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1

Prameela, Mrs N., Ch Srujana Sri, G. Kedarnath, and P. Sairam Venkat. "Smart Traffic Light Control System Using Arduino Mega." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 4382–85. http://dx.doi.org/10.22214/ijraset.2023.60997.

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Abstract: This article presents the "Smart Traffic Light Control System using Arduino Mega" design. These systems manage traffic flow at intersections, aiming for smooth vehicle movement. However, synchronizing multiple traffic lights at adjacent junctions is complex because of a number of variables. Conventional systems struggle with fluctuating traffic flows and lack consideration for emergencies, pedestrian crossings, and accidents. This often leads to congestion and traffic jams. The suggested method resolves these problems by integrating advanced control mechanisms to adjust traffic signa
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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 (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 result
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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 c
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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/isprs-annals-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 c
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Kareem Abdulrazzaq, Ali. "Design an Intelligent Traffic Light Controller." University of Thi-Qar Journal for Engineering Sciences 7, no. 1 (2016): 47–57. http://dx.doi.org/10.31663/utjes.v7i1.45.

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The aim of this research is to design an intelligent traffic light control system using Field Programmable Gate Array (FPGA) technology. And Very High Speed Hardware Description Language(VHDL). A structure of four road intersection (Al-Raiyah intersection) has been selected as reference site,which is located in Al-Nasiriyah city, Iraq. This intersection interconnects Bent-Al-Huda hospital, civil defense directory, the international high-way, the police office directory, and the railway station. In addition to utilizing a regular Traffic Light Controller (TLC), multiple level of functionality s
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Isdore Onyema Akwukwaegbu, Eleazar Benson Mfonobong, Jude-Kennedy Chibuzo Obichere, and Chiedozie Francis Paulinus-Nwammuo. "Smart fuzzy logic-based model of traffic light management." World Journal of Advanced Engineering Technology and Sciences 8, no. 2 (2023): 344–58. http://dx.doi.org/10.30574/wjaets.2023.8.2.0108.

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Traffic congestion difficulties have resulted in low productivity, significant air pollution, and energy losses in Owerri Metropolis, Nigeria. The paper looked at the design of a smart fuzzy logic traffic light management module, the development of a traffic control program using an Arduino microcontroller system, and the validation of the developed program's functionality using a Proteus circuit model to confirm the efficiency of fuzzy signal control. The traffic light environment of a fuzzy logic controller is simulated using Matlab software, and isolated traffic of multiple junctions is sim
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SREEVARDHAN, V., V. SANTOSH, and E. RAHUL. "AUTOMATIC SYNCHRONISED FSM BASED TRAFFIC LIGHT CONTROLLER." International Journal of Computer Science and Mobile Computing 11, no. 1 (2022): 214–20. http://dx.doi.org/10.47760/ijcsmc.2022.v11i01.029.

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Traffic light controller is designed to show the behavior of the traffic lights system and also a kind of good sequential circuit. Xilinx vivado is a tool which is being used to Annalise the heavy traffic by analyzing it through the various tools such as NEXYS-4, ARTIX -7, FPGA Board. The approach can be success by allowing a proper access to the areas shared through the multiple intersections and allocating effective time between various users, on or off the peaking hours. Theoretically the waiting times for drivers during peak hours has been reduced further, therefore this is system is bette
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TEME, Marius, and Catalin Dimon. "DEEP LEARNING - BASED OPTIMIZATION OF SMART TRAFFIC SIGNAL SYSTEMS." Annals of the Academy of Romanian Scientists Series on Science and Technology of Information 18, no. 1 (2025): 5–18. https://doi.org/10.56082/annalsarsciinfo.2025.1.5.

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This paper compares various artificial intelligence techniques applied to intelligent traffic systems for traffic light optimization. The use of Deep Learning algorithms for updating traffic light timings achieves superior results compared to the classical fixed-time approach. The traffic network is conceptualized as a modular component of the urban road infrastructure, facilitating traffic analysis in the context of an integrated management system. A case study analyzes a scenario with multiple connected intersections, with variable input flows estimated based on real data acquired from the B
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Vieira, Manuel Augusto, Manuela Vieira, Gonçalo Galvão, Paula Louro, and Mário Véstias. "Unlocking Traffic Control: Exploring Intersection Dynamics with Visible Light Communication." EPJ Web of Conferences 305 (2024): 00029. http://dx.doi.org/10.1051/epjconf/202430500029.

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This paper introduces the use of Visible Light Communication (VLC) to enhance traffic signal efficiency and vehicle trajectory management at urban intersections. By integrating VLC localization with learning-based traffic signal control, a multi-intersection traffic system is proposed. VLC enables communication between connected vehicles and infrastructure through mobile optical receivers. The primary objectives are to reduce waiting times and improve overall traffic safety by accommodating diverse traffic movements during multiple signal phases. Cooperative mechanisms and queue/response inter
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Shaharuddin, Raihanah Adawiyah, and Md Yushalify Misro. "Controlling Traffic Congestion in Urbanised City: A Framework Using Agent-Based Modelling and Simulation Approach." ISPRS International Journal of Geo-Information 12, no. 6 (2023): 226. http://dx.doi.org/10.3390/ijgi12060226.

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Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road users, particularly in densely populated urban cities. Since road capacity in urban cities changes throughout the day, an optimal traffic light signal duration might be different. Hence, in this paper, the effect of vehicle composition and traffic light phases on traffic flow during peak and off-peak hours in
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Galvão, Gonçalo, Manuel Augusto Vieira, Manuela Vieira, Paula Louro, and Mário Véstias. "Enhancing Urban Traffic Management with Visible Light Communication and Reinforcement Learning." EPJ Web of Conferences 305 (2024): 00030. http://dx.doi.org/10.1051/epjconf/202430500030.

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This paper introduces Visible Light Communication (VLC) to enhance traffic signal efficiency and vehicle trajectory management at urban intersections. A multi-intersection traffic control system is proposed, integrating VLC localization services with learning-based traffic signal control. VLC facilitates communication between connected vehicles and infrastructure using headlights, streetlights, and traffic signals to transmit information. By leveraging vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) interactions, joint transmission and data collection are achieved via mobile optic
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12

Iqbal, Masab, Luis Velasco, Marc Ruiz, et al. "Supporting Heterogenous Traffic on Top of Point-to-Multipoint Light-Trees." Sensors 23, no. 5 (2023): 2500. http://dx.doi.org/10.3390/s23052500.

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New 5 G and beyond services demand innovative solutions in optical transport to increase efficiency and flexibility and reduce capital (CAPEX) and operational (OPEX) expenditures to support heterogeneous and dynamic traffic. In this context, optical point-to-multipoint (P2MP) connectivity is seen as an alternative to provide connectivity to multiple sites from a single source, thus potentially both reducing CAPEX and OPEX. Digital subcarrier multiplexing (DSCM) has been shown as a feasible candidate for optical P2MP in view of its ability to generate multiple subcarriers (SC) in the frequency
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Velasco, Luis. "Supporting Heterogenous Traffic on Top of Point-to-Multipoint Light-Trees." Sensors 23, no. 5 (2024): 1–16. https://doi.org/10.3390/s23052500.

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New 5 G and beyond services demand innovative solutions in optical transport to increase efficiency and flexibility and reduce capital (CAPEX) and operational (OPEX) expenditures to support heterogeneous and dynamic traffic. In this context, optical point-to-multipoint (P2MP) connectivity is seen as an alternative to provide connectivity to multiple sites from a single source, thus potentially both reducing CAPEX and OPEX. Digital subcarrier multiplexing (DSCM) has been shown as a feasible candidate for optical P2MP in view of its ability to generate multiple subcarriers (SC) in the frequency
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14

Lin, Jing, Tingyu Wang, and Wen Lin. "Becoming Healthier without Paying More? Experimental Evidence from the Impact of Multiple Traffic Lights on Chinese College Students." Nutrients 16, no. 13 (2024): 2124. http://dx.doi.org/10.3390/nu16132124.

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The prevalence of overweight and obesity among Chinese residents has become a pressing public health concern. The UK Multiple Traffic Light labeling system, known for its user-friendly design, has demonstrated success in promoting healthier food choices. This paper presents novel findings from a randomized controlled experiment assessing the impact of traffic light labeling on Chinese consumers’ food choices. Results indicate that the label significantly reduces the intake of calories, fat, carbohydrates, and sodium without increasing the economic costs of food choices. This study contributes
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ANUJA, A., DG LOUKYA, RATNAM JUSTIN, and IMMACULATE MARY GERARDINE. "MODELING AND SUPERVISION OF SMART TRAFFIC LIGHT CONTROLLER USING AT89C51 MICROCONTROLLER." Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/ Journal of Tianjin University Science and Technology 56, no. 09 (2023): 215–25. https://doi.org/10.5281/zenodo.8375509.

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<strong>Abstract</strong> Traffic light control systems are widely used to monitor and control the flow of vehicles through the junction of many roads. They aim to realise smooth motion of cars in the transportation routes. However, the synchronisation of multiple traffic light systems at adjacent intersections is a complicated problem given the various parameters involved. Conventional systems do not handle variable flows approaching the junctions. In addition, the mutual interference between adjacent traffic light systems, the disparity of cars flow with time, the accidents, the passage of e
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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 (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 d
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Kamala Aliyeva, Kamala Aliyeva, and Shain Javadov Shain Javadov. "MODELİNG OF TRAFFİC LİGHT CONTROL SYSTEMS." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 28, no. 05 (2023): 119–26. http://dx.doi.org/10.36962/pahtei28052023-119.

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Traffic light control systems are commonly utilized to monitor and manage the flow of autos across multiple road intersections. Since traffic jams are ubiquitous in daily life, A crucial aim is to optimize the functioning of traffic signals for optimal traffic flow. Traffic light control systems aim to make sure automobiles flow smoothly along transit routes. However, considering the numerous parameters involved, synchronizing several traffic signal systems at neighboring junctions is a difficult challenge. Conventional systems are incapable of dealing with varied flows nearing intersections.
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Jafari, Sadiqa, Zeinab Shahbazi, and Yung-Cheol Byun. "Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections." Mathematics 10, no. 16 (2022): 2832. http://dx.doi.org/10.3390/math10162832.

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Traffic congestion is a significant issue in many countries today. The suggested method is a novel control method based on multiple intersections considering the kind of traffic light and the duration of the green phase to determine the optimal balance at intersections by using fuzzy logic control, for which the balance should be adaptable to the unchanging behavior of time. It should reduce traffic volume in transport, average waits for each vehicle, and collisions between cars by controlling this balance in response to the typical behavior of time and randomness in traffic conditions. The pr
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19

Shunu, Daniel. "IMPROVING TRAFFIC FLOW AT INTERSECTION USING INTELLIGENT TRAFFIC MANAGEMENT SYSTEM." Computer Science & IT Research Journal 1, no. 2 (2020): 65–70. http://dx.doi.org/10.51594/csitrj.v1i2.137.

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In this study, a proposed intelligent traffic management system is presented making use of the wireless sensor network for improving traffic flow. By making use of the clustering algorithm, VANET environment is utilized for the proposed system. The components of the proposed system include sensor node hardware, vehicle detection system through magnetometer, and UDP protocol for communication between the nodes. The intersection control agent receives the information about the vehicles and by making use of its algorithm, it dynamically changes the traffic light timings. By making use of the gree
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20

Poythress, Vern. "A simple traffic-light semiotic model for tagmemic theory." Semiotica 2018, no. 225 (2018): 253–67. http://dx.doi.org/10.1515/sem-2017-0025.

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AbstractThe complexity and flexibility of tagmemic theory, as a semiotic theory developed by Kenneth L. Pike, can be better understood by examining how it applies to a simple semiotic system like traffic lights. We can then compare the result with how it functions in analyzing a piece of natural language. Tagmemic theory introduces three observer viewpoints – the particle view, the wave view, and the field view. Each view generates a suite of questions to answer. Any one of the views results in a “complete” description of traffic lights, from which the information about the other views can be
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Buniel, Gideon G., and Carlo P. Tantoy. "SURATSA: Implementation of Surigao Real-Time Adaptive Traffic Signal Algorithm (RATSA) for Traffic Management in Barangay Luna, Surigao City, Philippines." International Journal of Research and Scientific Innovation XI, no. VIII (2024): 342–57. http://dx.doi.org/10.51244/ijrsi.2024.1108029.

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This research presents the implementation and evaluation of an adaptive traffic light system prototype in Barangay Luna, Surigao City, Philippines. The system utilizes Arduino Mega boards and ultrasonic sensors to detect vehicle presence in three lanes, dynamically adjusting traffic light sequences to optimize traffic flow. Data was collected over multiple trials, assessing various scenarios of vehicle detection. The results demonstrated that the adaptive system significantly reduced wait times and improved traffic efficiency compared to conventional fixed-time systems. Key findings highlighte
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Buniel, Gideon G., and Carlo P. Tantoy. "Implementation of Surigao Real-Time Adaptive Traffic Signal Algorithm (RATSA) for Traffic Management in Barangay Luna, Surigao City, Philippines." International Journal of Research and Scientific Innovation IX, no. VIII (2024): 284–300. http://dx.doi.org/10.51244/ijrsi.2024.1108024.

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This research presents the implementation and evaluation of an adaptive traffic light system prototype in Barangay Luna, Surigao City, Philippines. The system utilizes Arduino Mega boards and ultrasonic sensors to detect vehicle presence in three lanes, dynamically adjusting traffic light sequences to optimize traffic flow. Data was collected over multiple trials, assessing various scenarios of vehicle detection. The results demonstrated that the adaptive system significantly reduced wait times and improved traffic efficiency compared to conventional fixed-time systems. Key findings highlighte
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Gaikwad, Mayur M. "Smart Zebra Crossing with Smart Street-Light." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem51088.

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This research presents a prototype of a smart street and zebra crossing system using Arduino, designed to improve road safety and energy efficiency. The system integrates multiple sensors and actuators such as Light Dependent Resistors (LDRs), Infrared (IR) sensors, DC motors, servo motors, seven-segment displays, and LED traffic lights. The LDR sensor automates street lighting based on ambient light levels, conserving energy. The IR sensor detects pedestrians and activates DC motors to deploy sliding zebra crossings and servo motors to operate safety barriers, preventing accidents. A seven-se
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Mulung, Bibi Rawiyah, and Andino Maseleno. "Proposed SMART Traffic Control Signal in Brunei Darussalam." TELKOMNIKA Indonesian Journal of Electrical Engineering 15, no. 2 (2015): 277. http://dx.doi.org/10.11591/tijee.v15i2.1540.

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This paper presents proposed SMART (Systematic Monitoring of Arterial Road Traffic Signals) traffic control signal in Brunei Darussalam. Traffic congestion due to stops and delays at traffic light signals has much been complained about in Brunei Darussalam as well as across the world during the recent years. There are primarily two types of traffic signal controls in Brunei Darussalam. The most common one is the fixed or pre-timed signal operation traffic light and the other one is the actuated signal operation traffic light. Although the actuated signal control is more efficient than the fixe
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Guo, Jian, and István Harmati. "Comparison of Game Theoretical Strategy and Reinforcement Learning in Traffic Light Control." Periodica Polytechnica Transportation Engineering 48, no. 4 (2020): 313–19. http://dx.doi.org/10.3311/pptr.15923.

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Many traffic models and control methods have already been utilized in the public transportation system due to the increasing traffic congestion. Thus, an intelligent traffic model is formalized and presented to control multiple traffic light simultaneously and efficiently according to the distribution of vehicles from each incoming link (i.e. sections) in this paper. Compared with constant strategy, two methods are proposed for traffic light control, i.e., game theoretical strategy and reinforcement learning methods. Game theoretical strategy is generated in a game theoretical framework where
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Nimac, Peter, Andrej Krpič, Boštjan Batagelj, and Andrej Gams. "Pedestrian Traffic Light Control with Crosswalk FMCW Radar and Group Tracking Algorithm." Sensors 22, no. 5 (2022): 1754. http://dx.doi.org/10.3390/s22051754.

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The increased mobility requirements of modern lifestyles put more stress on existing traffic infrastructure, which causes reduced traffic flow, especially in peak traffic hours. This calls for new and advanced solutions in traffic flow regulation and management. One approach towards optimisation is a transition from static to dynamic traffic light intervals, especially in spots where pedestrian crossing cause stops in road traffic flow. In this paper, we propose a smart pedestrian traffic light triggering mechanism that uses a Frequency-modulated continuous-wave (FMCW) radar for pedestrian det
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Sun, D. H., M. Zhang, and T. Chuan. "Multiple optimal current difference effect in the lattice traffic flow model." Modern Physics Letters B 28, no. 11 (2014): 1450091. http://dx.doi.org/10.1142/s0217984914500912.

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Kerner and Konhäuser study moving jam dynamics first discovered in 1993 in Ref. 1. In light of their previous work, a new lattice hydrodynamic model is presented with consideration of the effect of multiple optimal current difference. To investigate the influences of new consideration on traffic jams, the linear stability analysis of the new model is conducted by employing the linear stability theory. Theoretical analysis result shows that the new consideration can stabilize traffic flow. By means of nonlinear analysis method, a modified Korteweg–deVries (mKdV) equation near the critical point
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Trinkaus, John. "An Informal Look at Left-Turning Traffic." Perceptual and Motor Skills 87, no. 2 (1998): 701–2. http://dx.doi.org/10.2466/pms.1998.87.2.701.

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Based on a total of 56 hours of observation of the traffic-light controlled left-turn lanes of a relatively busy road intersection, analysis showed lead vehicles of multiple vehicle queues generally took approximately 0.8 sec. to move out on a green arrow as contrasted with 0.5 sec. when the first vehicle was the only vehicle in the que.
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Rojas-Blanco, Sergio, Alberto Cerezo-Narváez, Manuel Otero-Mateo, and Sol Sáez-Martínez. "Adjacency List Algorithm for Traffic Light Control Systems in Urban Networks." Systems 12, no. 12 (2024): 539. https://doi.org/10.3390/systems12120539.

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The increasing complexity of urban road networks has driven the development of Intelligent Transportation Systems (ITS) to optimize vehicle flow. To address this challenge, this paper presents an algorithm and MATLAB function that generates an adjacency list of traffic signals to provide detailed information about the relationships between all signals within a network. This list is based on stable structural road and traffic lights data and offers a crucial global perspective for signal coordination, especially in managing multiple intersections. An adjacency list is more efficient than matric
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Setyowati, Rustiana, and Siti Maria Ulfa. "Hubungan Beban Kerja Dan Lingkungan Kerja Terhadap Stres Kerja Pada Polisi Satlantas Polres Bantul." Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo 6, no. 2 (2020): 169. http://dx.doi.org/10.29241/jmk.v6i2.338.

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In Indonesia cases of stress due to workload in the work environment of the police have occurred in several areas and have had quite serious impacts. The Research was conducted at the traffic police Special Region of Yogyakarta in 2019. This Research is a quantitative non experimental research with correlational descriptive. Data analysis techniques using multiple linier regression analysis. Respondents as many as 50 police Bantul Police Traffic Unit, the sample uses a saturated sample.The Study aims to determine the relationship of workload and work environment to work stress of Bantul Police
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Maczyński, Andrzej, Krzysztof Brzozowski, and Artur Ryguła. "Analysis and Prediction of Vehicles Speed in Free-Flow Traffic." Transport and Telecommunication Journal 22, no. 3 (2021): 266–77. http://dx.doi.org/10.2478/ttj-2021-0020.

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Abstract Speed is a crucial factor in the frequency and severity of road accidents. Light and heavy vehicles speed in free-flow traffic at six locations on Poland’s national road network was analyzed. The results were used to formulate two models predicting the mean speed in free-flow traffic for both light and heavy vehicles. The first one is a multiple linear regression model, the second is based on an artificial neural network with a radial type of neuron function. A set of the following input parameters is used: average hourly traffic, the percentage of vehicles in free-flow traffic, geome
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Wu, Qiang, Jianqing Wu, Jun Shen, Binbin Yong, and Qingguo Zhou. "An Edge Based Multi-Agent Auto Communication Method for Traffic Light Control." Sensors 20, no. 15 (2020): 4291. http://dx.doi.org/10.3390/s20154291.

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With smart city infrastructures growing, the Internet of Things (IoT) has been widely used in the intelligent transportation systems (ITS). The traditional adaptive traffic signal control method based on reinforcement learning (RL) has expanded from one intersection to multiple intersections. In this paper, we propose a multi-agent auto communication (MAAC) algorithm, which is an innovative adaptive global traffic light control method based on multi-agent reinforcement learning (MARL) and an auto communication protocol in edge computing architecture. The MAAC algorithm combines multi-agent aut
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Andronov, R. V., E. Eh Leverents, D. A. Genze, and E. N. Legostaeva. "The influence of traffic management at a regulated intersection on the uniformity of traffic capacity." Вестник гражданских инженеров 17, no. 6 (2020): 179–85. http://dx.doi.org/10.23968/1999-5571-2020-17-6-179-185.

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The paper deals with the issue of uniformity indicator of the traffic capacity at the regulated intersections from the standpoint of the traffic management, emphasizing the importance of accounting the value of uniformity, in addition to the value on the traffic performance. The schemes of traffic management are provided, where the interferences, due to turning vehicles and the movement of pedestrians in one phase, reduce the uniformity of the traffic capacity. This reduces the efficiency of traffic light regulation and increases the queue length and overall vehicle delays. The conclusions of
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Begum, Shaeista, and Dr Nagaraj B. Patil. "Optimal Intelligent Vehicle Control System for Emergency Vehicle Using Visible Light Communication VANET." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 6561–77. http://dx.doi.org/10.22214/ijraset.2023.53130.

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Abstract: Traffic congestion is one of the significant problems in every metropolitan city. Traffic congestion occurs, when large numbers of vehicles are all together and are not able to move or move slowly, it is also known as a traffic jam. The main aim of the proposed OIVC-VLC VANET system is to improve the data transmission rate to control traffic in high density loads for emergency vehicles. Traffic congestion leads to wasting of time, road accidents, delays of trips, and reduces regional economic health and fuel consumption. Moreover, the most critical concern of traffic congestion is a
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Vieira, Manuela, Manuel Augusto Vieira, Gonçalo Galvão, Paula Louro, Mário Véstias, and Pedro Vieira. "Enhancing Urban Intersection Efficiency: Utilizing Visible Light Communication and Learning-Driven Control for Improved Traffic Signal Performance." Vehicles 6, no. 2 (2024): 666–92. http://dx.doi.org/10.3390/vehicles6020031.

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This paper introduces an approach to enhance the efficiency of urban intersections by integrating Visible Light Communication (VLC) into a multi-intersection traffic control system. The main objectives include the reduction in waiting times for vehicles and pedestrians, the improvement of overall traffic safety, and the accommodation of diverse traffic movements during multiple signal phases. The proposed system utilizes VLC to facilitate communication among interconnected vehicles and infrastructure. This is achieved by utilizing streetlights, headlamps, and traffic signals for transmitting i
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Yan, Xuedong, Essam Radwan, and Elizabeth Birriel. "Analysis of Red Light Running Crashes Based on Quasi-Induced Exposure and Multiple Logistic Regression Method." Transportation Research Record: Journal of the Transportation Research Board 1908, no. 1 (2005): 70–79. http://dx.doi.org/10.1177/0361198105190800109.

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According to recent national statistics, red light running crashes represent a significant safety problem at signalized intersections. To examine the overall characteristics of red light running crashes, this study used the 1999 to 2001 Florida crash database to investigate the crash propensity related to traffic environments, driver characteristics, and vehicle types. The quasi-induced exposure concept and multiple logistic regression technique were used to perform this analysis. The results showed that traffic factors including number of lanes, crash time, weather, highway character, day of
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Wang, Yanhong. "A unified model for two-lane lattice traffic flow." International Journal of Modern Physics B 30, no. 31 (2016): 1650227. http://dx.doi.org/10.1142/s0217979216502271.

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In this paper, a unified model is presented for two-lane lattice traffic flow, with comparing different effects in the various lattice hydrodynamic models. Results of linear and nonlinear analysis show that multiple density difference effect (MDDE) is the strongest to enlarge the stable region in two-lane systems. Followed by density difference effect (DDE), multiple flux difference effect (MFDE), and finally flux difference effect (FDE). But when density is around 0.25, MFDE is better to enlarge the stable region than DDE. The reason is that a small flow-rate value might correspond to either
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Zhou, Xingyu, Ness Shroff, and Adam Wierman. "Asymptotically Optimal Load Balancing in Large-scale Heterogeneous Systems with Multiple Dispatchers." ACM SIGMETRICS Performance Evaluation Review 48, no. 3 (2021): 57–58. http://dx.doi.org/10.1145/3453953.3453965.

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We consider the load balancing problem in large-scale heterogeneous systems with multiple dispatchers. We introduce a general framework called Local-Estimation-Driven (LED). Under this framework, each dispatcher keeps local (possibly outdated) estimates of the queue lengths for all the servers, and the dispatching decision is made purely based on these local estimates. The local estimates are updated via infrequent communications between dispatchers and servers. We derive sufficient conditions for LED policies to achieve throughput optimality and delay optimality in heavy-traffic, respectively
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RATNA KUMARI, Mrs J., NADENDLA BHAVANI, SHAIK THALIB, VATLURU CHARAN NAGA SAI SURYA, and BATHULA Srikanth. "AN EFFCIENT SYSTEM FOR DETECTING TRAFFIC VIOLATIONS SUCH AS OVER SPEED, DISREGARDING SIGNALS, AND INSTANCES OF TRIPLE RIDING." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 15, no. 1 (2024): 104–8. http://dx.doi.org/10.61841/turcomat.v15i1.14548.

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In recent time surveys, the deaths and injuries due to traffic violations have increased chiefly in Indian roads. So, this needed the assistance of an automated computer vision-based object detection model, as manually identifying the vehicles violating traffic is hectic. The principle of this paper is to detect multiple violations using single video frames. The input video stream obtained from the surveillance camera is processed and annotated to carry out multiple processes. The dataset used for red-light jumping is COCO and the dataset for over boarding is created by annotating the images o
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Jiang, Ze-Hao, Xiao-Guang Yang, Tuo Sun, Tao Wang, and Zheng Yang. "Investigating the Relationship between Traffic Violations and Crashes at Signalized Intersections: An Empirical Study in China." Journal of Advanced Transportation 2021 (April 16, 2021): 1–8. http://dx.doi.org/10.1155/2021/4317214.

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About 90% of traffic crashes are caused by human factors, within which traffic violations are one of the most typical and common causes. In order to investigate the relationship between traffic violations and traffic crashes, this research targets signalized intersections in two Chinese cities: Yinchuan and Suqian. Thirty-one intersections are selected as the research sites, and additionally, the traffic volume, traffic violation, and traffic crash data of each intersection are collected for one year. A White’s test is conducted to test the homoscedasticity of the data and a multiple linear re
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Li, Zhe, Xiaolei Ji, Shuai Yuan, Zengli Fang, Zhennan Liu, and Jianping Gao. "A Green Wave Ecological Global Speed Planning under the Framework of Vehicle–Road–Cloud Integration." Electronics 13, no. 17 (2024): 3516. http://dx.doi.org/10.3390/electronics13173516.

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In response to energy consumption and traffic efficiency reduction caused by intersection congestion, a global speed planning that considered both ecological speed and green wave speed was conducted under the vehicle–road–cloud integration framework. After establishing an instantaneous energy consumption model for pure electric vehicles, a radial basis neural network model was used to estimate the queue length of traffic flow, and an isolated-intersection-based eco-approach and departure (I-EAD) plan was proposed based on a valid traffic signal light model. A two-stage optimization multi-inter
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Burdzik, Rafał, Ireneusz Celiński, Minvydas Ragulskis, Vinayak Ranjan, and Jonas Matijošius. "Estimation of Vehicle Traffic Parameters Using an Optical Distance Sensor for Use in Smart City Road Infrastructure." Journal of Sensor and Actuator Networks 13, no. 4 (2024): 35. http://dx.doi.org/10.3390/jsan13040035.

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In recent decades, the dynamics of road vehicle traffic have significantly evolved, compelling traffic engineers to develop innovative traffic monitoring solutions, especially for dense road networks. Traditional methods for measuring traffic volume along road sections may no longer suffice for modern traffic control systems. This is particularly true for induction loops, a widely used method since the last century. In contrast, measuring techniques using microwaves or visible light offer better accuracy but are often hindered by the high cost of sensors. This paper presents new techniques for
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Su, Baofeng, Jiangbi Hu, Juncheng Zeng, and Ronghua Wang. "Traffic Safety Improvement via Optimizing Light Environment in Highway Tunnels." International Journal of Environmental Research and Public Health 19, no. 14 (2022): 8517. http://dx.doi.org/10.3390/ijerph19148517.

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Driving in tunnel areas depends more heavily on light conditions than that on open roadways. Traditional lighting systems in highway tunnels adjust lighting parameters only caring about outside light luminance, and focus is usually on energy conservation; however, little concern is about drivers’ actual physical and psychological needs. How to leverage the enormous research progress of traffic safety, light environment, human factors engineering, and modern lighting sources to create an ideal tunnel light environment that aids with ensuring driving safety and lower interference effects caused
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Qu, Dayi, Kun Chen, Shaojie Wang, and Qikun Wang. "A Two-Stage Decomposition-Reinforcement Learning Optimal Combined Short-Time Traffic Flow Prediction Model Considering Multiple Factors." Applied Sciences 12, no. 16 (2022): 7978. http://dx.doi.org/10.3390/app12167978.

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Accurate short-term traffic flow prediction is a prerequisite for achieving an intelligent transportation system to proactively alleviate traffic congestion. Considering the complex and variable traffic environment, so that the traffic flow contains a large number of non-linear characteristics, which makes it difficult to improve the prediction accuracy, a combined prediction model that reduces the unsteadiness of traffic flow and fully extracts the traffic flow features is proposed. Firstly, decompose the traffic flow data into multiple components by the seasonal and trend decomposition using
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Kong, Yan, Ying Li, and Chih-Hsien Hsia. "MALight: A Deep Reinforcement Learning Traffic Light Control Algorithm with Pressure and Attentive Experience Replay." Journal of Internet Technology 25, no. 7 (2024): 955–62. https://doi.org/10.70003/160792642024122507001.

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This study proposes a new algorithm MALight based on multi-step deep Q network (DQN) and attentive experience replay (AER). Multi-step DQN samples multiple consecutive experiences within a time step, combines them into a long-term sample, and uses them to update the Q network to reduce the bias caused by inaccurate Q value estimation, which could accelerate the convergence of Q network. During training, we adopted the concept of AER to prioritize learning experiences close to the current state to enable the agent to learn better strategies. Finally, we conducted simulation experiments in the c
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Mu, Ching-Yun, and Pin Kung. "Enhancing the Image Pre-Processing for Large Fleets Based on a Fuzzy Approach to Handle Multiple Resolutions." Applied Sciences 14, no. 18 (2024): 8254. http://dx.doi.org/10.3390/app14188254.

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Image pre-processing is crucial for large fleet management. Many traffic videos are collected by closed-circuit television (CCTV), which has a fixed area monitoring for image analysis. This paper adopts the front camera installed in large vehicles to obtain moving traffic images, whereas CCTV is more limited. In practice, fleets often install cameras with different resolutions due to cost considerations. The cameras evaluate the front images with traffic lights. This paper proposes fuzzy enhancement with RGB and CIELAB conversions to handle multiple resolutions. This study provided image pre-p
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Maji, Akash, and Pragati Mahale. "An Exploring IOT Solution for Enhanced Smart Traffic Management System." An Exploring IOT Solution for Enhanced Smart Traffic Management System 1, Vol. 1 No. 2 (2023): October 2023 (2024): 14. https://doi.org/10.59890/ijaamr.v1i2.481.

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This paper delves into the use of the Internet of Things (IoT) to enhance smart traffic management systems. It acts as a middle layer built upon IoT technology, expanding the concept of a smart city by improving traffic light control, parking management, emergency assistance, anti-theft security, and more. IoT facilitates seamless communication between web-connected devices and various components like traffic sensors, services, and actuators, creating a robust network. Consequently, IoT's application in smart traffic management extends beyond just reducing traffic congestion and optimizing tra
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Hitesh Gehani. "Traffic Signal Violation Detection System Using Computer Vision." Journal of Electrical Systems 20, no. 2 (2024): 2661–70. http://dx.doi.org/10.52783/jes.2037.

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The Traffic Signal Violation Detection System is an innovative solution leveraging computer vision techniques to enhance traffic management and improve road safety. This project aims to develop an intelligent system capable of automatically detecting and monitoring traffic signal violations at intersections. Using computer vision algorithms, the system processes video feeds from surveillance cameras installed at traffic signals. The proposed approach involves multiple steps, including video preprocessing, object detection, and violation classification. In the preprocessing phase, the video fra
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Parinith, R. Iyer, Raman Iyer Shrutheesh, Ramesh Raghavendran, MR Anala, and N. Subramanya K. "Adaptive real time traffic prediction using deep neural networks." International Journal of Artificial Intelligence (IJ-AI) 8, no. 2 (2019): 107–19. https://doi.org/10.11591/ijai.v8.i2.pp107-119.

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The ever-increasing sale of vehicles and the steady increase in population density in metropolitan cities have raised many growing concerns, most importantly commute time, air and noise pollution levels. Traffic congestion can be alleviated by opting adaptive traffic light systems, instead of fixedtime traffic signals. In this paper, a system is proposed which can detect, classify and count vehicles passing through any traffic junction using a single camera (as opposed to multi-sensor approaches). The detection and classification are done using SSD Neural Network object detection algorithm. Th
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Rajeswaran, Sivanesan. "Acceptance of Multiple Traffic Light Food Label among Students: A Review of the Literature." International Journal of Science and Research (IJSR) 13, no. 12 (2024): 984–93. https://doi.org/10.21275/sr241209135422.

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