Journal articles: 'Traffic signal'

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Woscholski, Rüdiger, and Peter J. Parker. "Inositol lipid 5-phosphatases-traffic signals and signal traffic." Trends in Biochemical Sciences 22, no. 11 (1997): 427–31. http://dx.doi.org/10.1016/s0968-0004(97)01120-1.

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Patil, Vrushal. "Traffic Signal Pattern Algorithm." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 126–28. http://dx.doi.org/10.22214/ijraset.2023.57249.

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Abstract: Every day we are witnessing a rapid increase in traffic volume on roads. Traffic signals are made to manage the traffic to get less disturbance during the journey and to avoid collisions. Sometimes these traffic signals might become a reason for a delay due to poor time management at signal timings. The old traffic signal patterns are the main cause of this issue and hence this project of new signalling patterns will help in using traffic signals more efficiently. In the traditional pattern at a crossover only one signal can be opened but using our pattern algorithm more than one signal can be opened and traffic could clear more easily. Even concepts of image processing are used to make the system more automated and intelligent.

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Goyal, Omesh, and Chamkour Singh. "A Review on Traffic Signal Identification." International Journal of Trend in Scientific Research and Development Volume-3, Issue-4 (2019): 894–97. http://dx.doi.org/10.31142/ijtsrd23557.

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Royko, Yuriy, Yurii Yevchuk, and Romana Bura. "Minimization of traffic delay in traffic flows with coordinated control." Transport technologies 2021, no. 2 (2021): 30–41. http://dx.doi.org/10.23939/tt2021.02.030.

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The method and results of transport research, carried out by field research method, on the determination of the main indicators of traffic flows with significant unevenness of the movement on the arterial street in conditions of coordinated control is reviewed in the paper. Time parameters of traffic light control for which a reduction in traffic delay is achieved in direct and opposite traffic flow by the change of permissive signal depending on traffic intensity are determined using the simulation method. Change (increase) of the duration of the permissive signal provides uninterrupted movement of vehicles` group during their passage of stop-line at traffic light objects. The proposed method can be used on sections of transport networks with coordinated control, where there is significant heterogeneity of traffic flow, and it prevents the dissipation of groups that consist of vehicles with different dynamic characteristics. Such a result is being performed in the case when in the system of automated control, which combines adjacent intersections on an arterial street, fixed-time program control of traffic light signalization is operating. In this condition, there is a possibility to adjust the duration of signals of traffic light groups by correcting the width (permissive signal duration) and angle of inclination (speed of movement) of the timeline in coordination graphs. The scientific novelty of this research is that the method of traffic delay minimization in conditions of coordinated control acquired further development. The essence of the method is in the controlled change of the range of permissive signal duration in conditions of simultaneous control of the speed of movement between adjacent intersections. Practical value is the application of different programs of traffic light control on sections of arterial streets in transport districts where a significant difference of values of traffic intensity by directions is in morning and evening peak periods.

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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 fixed or pre-fixed signal control in the sense that it provides fewer stops and delays to traffic on the major arteries, the best option for Brunei Darussalam would be to introduce smart traffic control signal. This type of traffic signal uses artificial intelligence to take the appropriate action by adjusting the times in real time to minimise the delay in the intersection while also coordinating with intersections in the neighbourhood. SMART Signal simultaneously collects event-based high-resolution traffic data from multiple intersections and generates real-time signal performance measures, including arterial travel time, number of stops, queue length, intersection delay, and level of service. In Brunei Darussalam, where we have numerous intersections where several arterial roads are linked to one another, The SMART signal traffic control method should be implemented.

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Meghani, Jayesh, Gaurav Gumbade, and Komal A. Chaudhari. "Intelligent RF-ID based Traffic Signal Control." International Journal of Science and Research (IJSR) 12, no. 11 (2023): 1858–61. http://dx.doi.org/10.21275/mr231125163753.

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Prof. C.Y. Patil, Pallavi Mandhare, Dr Jyoti Yadav, Prof Vilas Kharat,. "Control and Coordination of Self-Adaptive Traffic Signal Using Deep Reinforcement Learning." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 373–79. http://dx.doi.org/10.17762/itii.v9i1.141.

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The most observable obstacle to sustainable mobility is traffic congestions. These congestions cannot effectively be fixed by traditional control of traffic signals. Safe and smooth movement of traffic is ensured by a self-controlled traffic signal. As such, to coordinate the traffic flow it is necessary to implement dynamic traffic signal subsequences. Primarily, Traffic Signal Controllers (TSC) provides sophisticated control and coordination of vehicles. The control and coordination of traffic signal control systems can be effectively achieved by implementing the Deep Reinforcement Learning (DRL) approaches. The decision-making capabilities at intersections are improved by having variations of traffic signal timing using an adaptive TSC. Alternatively, the actual traffic demand is nothing but managing the traffic systems. It analyses the incoming number and type of vehicles and gives a real-time response at intersection geometrics and controls the traffic signals accordingly. The proposed DRL algorithm observes traffic data and operates optimum management plans for the regulation of the traffic flow. Furthermore, an existing traffic simulator is used to help provide a realistic environment to support the proposed algorithm.

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Behzadi, Saeed. "AN INTELLIGENT LOCATION AND STATE REORGANIZATION OF TRAFFIC SIGNAL." Geodesy and cartography 46, no. 3 (2020): 145–50. http://dx.doi.org/10.3846/gac.2020.10806.

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In all geo-database related to traffic, beside storing roads data, the information associated to traffic signals such as location, types of traffic signals, side street name, and so on are also stored in that database. In reality, the reason of defining traffic signals for road is the situations and conditions which the roads have. So the existence of traffic signals in the network is related to the parameters of the road. In this paper, instead of storing traffic signal data in the database, a novel method is introduced which implemented on the road network. As a result, the spatial and non-spatial information of traffic signals in the network are extracted based on the location and attribute of the road network. The proposed method is implemented on the network; the result of the intelligent method is compared with the traffic signals information which stored in the database. By comparing the locations and states of proposed traffic signals and the real ones, the overall accuracy for recognizing locations of traffic signal is obtained 94% and the overall accuracy for recognizing states of traffic signal is obtained 89%.

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Nichat, Mr Onkar, Mr Suraj Kulkarni, Mr Aditya Shripad Mane, Mr Siddhesh Naik, and Mr Shubham Bhandari. "Traffic Signal Scheduling using Machine Learning." International Journal of Recent Technology and Engineering (IJRTE) 11, no. 6 (2023): 112–17. http://dx.doi.org/10.35940/ijrte.f7489.0311623.

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Within the past few years the number of vehicles increased drastically and therefore the traffic of vehicles became a major issue in urban as well as in rural areas. Major traffic is happening in the area where many roads do intersect with each other. Our existing traffic signal is not real-time and it is run according to how it is programmed earlier irrespective of traffic. To avoid traffic, traffic signals should give the priority to the road that has the maximum density of vehicles. By doing this we can pass the maximum number of vehicles in a certain period of time. This type of signal acts according to the real-time situation, and take a decision smartly. Hence this system is also called a smart traffic light system. The purpose of this study is to get the traffic situation on the roads in real-time and acts accordingly. Using a web camera that should be mounted on the signals, we can get real-time footage of the roads and by using image processing methods, we can determine the densities of vehicles on each road. Signals which are programmed priorly or wrong signal scheduling was found to play the greatest role in causing vehicle traffic. This smart traffic signal scheduling system is definitely a better option in comparison with existing traffic signal scheduling as it is taking the decision according to the traffic situations.

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Nuri, Sura, Sara M. Mahmood, Omar A. Abdulrazzaq, and Ahmed A. Abdullah. "Design and Fabrication of Smart Traffic Signal Using Arduino Card." Iraqi Journal of Industrial Research 9, no. 3 (2022): 23–32. http://dx.doi.org/10.53523/ijoirvol9i3id251.

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Traffic jam is becoming a headache in the big cities all over the world, which causes a significant delay for drivers and passengers. A smart on/off traffic signal optimization based on a motion IR Sensor (Infrared) is now a necessity to overcome this problem. This work is a design and implementation of a smart traffic signal (STS) that controls the time of the traffic signals (Red–Yellow–Green) according to the traffic congestion on the road. The STS is designed to imitate a side road (with a low traffic move) with a highway road (with a high traffic move). A motion IR sensor along with an Arduino PIC were installed to automatically control the traffic signals on/off delay times based on the existence of the vehicles on the side road. When the side road is empty, the highway traffic signal is always green (highway–always–on mode). However, when a vehicle reaches the traffic signal in the side road, the motion IR sensor sends a signal to the Arduino card, so that the highway traffic signal turns red, while the side road traffic signal turns green letting the vehicle to pass the intersection. The system will then automatically set back to the highway–always–on mode. The entire system is designed and simulated using Proteus workbench.

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Zhao, Ling, Juan Cao, and Bo Mi. "Fractal Characteristics of Mountain Cities' Traffic Flow Based on EMD and Multifractal." Advanced Materials Research 831 (December 2013): 430–34. http://dx.doi.org/10.4028/www.scientific.net/amr.831.430.

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Aim at the characteristics of the mountain cities road traffic network, the short-time data signals in the congestion state of the road network traffic is analyzed. Fractal characteristics of traffic data signal is in research based on the self-similarity of the traffic data signals. The non-stationary property of the traffic flow signal in the congestion state is known through the calculation of the multifractal spectrum of the traffic flow signal based on EMD. The experimental results show the feasibility of the method, which also can provide theoretical support for the traffic flow control of the mountain city road network in the sub-health state.

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Yang, Dongxia. "Traffic Signal Optimization under Uncertain Traffic Demands." Journal of Information and Computational Science 11, no. 13 (2014): 4737–45. http://dx.doi.org/10.12733/jics20104985.

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Yulianto, Budi. "Traffic Signal Controller for Mixed Traffic Conditions." IOSR Journal of Mechanical and Civil Engineering 4, no. 1 (2012): 18–26. http://dx.doi.org/10.9790/1684-0411826.

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Niittymäki, Jarkko, and Matti Pursula. "Saturation Flows at Signal-Group-Controlled Traffic Signals." Transportation Research Record: Journal of the Transportation Research Board 1572, no. 1 (1997): 24–32. http://dx.doi.org/10.3141/1572-04.

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The main goal of this research was to update the basic saturation flow values of signalized intersections. The secondary goal was to analyze the effects of certain external factors (such as weather, road, and traffic conditions) on saturation flow. The updating is based on extensive field measurements and simulations. Altogether, about 39,000 queues were observed in this study. Field measurements at 30 locations were made according to the method described in the Highway Capacity Manual and simulations were done with the Helsinki University of Technology HUT-SIM simulator, which was calibrated and carefully validated for Finnish road conditions. A summary of calibration parameters is also presented. The new base value for straight-through lanes is 1, 940 vehicles per hour; the previous value was 1, 700 vehicles per hour. In general, the updated saturation flow values of different lane types are 5 to 20 percent larger than the previous base values. The saturation flow models of different lane types are described. The effects of geometric and traffic composition factors, such as percentage of turning vehicles, traffic composition, lane width, and approach grade, were examined and modeled. Effects of weather, road surface, light conditions, and speed level were also analyzed. The drop in saturation flow was about 20 to 30 percent under slippery road and snowy conditions. In rainy conditions, the drop was smaller, about 10 percent. The effect of speed on saturation flow is also described. The most important results of this 2-year project are the saturation flow values for different lane types, knowledge of the effect of external factors (especially during winter), and the large database, which can be used for other purposes. The possibility of using special signal control programs under bad road conditions is discussed. With these kinds of programs, better safety and higher capacity can be achieved.

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Kumar, T. Anil. "IoT Based Signal Violated Vehicle Detector." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (2022): 187–97. http://dx.doi.org/10.22214/ijraset.2022.40221.

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Abstract: The number of new vehicles on the road is increasing rapidly, which in turn causes highly congested roads and due to the long awaiting red signals, few vehicle drivers ignore traffic rules by violating traffic signals. This leads to a high number of road accidents and hence it is essential to detect the signal violated vehicles automatically. Traffic violation detection systems using IOT technology can able to send violated vehicle information to the concern traffic police station automatically by which the vehicle can be penalized immediately. The proposed system can be implemented using vehicle ID card installed in the vehicle itself such that if the vehicle moves further during presence of red signal, automatically, vehicle information in the form of vehicle registration number, type of vehicle (weather it is two-wheeler, car, truck, auto, etc.), owner name, vehicle colour, etc, can be forwarded to the concern authorities through concern mobile phones. To prove the concept practically, all vehicles must be equipped with these low-cost wireless ID cards such that the vehicle data can be transmitted continuously. The demo module contains a mini automatic traffic signal post along with simulated road. The system is designed such that when red signal is energized and during this period, if any vehicle crosses the zebra lines, the system receives the vehicle data and transmits the same through Wi-Fi module. If anybody violates the traffic signal, immediately alarm will be energized to alert the nearest traffic police. The main processor must be installed near the traffic signals, which regrets to acquire vehicle information during the presence of yellow and green signals. The demo module contains one toy car which will be equipped with its wireless ID card. Major building blocks: Simulation of single lane road constructed with traffic signal post & zebra crossing, main processor designed with Arduino MCU, wireless ID card designed with 89C2051 controller chip, IR signal decoder (TSOP1738), Wi – Fi module, Alarm, IR LED, 5v Power supply unit, Toy car, etc.

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Gartner, Nathan H., and Mohammed Al-Malik. "Combined Model for Signal Control and Route Choice in Urban Traffic Networks." Transportation Research Record: Journal of the Transportation Research Board 1554, no. 1 (1996): 27–35. http://dx.doi.org/10.1177/0361198196155400104.

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Traffic signals have a significant effect on the choice of routes by motorists in urban areas. They are of primary importance in the development of advanced traffic management strategies that involve dynamic rerouting of traffic flows through signal-controlled street networks. A combined network model that simultaneously accounts for both the route choices made by motorists and the desired signal controls to match these choices is presented. Given origin-destination travel demand information, the model generates signal controls to optimize network performance and calculates the resulting traffic volumes in the network. This optimization model inherently reflects the mutual consistency between traffic flows and signal controls. The model is applicable to both fixed-time and demand-responsive signals. Computational procedures and sample network solutions are presented.

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Hajbabaie, Ali, and Rahim F. (Ray) Benekohal. "Traffic Signal Timing Optimization." Transportation Research Record: Journal of the Transportation Research Board 2355, no. 1 (2013): 10–19. http://dx.doi.org/10.3141/2355-02.

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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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Snehal Chaudhary, Et al. "Use of Convolutional Neural Network and SVM Classifiers for Traffic Signals Detection." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 490–93. http://dx.doi.org/10.17762/ijritcc.v11i9.8834.

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Road signals are crucial for preserving a safe and effective flow of traffic. They give directions to cars, warn them of potential dangers, and notify them of the conditions of the road ahead. Road signs make roadways safer for both vehicles and pedestrians by regulating traffic and reducing accidents. Failure to obey traffic signals can be harmful and result in collisions. Drivers must always be conscious of their surroundings and pay attention to traffic signs. If a driver misses a signal, they should proceed with caution and safety to prevent injuring themselves or others, and they should seek assistance to reroute themselves. Through the use of machine learning techniques, this project will create a traffic signal recognition system that will identify the traffic signals that are present on the road and inform the driver if the system determines that the motorist has missed a traffic signal or is thus violating traffic laws.

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Kamal, Md Abdus Samad, Jun-ichi Imura, Tomohisa Hayakawa, Akira Ohata, and Kazuyuki Aihara. "Network-Wide Optimization of Traffic Signals Using Mixed Integer Programming." Journal of Robotics and Mechatronics 26, no. 5 (2014): 607–15. http://dx.doi.org/10.20965/jrm.2014.p0607.

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<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00260005/09.jpg"" width=""300"" />Network with four intersections</div> In this paper a network-wide traffic signal control scheme in a model predictive control framework using mixed integer programming is presented. A concise model of traffic is proposed to describe a signalized road network considering conservation of traffic. In the model, the traffic of two sections that belong to a traffic signal group of a junction are represented by a single continuous variable. Therefore, the number of variables required to describe traffic in the network becomes half compared with the models that describe section wise traffic flows. The traffic signal at the junction is represented by a binary variable to express a signal state either green or red. The proposed model is transformed into a mixed logical dynamical system to describe the traffic flows in a finite horizon, and traffic signals are optimized using mixed integer linear programming (MILP) for a given performance index. The scheme simultaneously optimizes all traffic signals in a network in the context of model predictive control by successively extending or terminating a green or red signal of each junction. Consequently, traffic signal patterns with the optimal free parameters, i.e., the cycle times, the split times and the offsets, are realized. Use of the proposed concise traffic model significantly reduces the computation time of the scheme without compromising the performance as it is evaluated on a small road network and compared with a previously proposed scheme. </span>

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Movius, SJ, and JH Van Vuuren. "Self-organisation in traffic signal control algorithms under light traffic conditions." ORiON 35, no. 1 (2019): 57–87. http://dx.doi.org/10.5784/35-1-605.

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Fixed-time control and vehicle-actuated control are two distinct types of traffic signal control. The latter control method involves switching traffic signals based on detected traffic flows and thus offers more flexibility (appropriate for lighter traffic conditions) than the former, which relies solely on cyclic, predetermined signal phases that are better suited for heavier traffic conditions. The notion of self-organisation has relatively recently been proposed as an alternative approach towards improving traffic signal control, particularly under light traffic conditions, due to its flexible nature and its potential to result in emergent behaviour. The effectiveness of five existing self-organising traffic signal control strategies from the literature and a fixed-control strategy are compared in this paper within a newly designed agent-based, microscopic traffic simulation model. Various shortcomings of three of these algorithms are identified and algorithmic improvements are suggested to remedy these deficiencies. The relative performance improvements resulting from these algorithmic modifications are then quantified by their implementation in the aforementioned traffic simulation model. Finally, a new self-organising algorithm is proposed that is particularly effective under lighter traffic conditions.

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Gourav, Desh. "Smart Traffic System." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 2638–42. http://dx.doi.org/10.22214/ijraset.2021.37038.

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The objective of this project is to control the traffic signal with help of solar energy. This project has been developed as a model of Traffic light controller. The signals can be controlled through software programs and can be varied depending upon the location. For example some places needs green signal to glow for long time. And some directions need red signals to glow for long time. This can be achieved simply by varying the delay in the software. Solar power is used to provide the power to the solar lights. So this project is very useful to the government to save the power.The solar panel is solar photovoltaic modules use solar cells to convert light from the sun into electricity. Now-a-days, instead of using the power from the supply line for various operations, most of them are going for solar energy source, as it is cheapest.

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Sekiyama, Kosuke, and Yasuhiro Ohashi. "Distributed Route Guidance Systems with Self-Organized Multi-Layered Vector Fields." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 2 (2005): 106–13. http://dx.doi.org/10.20965/jaciii.2005.p0106.

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This paper deals with novel distributed route guidance that cooperates with self-organizing control of traffic signal networks. Self-organizing control of traffic signals provides a fully distributed approach to coordinate a number of signals distributed in a wide area based on local information of traffic flows so that split and offset control parameters between traffic signals are adjusted for efficient traffic flow. The self-organizing route guidance systems (SRGS) concept is introduced for efficient route guidance to facilitate offset adjustment of the self-organizing control of signal networks by self-organizing multilayered vector fields. Simulation demonstrates the effectiveness of the proposal under nonstationary traffic conditions.

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Maheshwari, Rashi. "Smart Traffic Light System." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (2021): 679–86. http://dx.doi.org/10.22214/ijraset.2021.38053.

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Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

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Turner, Glenn, Guoning Chen, and Yunpeng Zhang. "A Visual Analytics Approach for Anomaly Detection from a Novel Traffic Light Data." Electronic Imaging 2021, no. 1 (2021): 330–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.1.vda-330.

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Traffic signals are part of our critical infrastructure and protecting their integrity is a serious concern. Security flaws in traffic signal systems have been documented and effective detection of exploitation of these flaws remains a challenge. In this paper we present a visual analytics approach to look for anomalies in traffic signal data (i.e., abnormal traffic light patterns) that may indicate a compromise of the system. To our knowledge it is a first time a visual analytics approach is applied for the processing and exploration of traffic signal data. This system supports level-of-detail exploration with various visualization techniques. Data cleaning and a number of preprocessing techniques for the extraction of summary information (e.g., traffic signal cycles) of the data are also performed before the visualization and data exploration. Our system successfully reveals the errors in the input data that would be difficult to capture with simple plots alone. In addition, our system captures some abnormal signal patterns that may indicate intrusions into the system. In summary, this work offers a new and effective way to study attacks or intrusions to traffic signal control systems via the visual analysis of traffic light signal patterns.

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Pranevičius, Henrikas, and Tadas Kraujalis. "KNOWLEDGE BASED TRAFFIC SIGNAL CONTROL MODEL FOR SIGNALIZED INTERSECTION." TRANSPORT 27, no. 3 (2012): 263–67. http://dx.doi.org/10.3846/16484142.2012.719545.

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Intelligent transportation systems have received increasing attention in academy and industry. Being able to handle uncertainties and complexity, expert systems are applied in vast areas of real life including intelligent transportation systems. This paper presents a traffic signal control method based on expert knowledge for an isolated signalized intersection. The proposed method has the adaptive signal timing ability to adjust its signal timing in response to changing traffic conditions. Based on the traffic conditions, the system determines to extend or terminate the current green signal group. Using the information from its traffic detectors of isolated intersection, the proposed controller gives optimal signals to adapt the phase lengths to the traffic conditions. A comparative analysis between proposed control algorithm, fuzzy logic (FLC) and fixed-timed (pre-timed) controllers has been made in traffic flows control, with varying traffic volume levels, by using simulation software ‘Arena’. Simulation results show that the proposed traffic signal control method (EKC) has better performance over fuzzy logic and conventional pre-time controllers under light and heavy traffic conditions.

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LI, KEPING, and ZIYOU GAO. "CONTROLLING THE VEHICLE STATES IN TWO-LANE TRAFFIC." International Journal of Modern Physics C 16, no. 03 (2005): 501–12. http://dx.doi.org/10.1142/s0129183105007315.

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In this paper, we propose a new technique to control the vehicle states in two-lane traffic. A type of the control signals has been designated at a given site (i.e., signal point) of the road. Under the effect of control signal, the drivers on the right lane will slow down when their vehicles pass the signal point. We test this technique for the two-lane traffic model that is based on the deterministic NaSch traffic model. The simulation results indicate that the traffic flow states can be changed from disorder to order by the control signal, and these ordered states are safer.

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Davison, E. J., H. Shimizu, and H. Naraki. "Traffic Signal Control Algorithms of a Traffic Network." IFAC Proceedings Volumes 28, no. 10 (1995): 459–64. http://dx.doi.org/10.1016/s1474-6670(17)51561-x.

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Nashikkar, Siddharth, Aryaa Hanamar, Nuren Pathan, and Heena Mulla. "Traffic Signal Synchronization and Dynamic Control." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 1000–1001. http://dx.doi.org/10.22214/ijraset.2023.56156.

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Abstract: During the past decade, there has been a significant increase in popu- lation combined with ever-increasing automobile sales, resulting in increased traffic around the world. Although modern city infrastructure is designed to han-dle this increasing traffic, it is very difficult to deal with traffic in unplanned partsof cities or cities that were developed hundreds of years ago where congestion was not taken into account. During our analysis, we found that it is not possible to synchronize all the signals in such parts of cities as the distance between each traffic signal is different, with some intersections having very high traffic and the very next having low traffic. We came to the conclusion that although it is im- possible to synchronize all the traffic signals, we can form clusters of 2-3 inter- sections that can be synchronized and the intersection with the highest amount oftraffic will be dynamic i.e., the lane with the highest traffic will get more time. These traffic signals can then be connected through the internet and linked to maps which can show upcoming traffic signals and their real-time status

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Akbas, A., and M. Ergun. "Dynamic traffic signal control using a nonlinear coupled oscillators approach." Canadian Journal of Civil Engineering 32, no. 2 (2005): 430–41. http://dx.doi.org/10.1139/l04-121.

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Traditional signal control systems use prestored timing plans that have been developed offline using historic data. These systems are not responsive to dynamical demand changes of traffic and may deteriorate in performance over time. Dynamic traffic signal control systems can adapt to actual traffic conditions, coping with complex flow patterns and unpredictable variations. They seek continuous optimal system performance. The main goal of this paper is to design a methodology for control of arterial traffic flows. To fulfill this goal, the nonlinear coupled oscillators model is adapted to the traffic signal system of a two-way arterial road. The control methodology is based on measurements of the microscopic occupancy parameters for incoming flows at intersections that have a four-way geometrical structure with four-green splits. The desired signal parameters such as cycle times, green splits, and offsets are adjusted dynamically according to local traffic data. Thus, the desired signal patterns are self-organized through the mutual interactions among the signals. The numerical and case study simulation results demonstrate the effectiveness of the control methodology under the dynamical demand changes of traffic. Key words: traffic control, control systems, nonlinear coupled oscillators, signal control.

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Tomar, Ishu, Indu Sreedevi, and Neeta Pandey. "State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends." Electronics 11, no. 3 (2022): 465. http://dx.doi.org/10.3390/electronics11030465.

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The effective control and management of traffic at intersections is a challenging issue in the transportation system. Various traffic signal management systems have been developed to improve the real-time traffic flow at junctions, but none of them have resulted in a smooth and continuous traffic flow for dealing with congestion at road intersections. Notwithstanding, the procedure of synchronizing traffic signals at nearby intersections is complicated due to numerous borders. In traditional systems, the direction of movement of vehicles, the variation in automobile traffic over time, accidents, the passing of emergency vehicles, and pedestrian crossings are not considered. Therefore, synchronizing the signals over the specific route cannot be addressed. This article explores the key role of real-time traffic signal control (TSC) technology in managing congestion at road junctions within smart cities. In addition, this article provides an insightful discussion on several traffic light synchronization research papers to highlight the practicability of networking of traffic signals of an area. It examines the benefits of synchronizing the traffic signals on various busy routes for the smooth flow of traffic at intersections.

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Yu, Sen Bin, Yong Ju Hu, Xin Sheng He, Si Wei Yang, and Xi Wen Chen. "Single-Line Traffic Lights Wireless Signal Control Device." Applied Mechanics and Materials 178-181 (May 2012): 2721–24. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.2721.

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In the light of tunnel construction, traffic accidents, sudden geological disasters cause of single-line road conditions, designing a single-line road traffic lights wireless signal control device to solve the traffic congestion and the problem of low efficiency of traffic. The device uses wireless transceiver module to sent the signal what was got from the photoelectric sensor to the single-chip microcomputer, single chip microcomputer (SCM) processes switch signals, the last step is to control the traffic light state through the driver circuit. This paper expounds the wireless signal control device trickle structure, working principle, and technical index of the various components, and it puts forward the operation under a feasible solution.

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Zhu, Wen-Xing, and Li-Dong Zhang. "An original traffic flow model with signal effect for energy dissipation." International Journal of Modern Physics C 25, no. 07 (2014): 1450018. http://dx.doi.org/10.1142/s0129183114500181.

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We proposed an original traffic flow model with a consideration of signal effect based on Bando's optimal velocity model. The optimal velocity function was improved more realistically in describing the motion process of vehicles moving on a road with signals. Based on the improved model, we derived the mathematical expression for energy dissipation. Simulations are conducted to verify the energy dissipation laws in traffic flow with signals. Numerical results show that energy dissipation (rate) can be affected not only by traffic density, but also traffic signal control parameters: split and cycle.

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Hongo, Kazutaka, Hayashi Kentaro, Yoshinori Akinaga, Masahiro Kourogi, Makoto Miyauchi, and Seiichi Serikawa. "Development of LED Road Traffic Signal Considering Washout Phenomenon." Journal of the Institute of Industrial Applications Engineers 2, no. 2 (2014): 58–61. http://dx.doi.org/10.12792/jiiae.2.58.

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Kozin, Yuriy. "Road Traffic Light in New Configuration." Journal of Road Safety 32, no. 1 (2021): 52–54. http://dx.doi.org/10.33492/jrs-d-20-00253.

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The three-color system containing signals of the same circular shape has been in existence for over a hundred years. Each traffic signal has been justifiably selected to have a special color light to correspond to human psychoemotional reaction (red – stop, yellow – caution, green – go) to a given color signal (British Standards, 2015) and to comply with the laws of physics (The Motivated Engineer, 2015) – Rayleigh’s scattering law (Banc SpaceTek, 2017). The main downsides of the traditional road traffic light include the following: • The uniform circular shape of light signals results in uncertainty and difficulties for road users with color blindness and visual impairments, resulting in the need for restrictions or bans on driving license issuance in some countries. This uncertainty becomes particularly acute in conditions of low visibility. • According to the concept of harmony of form and color (Itten, 1961), a green light alone corresponds to the circular (spherical-like) shape of the signal. Red and amber lights harmoniously combine with other geometrical shapes. • The uniform shape of light signals prevents the implementation of the original compact combined model of traffic lights. For example, during the day, colorblind people can tell which signal is which because there is a standard position assigned: top – bottom or right – left (Oliveira, Souza, Junior, Sales & Ferraz, 2015). This becomes problematic if the compact combined models of traffic lights are used. Engineers and inventors have been trying to solve these problems by introducing random changes in the light signal shape and complicating the traffic light design. For a long time there have been different proposals about how to eliminate the demerits of the existing traffic lights: from arbitrary changes in the signal shape (Patterson, 1988) to transformation of traffic lights into a single-section display panel (Kulichenko, 2011) which replaces among others stationary road signs. However, technical solutions like these deprive the traffic light of its signal uniformity and conciseness (simplicity, clarity and precision of its controlling effect), features which help safe traffic regulation in a busy and dynamic mode. Technical modernization of individual signal components has been going hand in hand with technological developments as light sources, diffusers, lenses, controllers, materials, control systems, timers, etc. are improved. However, adequate design and aesthetic proposals are considerably behind. The aim of this paper is to propose a concept of creating control signals of traffic light that harmonize color and form, and, as a result, to create a new model of traffic light that will be convenient for all road users.

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V, Parinitha, Jahnavi Reddy, Navya LS, and Ratna V. Mulimani. "REAL TIME TRAFFIC MANAGEMENT SYSTEM." International Journal of Innovative Research in Advanced Engineering 9, no. 8 (2022): 261–66. http://dx.doi.org/10.26562/ijirae.2022.v0908.21.

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Every day, there are more cars on the road, and conventional traffic control techniques can't keep up with the volume of traffic. The traditional method only succeeds in the current environment if the number of vehicles is low; if the number of vehicles increases and becomes disproportionately heavier on one side of the road, the method fails. Our objective is to transition the static traffic signal system into a signal switching system that can manage and monitor signals in real-time. As a result, in this research, the signal switching time will be precisely determined in congested traffic utilizing real-time image detection. This approach may be able to relieve backed-up traffic in a quicker and more effective way.

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Noland, Robert B. "Pedestrian Travel Times and Motor Vehicle Traffic Signals." Transportation Research Record: Journal of the Transportation Research Board 1553, no. 1 (1996): 28–33. http://dx.doi.org/10.1177/0361198196155300104.

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Traffic signals generally have been installed to maximize the flow of motor vehicle traffic by reducing the average travel delay time. Under free-flow conditions, motor vehicle travel delay is very sensitive to the amount of green phase and the total cycle of the traffic signal. Average pedestrian delay at traffic signals is not taken into account. Some simple examples are used to demonstrate that travel time delay costs to pedestrians caused by existing signalization cycles may often result in increased travel time costs to society. In areas with heavy pedestrian traffic (or during peak pedestrian hours), traffic signals should trade off the costs of motor vehicle delay with pedestrian delay. This may suggest that in some areas, motor vehicle traffic should be banned or severely restricted. Narrower street widths that can allow reduced total signal cycle times can also reduce pedestrian delay.

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Weerasundara, W. A. G., D. P. D. Udugahapattuwa, T. D. Munasingha, W. D. K. Gunathilake, and Udaya Dampage. "An Adaptive and Greener Traffic Signal Coordination Scheme for Transport 4.0." International Journal of Engineering and Technology 14, no. 2 (2022): 24–33. http://dx.doi.org/10.7763/ijet.2022.v14.1197.

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Traffic congestion has become a major concern, aroused as a result of increased population and urbanization. Hence, novel and innovative methods for controlling ever-increasing traffic volumes are essential. Conventional traffic light schemes are the most popular method of controlling traffic, and it is logical and economical to make research endeavors to optimize their existing performance. Despite numerous studies, the aforementioned problem has not been optimally and sufficiently solved. In this research, we introduce an adaptive traffic signaling scheme based on vehicle density to facilitate optimal traffic signal control as well as effective traffic management. We also propose effective coordination of the traffic amongst the junctions. Here, the live video is utilized as an input provided to a deep Q network to provide adaptive phase timings as the output. In the proposed scheme, we introduced per car unit (PCU) as a novel parameter to represent the effect of each vehicle type on traffic conditions. Numerous filed trials on real-time data amply prove that the proposed scheme enhances the average speed of traffic up to 5.597 km/h. The proposed scheme shows an average increment of 175.71% in average mean speed compared to the existing static schemes. Except for the high traffic scenario, for both mid traffic and low traffic scenarios, the proposed scheme shows a considerable improvement in both average densities and maximum densities. In the mid-traffic scenario, the average speed shows an improvement of 3.85 km/h, while in the low traffic scenario, the average mean speed shows an improvement of 7.96 km/h. A reduction in fuel consumption and average delay were also observed, which will lead to a greener Transport 4.0.

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Mathew, Jijo, Howell Li, and Darcy M. Bullock. "Using Stochastic Variation of Cyclic Green Distributions to Populate SAE J2735 Message Confidence Values along a Signalized Corridor." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 9 (2020): 426–37. http://dx.doi.org/10.1177/0361198120929337.

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The communication between connected vehicles and traffic signal controllers is defined in SAE Surface Vehicle Standard J2735. SAE J2735 defines traffic signal status messages and a series of 16 confidence levels for traffic signal transitions. This paper discusses a statistical method for tabulating traffic signal data by phase and time of day and populating the SAE J2735 messages. Graphical representations of the red–green and green–yellow transitions are presented from six intersections along a 4-mile corridor for five different time-of-day timing plans. The case study provided illustrates the importance of characterizing the stochastic variation of traffic signals to identify locations, phases, and time-of-day periods when traffic indications operate with high predictability. Specific cases, such as low vehicle demand and occasional actuation of pedestrian phases are highlighted as situations that may reduce the predictability of traffic signal change intervals. The results from this study also open up discussion among transportation professionals on the importance of consistent tabulation of confidence values for both beginning and end of green signal states. We believe this paper will initiate dialog on how to consistently tabulate important data elements transmitted in SAE J2735 and perhaps refine those definitions. The paper concludes by highlighting the importance of traffic engineers and connected vehicle developers to work together to develop shared visions on traffic signal change characteristics so that the in-vehicle use cases and human–machine interface meet user expectations.

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Arikumar, Kochupillai Selvaraj, Sahaya Beni Prathiba, Shakila Basheer, Rajalakshmi Shenbaga Moorthy, Ankur Dumka, and Mamoon Rashid. "V2X-Based Highly Reliable Warning System for Emergency Vehicles." Applied Sciences 13, no. 3 (2023): 1950. http://dx.doi.org/10.3390/app13031950.

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Vehicle-to-everything (V2X) in networks is a communication technology that allows vehicles to communicate with their surroundings. Traffic congestion and unawareness of the travel of emergency vehicles (EVs) lead to delays in reaching the destination of the EV. In order to overcome this time delay, we propose a jitter-to-highly reliable (J2H) approach of customizing the traffic signals and an alert passer mechanism to alert other vehicles. Once an EV is started, its source, destination and level of emergency will be updated on the network, and based on the traffic density, the fastest route to reach the destination is determined. The V2X system in the J2H approach passes an alert to all the traffic signals on that route. The traffic signals will continuously monitor the position of the vehicle by using the Global Positioning System (GPS). Based on the position of the vehicle, the distance between the vehicle and the traffic signal on that route is periodically updated. Once the vehicle comes within the range of the closest traffic signal, based on constraints such as number of lanes, emergency level, types of roads, traffic density, number of EVs approaching, and time of arrival of the vehicles, the traffic signal will be customized. The V2X then passes the information to all the traffic signals that are available in the route of the EV. The alert passer mechanism warns about the approaching EV to other vehicles on that route. Thus, by adapting the J2H technique, EVs can overcome the time delay to reach the destination. Traffic congestion is overcome by customizing the traffic signals. Path blockage can be cleared by vehicle-to-vehicle (V2V) communication.

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Astarita, Vittorio, Vincenzo Giofré, Demetrio Festa, Giuseppe Guido, and Alessandro Vitale. "Floating Car Data Adaptive Traffic Signals: A Description of the First Real-Time Experiment with “Connected” Vehicles." Electronics 9, no. 1 (2020): 114. http://dx.doi.org/10.3390/electronics9010114.

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The future of traffic management will be based on “connected” and “autonomous” vehicles. With connected vehicles it is possible to gather real-time information. The main potential application of this information is in real-time adaptive traffic signal control. Despite the feasibility of using Floating Car Data (FCD), for signal control, there have been practically no real experiments with all “connected” vehicles to regulate traffic signals in real-time. Most of the research in this field has been carried out with simulations. The purpose of this study is to present a dedicated system that was implemented in the first experiment of an FCD-based adaptive traffic signal. For the first time in the history of traffic management, a traffic signal has been regulated in real time with real “connected” vehicles. This paper describes the entire path of software and system development that has allowed us to make the steps from just simulation test to a real on-field implementation. Results of the experiments carried out with the presented system prove the feasibility of FCD adaptive traffic signals with commonly-used technologies and also establishes a test-bed that may help others to develop better regulation algorithms for these kinds of new “connected” intersections.

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Skabardonis, Alexander, Robert L. Bertini, and Brian R. Gallagher. "Development and Application of Control Strategies for Signalized Intersections in Coordinated Systems." Transportation Research Record: Journal of the Transportation Research Board 1634, no. 1 (1998): 110–17. http://dx.doi.org/10.3141/1634-14.

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Modern controllers permit traffic signals in coordinated systems to operate as pretimed, semiactuated or fully actuated to improve the traffic performance at the particular intersection or over the total system. Criteria were established for selecting the type of control, and timing strategies were developed for signals in coordinated systems. The proposed strategies were evaluated through simulation on 14 representative real-world arterials and grid networks. Based on the analysis of the simulation results, guidelines were formulated to assist practicing traffic engineers in selecting the most appropriate control strategies at specific intersections in coordinated signal systems. The guidelines were then applied to select the type of signal control at several intersections in the City of Los Angeles. The results from before and after field studies indicate that the recommended control strategies improved traffic performance, and the study guidelines can be used as an operating tool for traffic signal management.

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Postranskyy, Taras, and Kateryna Khoreva. "The influence of the traffic light`s permissive signal share on the duration of traffic delays." Transport technologies 2022, no. 2 (2022): 63–71. http://dx.doi.org/10.23939/tt2022.02.063.

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Today, the motorization level and the value of traffic flow on the street-road network have increased. Often this leads to an excessive load on the existing traffic management system, highways, and roads. As a result, the number and duration of traffic delays are increasing, especially within populated areas. The consequence of this is the formation of traffic jams, increase of fuel and lubricants consumption, noise pollution, and emissions of exhaust gases. Another, no less critical consequence is an increase in traffic accidents, particularly at unsignalized intersections. Therefore, a traffic light control system is often implemented at street intersections to increase traffic safety and reduce the number of conflicting flows. In addition, this system should be optimized for signalized objects. The object of the study is a signalized intersection of multi-lane streets located in the city. The main problem that needs to be solved is the reduction of the vehicles` delay duration at the approaches to such intersections, in particular with the use of appropriate organizational measures and planning of the traffic light control system. According to the study's results, regularities were revealed regarding the change in the traffic's delay duration depending on the share of the permissive signal and the duration of the traffic light's cycle at the street intersection. At the same time, the received modulation results in the PTV Vissim software environment indicate an increase in delay values with an increase in the duration of the traffic light cycle. However, an equally important influence factor is the share of the permissive signal, as it reduces to a certain extent the duration of vehicles in standby mode at the approaches to the signalized intersection. The obtained results are recommended to be used in both developing new traffic organization schemes at signalized street intersections and improving existing ones.

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Astarita, Vittorio, Vincenzo Pasquale Giofrè, Giuseppe Guido, and Alessandro Vitale. "A Single Intersection Cooperative-Competitive Paradigm in Real Time Traffic Signal Settings Based on Floating Car Data." Energies 12, no. 3 (2019): 409. http://dx.doi.org/10.3390/en12030409.

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New technologies such as "connected" and "autonomous" vehicles are going to change the future of traffic signal control and management and possibly will introduce new traffic signal systems that will be based on floating car data (FCD). The use of floating car data to regulate traffic signal systems, in real time, has the potential for an increased sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. However, research has never explored how not "connected" vehicles would benefit by the implementation of such systems. This paper explores the use of floating car data to regulate traffic signal systems in real-time in a single intersection and in terms of cooperative-competitive paradigm between "connected" vehicles and conventional vehicles. In a dedicated laboratory, developed for testing regulation algorithms, results show that "invisible vehicles" for the system (which are not "connected") in most simulated cases also benefit when real time traffic signal settings based on floating car data are introduced. Moreover, the study estimates the energy and air quality impacts of a single intersection signal regulation by evaluating fuel consumption and pollutant emissions. Specifically, the study demonstrates that significant improvements in air quality are possible with the introduction of FCD regulated traffic signals.

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SAMSON, AJIBESIN, PONNLE AKINLOLU, and OYEDEPO OLUGBENGA. "SMART TRAFFIC SIGNAL CONTROL SYSTEM FOR TWO INTER-DEPENDENT INTERSECTIONS IN AKURE, NIGERIA." Journal of Engineering Studies and Research 28, no. 3 (2022): 82–92. http://dx.doi.org/10.29081/jesr.v28i3.010.

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The increasing growth in urban population and vehicular volume coupled with inefficient traffic management results in traffic congestion on road networks. In this work, a smart/intelligent traffic signal control system was developed for two inter-dependent intersections in Akure, Nigeria. The system developed in this work uses deep learning and computer vision techniques to estimate the density of traffic and uses this information to adaptively switch traffic signals based on the traffic density estimated. Simulation results show that in 30 minutes of simulation, 32 signal cycles can be achieved and 967 vehicles can move at these two inter-dependent intersections

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Dhamija, Srishti, Alolika Gon, Pradeep Varakantham, and William Yeoh. "Online Traffic Signal Control through Sample-Based Constrained Optimization." Proceedings of the International Conference on Automated Planning and Scheduling 30 (June 1, 2020): 366–74. http://dx.doi.org/10.1609/icaps.v30i1.6682.

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Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such an approximation degrades schedule quality with respect to expected delay as vehicle turn uncertainty at intersections increases. We introduce TUSERACT (TUrn-SamplE-based Real-time trAffic signal ConTrol), an approach that minimizes expected delay over samples of turn movement uncertainty of vehicles. Specifically, our key contributions are: (a) By exploiting the insight that vehicle turn movements do not change with traffic signal control schedule, we provide a scalable constraint program formulation to compute a schedule that minimizes expected delay across multiple vehicle movement samples for a traffic signal; (b) a novel mechanism to coordinate multiple traffic signals through vehicle turn movement samples; and (c) a comprehensive experimental evaluation to demonstrate the utility of TUSERACT over SURTRAC, a leading approach for online traffic signal control which makes the aforementioned approximation. Our approach provides substantially lower (up to 60%) mean expected delay relative to SURTRAC with very few turn movement samples while providing real-time decision making on both real and synthetic networks.

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Ji, Yuxiong, Yu Tang, Wei Wang, and Yuchuan Du. "Tram-Oriented Traffic Signal Timing Resynchronization." Journal of Advanced Transportation 2018 (September 2, 2018): 1–13. http://dx.doi.org/10.1155/2018/8796250.

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Modernized trams usually run on exclusive rail lanes along urban streets, but they share the right of way with general vehicles at intersections and often get interrupted by traffic signals. We developed a mixed integer model to resynchronize traffic signal timings to favor tram movements. The objective is to balance the operational needs between minimizing bidirectional tram travel times and reducing the likelihood of activating the green extensions. The model depicts both tram and vehicle progressions in one signal timing plan, making it possible to control the impact of signal timing resynchronization through traffic. Trams following the tram bands produced by the proposed model are prevented from being stopped by red phases at signalized intersections. The applicability and effectiveness of the proposed model were demonstrated in a real-world case study. Compared with the state-of-the-art practice approach, the developed model reduced tram travel time by 10% with lower negative impacts on traffic on side streets. The reduction in tram travel time was obtained without sacrificing the mobility of through traffic.

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Nameda, Naoyoshi. "Measurement of Traffic Signal Colors." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 73, no. 6 (1989): 319–24. http://dx.doi.org/10.2150/jieij1980.73.6_319.

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Zwahlen, Helmut T., Andrew Russ, Şahika Vatan, Jessica Hirth, and Ken Greene. "Traffic-Signal Group Relamping Model." Transportation Research Record: Journal of the Transportation Research Board 1877, no. 1 (2004): 17–25. http://dx.doi.org/10.3141/1877-03.

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Kumar, Er Neeraj. "Study of Design Traffic Signal." International Journal for Research in Applied Science and Engineering Technology 7, no. 5 (2019): 3715–20. http://dx.doi.org/10.22214/ijraset.2019.5611.

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Journal articles on the topic 'Traffic signal'

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