org/10.54254/2753-7064/45/20240059.

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There are often some problems with the traditional setting mode of traffic lights, especially on some non-main roads. The unreasonable setting of pedestrian traffic lights can easily lead to empty spaces for people and vehicles, waste resources, and increase the risks of traffic congestion, Although the push-button traffic lights improves traffic efficiency, there is still a waste of waiting time for pedestrians and vehicles due to the fixed setting of the traffic time. This article mainly studies the use of machine learning to solve the recognition, motion direction, and time models of people and vehicles, and optimize pedestrian traffic light signals. By identifying pedestrians and vehicles and allocating release signal time reasonably, the waiting time of pedestrians and vehicles crossing the road can be reduced, and traffic accidents can be minimized. The optimized traffic system is applied to sidewalks on non-main roads, it can replace the push-button traffic lights, reduce manual intervention, save construction costs, and improve traffic efficiency.

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Anindito, Benediktus, Slamet Winardi, and Moh Noor Al-Azam. "Traffic Light Signal Detector using Average Light Intensity Method." JURNAL MEDIA INFORMATIKA BUDIDARMA 4, no. 3 (July 20, 2020): 511. http://dx.doi.org/10.30865/mib.v4i3.2115.

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Electronic Traffic Law Enforcement (ETLE) is a way of using information technology to record a violation of traffic. This ETLE was developed to support security, order, and safety in traffic. Some cities or districts in Indonesia have started to apply this ETLE in several locations, which usually have traffic lights and frequent violations at these locations. In this paper, one of the elements in ETLE is tested, which is a traffic light signal detector, which will be used as a basis for whether a vehicle violates a traffic light or not. This detector uses a CCTV camera mounted on the location. It then analyzed the intensity of several image areas on the traffic lights in red, yellow, and green. From the test results, this method can determine the conditions of the traffic lights with 100% accuracy

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Arief, Muhammad, Eko Kustiawan, Suwandi Suwandi, and Deswan Royana. "Perancangan Lampu Lalu Lintas Dengan Led Bicolor Menggunakan Arduino." SUTET 12, no. 2 (January 9, 2023): 98–108. http://dx.doi.org/10.33322/sutet.v12i2.1851.

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The growth in the number of vehicles every year will have an impact on the number of vehicles on the road. Thus, road congestion will increasingly occur in big city areas. Traffic lights are one of the tools to prevent congestion at especially at road intersections by making motorists more orderly stop and walk according to the signal of the light on. The need for traffic lights will also increase along with the number of congestion points at road intersections. Conventional traffic lights use three sets of LED lights with each set of red, yellow and green lights. Along with the development of technology, a Bicolor LED lamp was created which has two basic colors, namely red and green. With these conditions, the author is interested in developing a traffic light system with a one-package light system using Bicolor LED lights using an Arduino UNO R3 mockup. One Bicolor LED used will have red, yellow, and green colors. In this development it is expected to produce a system that is cheaper in manufacture and operation.

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Yudanto, Adhitya Yoga, Marvin Apriyadi, and Kevin Sanjaya. "Optimalisasi Lampu Lalu Lintas dengan Fuzzy Logic." Jurnal ULTIMATICS 5, no. 2 (December 1, 2013): 58–62. http://dx.doi.org/10.31937/ti.v5i2.322.

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The traffic lights problem is already commonly found in large cities. The traffic lights are supposed to control the flow of the road, but sometimes causes a congestion. This happens because the distribution of the time are all the same for all lines, without seeing the condition of the density of each lane. There’s one effort that can be done to overcome this problem, is to create a traffic light control system. With this system, the congestion that occurs around the traffic lights can be reduced. This system is using fuzzy logic. Fuzzy logic is one of computer science that studies about the value of truth that worth a lot. For example, a air conditioning system control subway Sendai in Japan. As for making a traffic light control system, the author using Fuzzy Inference System (FIS) that already exist in the application of MATLAB R2013a with Mamdani method. Index Terms —fuzzy logic, traffic lights, MATLAB.

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Zhang, Zitai. "Design of a Crossroad Traffic Light System." Highlights in Science, Engineering and Technology 97 (May 28, 2024): 29–39. http://dx.doi.org/10.54097/gvt3cd17.

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Nowadays, the situation of traffic jams is gradually increasing, and the demand for intelligent traffic lights is increasing as well. This paper designs a crossroad traffic light based on sequential logic using NI Multisim 14.0 virtual simulation software. The design includes: using 555 timer to build a second pulse oscillator circuit which outputs clock signal. Using 74LS169 counting chip to build timing circuit. Set up state control with 74LS74D trigger. Using nixie tubes and 74LS47 decoder chips to build the timing display circuit. Finally, logic gate and LED lights are used to build the display circuit of traffic lights. Next, how to design intelligent traffic lights is discussed based on this design combined with image monitoring technology. The feedback bit of image processing technology is added to the designed circuit, so that the circuit can change the green light duration with the traffic flow, and the designed circuits are also becoming smarter.

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Sendow, Ezra Shalom, Murni Sulistyaningsih, and Jorry F. Monoarfa. "Optimasi Waktu Tunggu Lampu Lalu Lintas dengan Mengaplikasikan Teori Graf dan Metode Webster." Journal on Education 6, no. 1 (June 7, 2023): 2272–84. http://dx.doi.org/10.31004/joe.v6i1.3240.

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Mobility in the city of Manado is a trigger for the occurrence of traffic volume density, leading to congestion at several points, particularly at intersections. The Toar-Lumimuut intersection is one such vulnerable location where congestion often occurs, despite the presence of traffic lights controlling the flow of vehicles. In fact, many drivers still have to wait for the red light more than once at the Toar-Lumimuut intersection. Based on these findings, it indicates that the waiting time for traffic lights at the Toar-Lumimuut intersection is still inefficient. This study aims to determine the synchronized waiting time for traffic lights according to the traffic situation, in order to achieve a more optimal waiting time for traffic lights. This problem can be addressed using graph theory and the Webster method. The research yielded results, with the optimum cycle time increasing to 285 seconds, accompanied by an increase in green light duration and a decrease in red light duration as a percentage for each road segment. Therefore, the research concludes that this provides a more effective waiting duration.

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Binoua, H., H. Ez-Zahraouy, A. Khallouk, and N. Lakouari. "Carbon dioxide emission in a single-lane cellular automaton model with a series of traffic lights." International Journal of Modern Physics C 31, no. 11 (September 30, 2020): 2050154. http://dx.doi.org/10.1142/s0129183120501545.

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In this paper, we propose a cellular automaton model to simulate traffic flow controlled by a series of traffic lights. The synchronized traffic light and the green wave light strategies were investigated. The spatiotemporal diagrams, energy dissipation, and CO2 emission of the system were presented. Our simulations are conducted to clarify the difference between both strategies and their effects on the traffic flow and the CO2 emission. We found that the traffic flow depends mainly on the strategy used for managing the traffic lights as well as on the parameters of the traffic lights, namely the cycle length, the number of traffic lights and the length of the system. The fundamental diagram has barely the same characteristics for both methods and it depends on the combination of the parameters of the system. We find that the green wave is more convenient for the management of a series of traffic lights than the synchronized control strategy in terms of throughput, especially for large-sized systems. Unlike in terms of CO2 emission and energy dissipation, both control strategies outperform each other depending on the density regions and the parameters of the system. Finally, we investigate the effect of both cycles (i.e. red and green) for the synchronized control method on the CO2 emission. It is found that the green cycle generates often a series of acceleration events that increase CO2 emission.

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Wu, Wen Liang. "Design of Intelligent Traffic Light Control System Based on Multi CPU." Applied Mechanics and Materials 716-717 (December 2014): 1562–66. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.1562.

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The intelligent traffic light control is the core problem in the intelligent traffic research field, in order to solve this problem, the intelligent traffic light control system is proposed based on multi CPU. In a multi processor system, aiming at the intelligent traffic light, the reasonable control is taken. In the intelligent traffic light control system, the related principles of multi processor system design and shared memory are elaborated in detail. The BP neural network self-tuning PID control algorithm is applied in the traffic lights control process, reasonable control of traffic lights is obtained. The experiment results show that the principle is applied in the intelligent traffic light control system, it can greatly improve the control accuracy, so it can meet the actual demand of intelligent traffic management.

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Maulinda, Vika, Syifa Salsabilah, and Zanindra Primahmudika. "EFEKTIVITAS KEBIJAKAN PENGGUNAAN LAMPU LALU LINTAS DALAM MENGATASI KEMACETAN DI KOTA CIMAHI." JIA: Jurnal Ilmiah Administrasi 10, no. 2 (October 10, 2022): 74–80. http://dx.doi.org/10.55678/jia.v10i2.713.

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The number of vehicles continues to increase in line with economic growth, while on the other hand the growth of traffic infrastructure is not as high as the growth in the number of vehicles and community mobility. The existence of traffic lights that do not work is one of the causes of congestion at several Cimahi intersection points, it is very unfortunate when public facilities do not function optimally and are used by certain people who want to take advantage. The author in this study used a qualitative approach with a case study method. This qualitative approach was chosen by the researcher because by using a qualitative approach with the case study method, the researcher could describe in more depth the study of the effectiveness of the traffic light policy that actually happened in the field. The purpose of this study was to analyze the effectiveness of the use of traffic lights that did not work at several points in Cimahi City. The results of this study indicate that the policy regarding the use of traffic lights in Cimahi City is quite appropriate considering the use of traffic lights is vital for the regularity of traffic flow in Cimahi City, but unfortunately there are several points where traffic lights do not function to make traffic flow. uncontrollable and experiencing traffic jams because there is no budget to repair the dead traffic lights. Keywords: Effectiveness, Traffic, Community Mobility

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Gershenson, Carlos. "Self-organizing Traffic Lights." Complex Systems 16, no. 1 (March 15, 2005): 29–53. http://dx.doi.org/10.25088/complexsystems.16.1.29.

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Steering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The disadvantage of this lies in the fact that traffic densities and configurations change constantly. Traffic seems to be an adaptation problem rather than an optimization problem. We propose a simple and feasible alternative, in which traffic lights self-organize to improve traffic flow. We use a multi-agent simulation to study three self-organizing methods, which are able to outperform traditional rigid and adaptive methods. Using simple rules and no direct communication, traffic lights are able to self-organize and adapt to changing traffic conditions, reducing waiting times, number of stopped cars, and increasing average speeds.

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ITO, Shinya. "Developing Traffic Signal Lights." Journal of the Society of Mechanical Engineers 107, no. 1030 (2004): 696–97. http://dx.doi.org/10.1299/jsmemag.107.1030_696.

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Vannucchi, Alessandro M., and Paola Guglielmelli. "Traffic lights for ruxolitinib." Blood 130, no. 9 (August 31, 2017): 1075–77. http://dx.doi.org/10.1182/blood-2017-07-795880.

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Finch, Irene. "BEWARE TRAFFIC LIGHTS AHEAD." Nutrition & Food Science 86, no. 5 (May 1986): 15–16. http://dx.doi.org/10.1108/eb059135.

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Ferrer, Javier, José García-Nieto, Enrique Alba, and Francisco Chicano. "Intelligent Testing of Traffic Light Programs: Validation in Smart Mobility Scenarios." Mathematical Problems in Engineering 2016 (2016): 1–19. http://dx.doi.org/10.1155/2016/3871046.

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In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic lights requires a validation process of the generated solutions, since they can affect the mobility (and security) of millions of citizens. In this paper, we propose a validation strategy based on genetic algorithms and feature models for the automatic generation of different traffic scenarios checking the robustness of traffic light cycle programs. We have concentrated on an extensive urban area in the city of Malaga (in Spain), in which we validate a set of candidate cycle programs generated by means of four optimization algorithms: Particle Swarm Optimization for Traffic Lights, Differential Evolution for Traffic Lights, random search, and Sumo Cycle Program Generator. We can test the cycles of traffic lights considering the different states of the city, weather, congestion, driver expertise, vehicle’s features, and so forth, but prioritizing the most relevant scenarios among a large and varied set of them. The improvement achieved in solution quality is remarkable, especially forCO2emissions, in which we have obtained a reduction of 126.99% compared with the experts’ solutions.

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Yoneda, Keisuke, Akisuke Kuramoto, Naoki Suganuma, Toru Asaka, Mohammad Aldibaja, and Ryo Yanase. "Robust Traffic Light and Arrow Detection Using Digital Map with Spatial Prior Information for Automated Driving." Sensors 20, no. 4 (February 21, 2020): 1181. http://dx.doi.org/10.3390/s20041181.

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Traffic light recognition is an indispensable elemental technology for automated driving in urban areas. In this study, we propose an algorithm that recognizes traffic lights and arrow lights by image processing using the digital map and precise vehicle pose which is estimated by a localization module. The use of a digital map allows the determination of a region-of-interest in an image to reduce the computational cost and false detection. In addition, this study develops an algorithm to recognize arrow lights using relative positions of traffic lights, and the arrow light is used as prior spatial information. This allows for the recognition of distant arrow lights that are difficult for humans to see clearly. Experiments were conducted to evaluate the recognition performance of the proposed method and to verify if it matches the performance required for automated driving. Quantitative evaluations indicate that the proposed method achieved 91.8% and 56.7% of the average f-value for traffic lights and arrow lights, respectively. It was confirmed that the arrow-light detection could recognize small arrow objects even if their size was smaller than 10 pixels. The verification experiments indicate that the performance of the proposed method meets the necessary requirements for smooth acceleration or deceleration at intersections in automated driving.

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Liao, Zhuhua, Hao Xiao, Silin Liu, Yizhi Liu, and Aiping Yi. "Impact Assessing of Traffic Lights via GPS Vehicle Trajectories." ISPRS International Journal of Geo-Information 10, no. 11 (November 12, 2021): 769. http://dx.doi.org/10.3390/ijgi10110769.

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The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we propose a low-cost and fast traffic signal detection and impact assessment framework, which detects traffic lights from GPS trajectories and intersection features in a supervised way, and analyzes the impact range and time of traffic lights from intersection track data segments. The experimental results show that our approach gains the best AUC value of 0.95 under the ROC standard classification and indicates that the impact pattern of traffic lights at intersections is high related to the travel rule of traffic participants.

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Yabuuchi, Kento, Masahiro Hirano, Taku Senoo, Norimasa Kishi, and Masatoshi Ishikawa. "Real-Time Traffic Light Detection with Frequency Patterns Using a High-Speed Camera." Sensors 20, no. 14 (July 20, 2020): 4035. http://dx.doi.org/10.3390/s20144035.

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LEDs are widely employed as traffic lights. Because most LED traffic lights are driven by alternative power, they blink at high frequencies, even at twice their frequencies. We propose a method to detect a traffic light from images captured by a high-speed camera that can recognize a blinking traffic light. This technique is robust under various illuminations because it can detect traffic lights by extracting information from the blinking pixels at a specific frequency. The method is composed of six modules, which includes a band-pass filter and a Kalman filter. All the modules run simultaneously to achieve real-time processing and can run at 500 fps for images with a resolution of 800 × 600. This technique was verified on an original dataset captured by a high-speed camera under different illumination conditions such as a sunset or night scene. The recall and accuracy justify the generalization of the proposed detection system. In particular, it can detect traffic lights with a different appearance without tuning parameters and without datasets having to be learned.

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Rahman, Gusairi, Nina Paramytha, and Muhamad Ariandi. "Traffic Light Control Prototype Using PIR Motion and Microcontroller-Based Ultrasonic Sensors." Jurnal Sains dan Teknologi Industri 20, no. 2 (March 15, 2023): 773. http://dx.doi.org/10.24014/sitekin.v20i2.22095.

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Traffic lights at crossroads help regulate the flow of vehicles so they can run smoothly and avoid congestion. One of the causes of traffic congestion is a traffic control light system that is not optimal because it still uses a fixed timer system, so the lights' duration is less efficient in its application. When the green light is on, the streets are deserted. But there is a traffic jam on another road. Therefore the concept of traffic light timing needs to be developed to get efficient timing. This study aims to create a traffic light control system that uses a PIR (Passive Infrared) motion sensor and an ultrasonic sensor based on the Arduino Mega2560 microcontroller based on the congestion level. The method used in this traffic control prototype is an experimental method of reading vehicle objects mounted with PIR sensors and ultrasonic sensors. This system can detect the movement of vehicles approaching a traffic light, measure the distance between the car and the traffic light, and set the timing of the light signal according to the level of congestion detected. This system has been tested using vehicle movement simulations brought closer to the PIR and ultrasonic sensors at different distances. The test results show the system can work properly and produce the light signal according to the detected traffic conditions. For its application to traffic lights in the future, it is feasible to help the traffic unit.

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Horvat, Rajko, Berislav Barišić-Jaman, Gordan Mršić, Igor Špoljarić, Andro Vrdoljak, and Ivan Pehar. "Method of Light Bulbs Analysis on Vehicles Damaged in Traffic Accidents." PROMET - Traffic&Transportation 22, no. 4 (March 1, 2012): 259–71. http://dx.doi.org/10.7307/ptt.v22i4.191.

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One of the measures to increase road traffic safety in Croatia is the introduction of obligatory use of daily lights on vehicles in road traffic during driving, regardless of the visibility and the time of day. The paper describes the new original technical and technological procedure of analysing automotive light bulbs in order to find the traces of glass particles of the broken glass balloon in the marginal cases of action of small inertia forces generated as result of a traffic accident. Investigations of light bulbs in traffic accidents had been rarely done before; therefore the subject of this scientific research is the analysis of the light bulb filament used in automobiles to light the road ahead and to give light signals, i.e. all the light signalling devices on the automobile using the new technical and technological procedure by means of SEM/EDX method. The scientific research has improved the investigation procedure in analysing the light bulbs on automobiles in determining whether at the moment of the traffic accident the regulatory lights were switched on. In determining the responsibility of participants for causing the traffic accident, such a fact may sometimes be of crucial significance. KEY WORDS: traffic accident, light bulb, technical and technological procedure, lights in traffic, microscope, molten glass particles

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Tian, Xiao Wei. "Road Traffic Light Control System Analysis and Design." Advanced Materials Research 1079-1080 (December 2014): 1002–5. http://dx.doi.org/10.4028/www.scientific.net/amr.1079-1080.1002.

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PLC as a kind of widely used industrial control equipment, is now increasingly used in traffic lights system, which can realize the automatic control of a traffic signal system, shortening the time of waiting vehicles, realize scientific management. In the design of this article, but also introducing EDA simulation crossroads traffic lights ablaze and vehicle traffic, very vividly shows the practical application of PLC in the traffic light system. This article is built on a typical intersection traffic research investigation, and PLC controller to realize intelligent control of road traffic signal lamp.

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HUANG, DING-WEI, and WEI-NENG HUANG. "OPTIMIZATION OF TRAFFIC LIGHTS AT CROSSROADS." International Journal of Modern Physics C 14, no. 05 (June 2003): 539–48. http://dx.doi.org/10.1142/s0129183103004784.

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We study the influence of traffic lights on the traffic flow in cities. The urban traffic is simulated in the cellular automata framework. Both the deterministic and probabilistic models are discussed. The effects of speed limit and stochastic noise are analyzed. The operation of a traffic light is characterized by two parameters: signal period and phase allocation. With two traffic lights on road, one more parameter is prescribed: synchronization shift. The results of tuning these parameters are presented in the fundamental diagram. We examine the traffic flow and discuss the choice of optimized setting in different density regions.

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Maslim, Martinus, B. Yudi Dwiandiyanta, and Nonety Viany Susilo. "Implementasi Metode Logika Fuzzy dalam Pembangunan Sistem Optimalisasi Lampu Lalu Lintas." Jurnal Buana Informatika 9, no. 1 (July 12, 2018): 11–20. http://dx.doi.org/10.24002/jbi.v9i1.1661.

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Traffic lights are the lights for controlling the flow of traffic which installed at crossroads. Traffic lights have an important role in regulating traffic especially crossroads. One way to overcome the traffic problem is to build a system of traffic optimization where each point of the intersection phase at the road signals automatically. This system implements fuzzy mamdani logic method with MOM (Mean of Maximum) defuzzification for this method is very simple, easy to understand and objective. The traffic optimization system can generate the maximum green light seconds at each intersection according to the officer's input. The input required by the system is the length of the set queue, the width of the regulated path, the length of the queue on the next path, and the width of the path on the regulated path. The output of this system is proven to help optimize the number of green light seconds according to crossroads conditions.

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Dimitrov, R. "DETERMINATION OF MAXIMUM VISIBILITY OF RAILWAY TRAFFIC LIGHTS." World of Transport and Transportation 16, no. 1 (February 28, 2018): 186–99. http://dx.doi.org/10.30932/1992-3252-2018-16-1-15.

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[For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version)].ABSTRACT The author examines the features of the light signaling system operating on the Bulgarian railways, designed to regulate movement of trains and ensure safety of people, goods and vehicles at railway crossings. On the basis of the heuristic approach, the maximum (limiting) range of visibility of signal lights of traffic lights is determined, a comparative analysis of data obtained in different weather conditions (including snow drifts), different time of day (day, night), at a different threshold of light sensitivity of the human eye depending on the strength of the light source (in particular, the specificity of mast and dwarf traffic lights) is suggested. Keywords: railway, light signaling, safety, traffic lights, visibility, range limits, heuristics, comparative analysis.

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VOLOSOVA, A. V., E. N. MATYUKHINA, and E. A. MOROZOV. "IMPLEMENTATION OF SECURE TRAFFIC LIGHT MANAGEMENT USING A NEUROMORPHIC COMPUTING BASE BASED ON FUZZY GRAPHS." Computational Nanotechnology 12, no. 1 (March 28, 2025): 11–16. https://doi.org/10.33693/2313-223x-2025-12-1-11-16.

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The task of safe traffic light management is to normalize traffic. Secure management involves the implementation of the protection of information involved in the management process. The traffic light management process is a complex dynamic process. The control object is a set of traffic lights. The subject of management is a specific management system, which can be autonomous or part of a top-level management system. The implementation of a traffic light based on a neuromorphic computing base allows you to perform some of the control processes in automatic mode. As part of the control process, you have to deal with different types of data (sensor readings, control signals of different levels, etc.). Big data is processed throughout the entire control process, and one of the main tasks is to reduce the dimensionality of the information being processed. The successful solution of this problem directly depends on the model of organization of a set of traffic lights. The article discusses various traffic lights, each of which is equipped with an intelligent controller. The neuromorphic basis of the intelligent controller allows you to expand the capabilities of the computing base at a low level. Fuzzy graphs are used to represent a set of traffic lights and to connect the traffic lights to the control system. This model makes it possible to combine the information and control components of the process of interaction between the object and the subject of management into one whole. The advantages of this representation are the minimization of information necessary for the successful solution of the problem of safe management, and the expansion of the possibilities of the management process through the use of fuzzy information.

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Qi, Weiwei, Huiying Wen, Chuanyun Fu, and Mo Song. "Game Theory Model of Traffic Participants within Amber Time at Signalized Intersection." Computational Intelligence and Neuroscience 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/756235.

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The traffic light scheme is composed of red, green, and amber lights, and it has been defined clearly for the traffic access of red and green lights; however, the definition of that for the amber light is indistinct, which leads to the appearance of uncertainty factors and serious traffic conflicts during the amber light. At present, the traffic administrations are faced with the decision of whether to forbid passing or not during the amber light in the cities of China. On one hand, it will go against the purpose of setting amber lights if forbidding passing; on the other hand, it may lead to a mess of traffic flow running if not. And meanwhile the drivers are faced with the decision of passing the intersection or stopping during the amber light as well. So the decision-making behavior of traffic administrations and drivers can be converted into a double game model. And through quantification of their earnings in different choice conditions, the optimum decision-making plan under specific conditions could be solved via the Nash equilibrium solution concept. Thus the results will provide a basis for the formulation of the traffic management strategy.

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