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Journal articles on the topic 'Traffic system control'

Author: Grafiati

Published: 19 February 2023

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1

Gaikwad, Anand, Shreya Shreya, and Shivani Patil. "Vehicle Density Based Traffic Control System." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 511–14. http://dx.doi.org/10.31142/ijtsrd10938.

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2

suryawanshi, Prof Ranjeetsingh, Ms Pooja Mahajan, and Ms Harshada Jagtap. "Traffic Control System." IJARCCE 7, no. 11 (November 30, 2018): 183–85. http://dx.doi.org/10.17148/ijarcce.2018.71141.

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3

T M, Inba Malar, Bharatha Sreeja G, Amala Justus Selvam M, Jemima Sharon E, Jeevitha K, Keerthi R, and Mahalashmi R. "Intelligent Traffic Control System Using Deep Learning." ECS Transactions 107, no. 1 (April 24, 2022): 2783–90. http://dx.doi.org/10.1149/10701.2783ecst.

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Traffic congestion and regulating traffic in traffic signals are major issues in cities. Nowadays, in most of the cities, traffic management centers installed numerous cameras all over the roads and traffic signals. Such cameras can be effectively used for the automation of traffic signals. The objective is to develop a real time system that can automatically monitor real time traffic and make the system intelligent using artificial intelligence techniques. Specifically, Deep Convolutional Neural Networks are employed to perform the task. From statistical traffic data, it determines count, type of vehicle, average speed, distance between vehicles, etc. Based on traffic, the algorithm instructs to stop vehicle or queue or move. It can also record a wrong-way driver. Using license plate recognition, security applications such as unauthorized vehicles are identified. If there is violation of traffic rules, they are recorded with registration number. It can detect ambulances and give first preference. The proposed algorithm identifies VIP vehicles and clear traffics in automated ways. Ambulances are given priority to pass the road. The entire system have been developed using a standalone-Graphical User Interface (GUI). We have implemented successfully and the proposed framework performs satisfactorily.

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4

Zaidi, Subiya, Harshita Yadav, Hemant Kumar Chaudhary, Hrithik Puri, and Kartikeya Saraswat. "Dynamic Traffic Control System." Journal of Big Data Technology and Business Analytics 1, no. 2 (July 28, 2022): 25–31. http://dx.doi.org/10.46610/jbdtba.2022.v01i02.004.

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A country with a population of 1.3 billion and almost 300 million vehicles, India is one of the biggest contributors to traffic jams, vehicle- specific pollution, and chronic lung diseases. To manage the footfall of this gigantic urban population, and the vehicles, our country has blindly poured in resources towards both active and passive traffic management, investing in measures such as smart traffic management systems and deploying enormous armies of traffic police to handle intersections and exits. The paper aims, towards showcasing a dynamic, fully autonomous model, that uses real-time feeds from existing traffic junctions/ intersection cameras, process them and provide an intensity score based on the density of traffic in each adjoining lane. The system, based upon the intensity scores, provides suitable traffic go time to each lane. The model also scans for emergency vehicles in each lane, to provide a priority pass to such vehicles.

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Galkin, A. V., A. S. Sysoev, and N. S. Bondar. "AUTOMATED TRAFFIC CONTROL SYSTEM." Mathematical Methods in Technologies and Technics, no. 7 (2022): 11–15. http://dx.doi.org/10.52348/2712-8873_mmtt_2022_7_11.

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6

Pardesi, M. A., Saquib S. Aowte, Tanmay V. Kakare, Revati U. Bhosale, and Swayambhoo R. Pati. "ADAPTIVE TRAFFIC CONTROL SYSTEM." International Journal of Engineering Applied Sciences and Technology 04, no. 09 (January 30, 2020): 421–23. http://dx.doi.org/10.33564/ijeast.2020.v04i09.056.

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7

Chandel, Shiva, Shubhransh Yadav, and Sandeep Yadav. "Modern traffic control system." Malaya Journal of Matematik S, no. 1 (January 2018): 22–25. http://dx.doi.org/10.26637/mjm0s01/04.

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8

R U, Yawle, Kiran K.Modak, Parmeshwar S.Shivshette, and Snehal S.Vhaval. "Smart Traffic Control System." International Journal of Electronics and Communication Engineering 3, no. 3 (March 25, 2016): 20–23. http://dx.doi.org/10.14445/23488549/ijece-v3i3p106.

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9

Choudhary, Vineeta, Shrey Tank, Kriti Gulati, Shubham Jani, and Bhaumik Machhi. "Adaptive Traffic Control System." International Journal for Research in Applied Science and Engineering Technology 11, no. 2 (February 28, 2023): 495–99. http://dx.doi.org/10.22214/ijraset.2023.49068.

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Abstract: Whenever we hear the word traffic, we all think of people blaring horns and waiting endlessly, stress is always silent but prominent in the word traffic. We all face traffic daily and have experienced the frustration and stress that traffic induces. Our project focuses on reducing the traffic waiting time significantly and hence reducing air and noise pollution. Less waiting time at traffic means less wastage of fuel leading to energy conservation in the times of a global warming

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10

Gopalakrishnan, Karthik, and Hamsa Balakrishnan. "Control and Optimization of Air Traffic Networks." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (May 3, 2021): 397–424. http://dx.doi.org/10.1146/annurev-control-070720-080844.

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The air transportation system connects the world through the transport of goods and people. However, operational inefficiencies such as flight delays and cancellations are prevalent, resulting in economic and environmental impacts. In the first part of this article, we review recent advances in using network analysis techniques to model the interdependencies observed in the air transportation system and to understand the role of airports in connecting populations, serving air traffic demand, and spreading delays. In the second part, we present some of our recent work on using operational data to build dynamical system models of air traffic delay networks. We show that Markov jump linear system models capture many of the salient characteristics of these networked systems. We illustrate how these models can be validated and then used to analyze system properties such as stability and to design optimal control strategies that limit the propagation of disruptions in air traffic networks.

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11

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

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

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12

Agarwal, Bikash, Sanidhya Rasiwasi, Shyam Agarwal, and Roshan Kumar. "Intelligent Highway Control System for Managing Traffic on Highway Intersections." International Journal of Engineering and Technology 4, no. 2 (2012): 153–57. http://dx.doi.org/10.7763/ijet.2012.v4.338.

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13

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

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

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14

KANAKAM, VYSHNAVI, and RAGHUNATH SWAPNA. "INTELLIGENT TRAFFIC LIGHT CONTROL SYSTEM." i-manager’s Journal on Image Processing 8, no. 2 (2021): 9. http://dx.doi.org/10.26634/jip.8.2.18188.

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15

Jose, Pinky Ann. "Smart Traffic Congestion Control System." International Journal for Research in Applied Science and Engineering Technology 8, no. 7 (July 31, 2020): 1210–13. http://dx.doi.org/10.22214/ijraset.2020.30438.

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16

Ferro-Novick, Susan, and Nils Brose. "Traffic control system within cells." Nature 504, no. 7478 (December 2013): 98. http://dx.doi.org/10.1038/504098a.

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17

IZUMI, Takashi, and Satoshi TAKAHASHI. "ITS and Traffic Control System." Journal of The Institute of Electrical Engineers of Japan 142, no. 11 (November 1, 2022): 712–15. http://dx.doi.org/10.1541/ieejjournal.142.712.

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18

POOJA, MISHRA, PATIL SUVARNA, and BHENDE MANISHA. "SMART TRAFFIC CONTROL SYSTEM FOR CONGESTION CONTROL." i-manager's Journal on Digital Signal Processing 9, no. 2 (2021): 21. http://dx.doi.org/10.26634/jdp.9.2.16145.

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19

Spall, James C., and Daniel C. Chin. "Traffic-responsive signal timing for system-wide traffic control." Transportation Research Part C: Emerging Technologies 5, no. 3-4 (August 1997): 153–63. http://dx.doi.org/10.1016/s0968-090x(97)00012-0.

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20

Henderson, J. Isaac, and M. Aravind. "Intelligent Traffic Control System Using Ad-Hoc Wireless sensor Systems." International Journal of Students' Research in Technology & Management 3, no. 4 (September 27, 2015): 333–35. http://dx.doi.org/10.18510/ijsrtm.2015.346.

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This paper deals with designing an automatic traffic control system which works on principle of TRAFFIC DENSITY monitored by Sensors on each side which provides direct information to microcontroller which rerforms decision making to allow traffic based on density. The three density zones are low, medium and high. In each zone an ad hoc sensor is placed. Each sensor will check the presence of the vehicle in the zone using infrared technology and then ad hoc sensor sends the data to master ad hoc. To locate the sensor, each sensor of different zone is addressed by user and that address is fed to the master ad hoc sensor. This master ad hoc sensor will arrange the data from various sensors in an 8 bit data format. It then performs the required processing to determine the green signal time for each side. It has an exceptional system for high priority vehicles like ambulance, as it senses the direction of arrival of these vehicles and gives a green corridor. The main advantage over conventional system is that a side with heavy traffic doesn’t have to wait unreasonably while a side with no/less traffic gets an equal amount of time as that of heavy traffic side which is irascible. This is an improved system based on preference for urgency/density of traffic. This can prove useful in especially Junctions of importance, thereby mediating traffic flow correctly.

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21

Kosanam, Bindu Varshini, and Abhinay Kukkadapu. "Swarm Intelligence Based Traffic Control System." IRA-International Journal of Technology & Engineering (ISSN 2455-4480) 7, no. 2 (May 27, 2017): 46. http://dx.doi.org/10.21013/jte.v7.n2.p5.

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<div><p class="Abstract"><em>Traffic congestion is one of the major problems in many of metro cities all over the world today. It affects daily life in many aspects such as improper time management, stress, frustration which leads to reckless driving. Average time to reach destination is decided by travel speed which is directly proportional to traffic congestion and also the wait time at each and every traffic signal. In this paper a novel Swarm Intelligence based Traffic Control System (SITS) inspired from nature mimicking (Particle Swarm Optimization) is discussed. This State of the art SITS with Six Degrees of Separation approach to traffic congestion is applying swarm intelligence to traffic lights to avoid waiting of vehicles at red light decreasing wait time and congestion. Here cars will not take random paths or will not take dynamic routes. Six degrees of separation will be employed at each node (traffic signal) to limit computational power and to improve efficiency.</em></p></div>

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22

Royko, Yuriy, Yurii Yevchuk, and Romana Bura. "Minimization of traffic delay in traffic flows with coordinated control." Transport technologies 2021, no. 2 (December 10, 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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23

Malkar, Prof M. S. "Smart City Traffic Congestion Control System." International Journal for Research in Applied Science and Engineering Technology 6, no. 1 (January 31, 2018): 805–6. http://dx.doi.org/10.22214/ijraset.2018.1122.

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24

R, Sooraj, N. S. Rajesh, R. Praveen Kumar, and N. Saravana Kumar. "Intelligent Traffic Control System using RFID." International Journal of Communication and Networking System 5, no. 2 (December 15, 2016): 121–22. http://dx.doi.org/10.20894/ijcnes.103.005.002.006.

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25

SinghSaini, Bhupinder, Ankur Sodhi, and Baljit Singh Saini. "Coordinated Intelligent Traffic Control System (CITCS)." International Journal of Applied Information Systems 4, no. 7 (December 15, 2012): 11–14. http://dx.doi.org/10.5120/ijais12-450794.

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26

Israni, Ms Kiran. "Traffic Control System using Image Processing." International Journal for Research in Applied Science and Engineering Technology 7, no. 5 (May 31, 2019): 504–8. http://dx.doi.org/10.22214/ijraset.2019.5085.

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27

Sharma, Abhilash. "Area based Dynamic Traffic Control System." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (June 30, 2019): 1782–87. http://dx.doi.org/10.22214/ijraset.2019.6299.

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28

kanrar, Soumen. "Efficient Traffic Control of VoD System." International journal of Computer Networks & Communications 3, no. 5 (September 30, 2011): 95–106. http://dx.doi.org/10.5121/ijcnc.2011.3507.

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29

Prasad, V. V. S. Maruthy, and Shuba Swaminathan. "Voice Governed Traffic Light Control System." IETE Journal of Education 36, no. 2-3 (April 1995): 115–20. http://dx.doi.org/10.1080/09747338.1995.11415622.

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30

Taher, Fady, Ayman EL-SAYED, Ahmed Shouman, and Ahmed Elmahalawy. "Hierarchal Clusters Based Traffic Control System." Menoufia Journal of Electronic Engineering Research 29, no. 1 (January 1, 2020): 1–12. http://dx.doi.org/10.21608/mjeer.2020.68928.

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31

Nikolaev, Andrey Borisovich, and Yuliya Sergeevna Sapego. "Development of Traffic Accidents Control System." International Journal of Advanced Studies 5, no. 1 (May 31, 2015): 8. http://dx.doi.org/10.12731/2227-930x-2015-1-2.

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32

Nikolaev, Andrey Borisovich, and Yuliya Sergeevna Sapego. "Development of Traffic Accidents Control System." Automation and Control in Technical Systems, no. 1 (April 5, 2015): 45. http://dx.doi.org/10.12731/2306-1561-2015-1-6.

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33

Barz, C., C. Todea, T. Latinovic, D. M. Preradovic, S. Deaconu, and A. Berdie. "Intelligent traffic control system using PLC." IOP Conference Series: Materials Science and Engineering 144 (August 2016): 012017. http://dx.doi.org/10.1088/1757-899x/144/1/012017.

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34

Gowri, S., R. Sathiyavathi, and J. S. Vimali. "Time-sensitivity based traffic control system." Contemporary Engineering Sciences 8 (2015): 7–11. http://dx.doi.org/10.12988/ces.2015.411247.

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35

Athani, V. V. "A microprocessor-based traffic control system." Journal of Microcomputer Applications 8, no. 2 (April 1985): 181–88. http://dx.doi.org/10.1016/0745-7138(85)90017-x.

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36

Keong, Chin Kian. "The GLIDE system—Singapore's urban traffic control system." Transport Reviews 13, no. 4 (October 1993): 295–305. http://dx.doi.org/10.1080/01441649308716854.

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37

Sun, Chunling, and Fuhai Liu. "Simulation and Research of Urban Intelligent Traffic Light Control System." Journal of Physics: Conference Series 2068, no. 1 (October 1, 2021): 012043. http://dx.doi.org/10.1088/1742-6596/2068/1/012043.

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Abstract Intelligent traffic light control system belongs to the field of transportation public safety control. So far, the traffic light control system on the market cannot change the working time of the traffic lights according to the actual traffic flow, which is not conducive to the easing of the traffic flow and easy to cause traffic jams. Therefore, it is necessary to solve the problem of the existing traffic light control system which cannot adjust the working hours of the traffic light according to the actual road conditions, so as to alleviate the traffic jam at the intersection to a certain extent. In this paper, the design of intelligent traffic light control system uses AT89C51 MCU as the core device. The system controls the traffic of different times and different conditions, and it can alleviate traffic jam to a certain extent. This paper analyzes the hardware and software designes of intelligent traffic light control system, and simulates traffic light control by simulation software. The system of this paper is simple in structure, economical and practical, reliable in operation and it can effectively dredge the traffic.

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38

Durso, Francis T., and Carol A. Manning. "Air Traffic Control." Reviews of Human Factors and Ergonomics 4, no. 1 (October 2008): 195–244. http://dx.doi.org/10.1518/155723408x342853.

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Determining how the controller (or air navigation service provider) of the future will function in tomorrow's Next Generation Air Transportation System (NextGen) will require an understanding of the existing literature. In this chapter, after an analysis of the controller's job, we focus on technology, which is an important factor in air traffic control (ATC) today and will become increasingly so in NextGen. We then turn to workload and the extent to which it can be predicted. From human-technology interaction and workload, we move to the multiple facets of cognition thought to underlie these and other aspects of the controller's job. Beyond individual cognition, we review collaboration among controllers and discuss both synchronous cooperation and the cooperative shift change. As we move up the system, we look at error, risk, and safety. Finally, we consider the work on controller selection, covering both “select-in” (KSAOs) and “select-out” (e.g., medical and suitability) factors. For NextGen to be successful, human factors researchers must determine from today's research how the human operator can best function to provide ATC services in the future.

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39

Sukhova, T. S., O. V. Aleksashina, and O. N. Grinyuk. "AIR TRAFFIC CONTROL BASICS." Spravochnik. Inzhenernyi zhurnal, no. 295 (October 2021): 53–56. http://dx.doi.org/10.14489/hb.2021.10.pp.053-056.

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The concept of flight safety is considered, the features and purpose of the air traffic control system, the air traffic control complex, the capabilities of the system that ensure flight safety are presented.

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40

K, Renuka. "An Optimized Intelligent Transport System to Control Traffic in Internet of Vehicles." Journal of Advanced Research in Dynamical and Control Systems 51, SP3 (February 28, 2020): 420–31. http://dx.doi.org/10.5373/jardcs/v12sp3/20201277.

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41

Kim, J. L., J. C. S. Liu, P. I. Swarnam, and T. Urbanik. "The areawide real-time traffic control (ARTC) system: a new traffic control concept." IEEE Transactions on Vehicular Technology 42, no. 2 (May 1993): 212–24. http://dx.doi.org/10.1109/25.211459.

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42

Kulkarni, Swarup Suresh, and Dr Roshani Ade. "Intelligent Traffic Control System Implementation for Traffic Violation Control, Congestion Control and Stolen Vehicle Detection." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 5, no. 2 (July 6, 2017): 57. http://dx.doi.org/10.3991/ijes.v5i2.7230.

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<p>Traffic is significant issue in our nation, particularly in urban ranges. Aftereffect of this, activity clog issue happens. Crisis vehicle like rescue vehicle, fire unit, squad cars confront bunches of issue to achieve their goal on account of congested driving conditions, coming about loss of human lives. To minimize this issue we approach new idea name as ”Traffic control framework for blockage control and stolen Vehicle location”. In this framework activity freedom done by transforming Red flag into Green flag. We demonstrate idea of what is called ”Green wave”. Alongside this, we distinguish stolen vehicle by utilizing extremely advantageous RFID innovation. In the event that stolen vehicle is been distinguished, the framework gives ready sign through ringer. Framework sends Message with the assistance of GSM to Police station. In this framework we Use diverse RFID labels for recognizing rescue vehicle, stolen Vehicles. On the off chance that Red flag is on and IR sensor is initiated, then framework gives ringer alarm to movement police. This is novel framework which encourage great answer for comprehend traffic clog.</p>

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43

Kumar, Harsh, Vijay Kumar, Bharat Singh, and Manish Saraswat. "Design and Fabrication of Street Light Management and Control System." International Journal of Materials Manufacturing and Sustainable Technologies 1, no. 2 (December 30, 2022): 10–21. http://dx.doi.org/10.56896/ijmmst.2022.1.2.008.

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In India, most of the streets within the habitations are illuminated from evening until morning, averaging roughly 12 hours per day. Throughout the night, some streets may not have automobiles or even pedestrians travelling through them which results in power loss. In addition, the number of vehicles on the road is increasing every day, and traditional traffic management is still in use, road accidents are one of our country's key issues. Many important lives are lost as a result of these accidents, which occur when emergency assistance is unavailable. So, our proposed solution for this problem is that we are designing a model that first detects the traffic and examine then based on situation it controls the lightening system and send traffic intensity data to internet hour wise. For accident detection we used the SOS button to get help immediately and crewman get the exact location of accident. According to the results obtained from the proposed method, energy usage is greatly reduced, and we can receive a very quick alarm when something unpleasant occurs.

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44

Nowakowski, Waldemar, Piotr Bojarczyk, and Zbigniew Łukasik. "Functional analysis of railway traffic control system using an expert system." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 19, no. 6 (June 30, 2018): 627–31. http://dx.doi.org/10.24136/atest.2018.145.

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The major functionality of railway traffic control system is to ensure efficient and safe railway traffic. Contemporary technique, electronics and informatics in particular, allows for automation of more and more tasks in transportation processes. Irrespective of the manufacturing technology, railway traffic control systems have to meet specific safety requirements. Because of this, these systems belong to group of safety-critical systems, also called safety-related systems. Due to these requirements, development, building and verification processes of railway traffic control systems always end with the assessment of correctness of each process. It should be pointed out that these processes are compound and require high skills level for persons involved in it. Because of this, an environment for an expert system (ExSys Corvid) can be used to automation of these processes. Authors used ExSys Corvid environment to build the expert system for verification and validation of Level Crossing Protection System (LCPS). Research conducted by authors confirmed high usefulness of this technology and showed the need for the usage of it in other railway traffic control systems.

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45

Mandhare, Pallavi A., Vilas Kharat, and C. Y. Patil. "Intelligent Road Traffic Control System for Traffic Congestion A Perspective." International Journal of Computer Sciences and Engineering 6, no. 7 (July 31, 2018): 908–15. http://dx.doi.org/10.26438/ijcse/v6i7.908915.

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46

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

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

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Kara, T., and M. Cengiz Savas. "Design and Simulation of a Decentralized Railway Traffic Control System." Engineering, Technology & Applied Science Research 6, no. 2 (April 17, 2016): 945–51. http://dx.doi.org/10.48084/etasr.631.

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With the increasing use of railway transportation, various methods have been developed for the control and management of train traffic. Train traffic control systems that are currently in use are overwhelmingly centralized systems. In this study, the development of the general structure of railway traffic control techniques is examined, centralized and decentralized control systems are investigated, and an alternative train traffic control system, the Decentralized Train Traffic Management System (DTMS), is suggested. Simulation results on the possible application of the proposed method to a railway line in South-East Turkey are employed to evaluate the performance of the developed system.

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McLin, John L., and William T. Scherer. "Development and Evaluation of a Control System for Regional Traffic Management." Advances in Civil Engineering 2011 (2011): 1–11. http://dx.doi.org/10.1155/2011/724897.

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Traffic congestion is a worsening problem in metropolitan areas which will require integrated regional traffic control systems to improve traffic conditions. This paper presents a regional traffic control system which can detect incident conditions and provide integrated traffic management during nonrecurrent congestion events. The system combines advanced artificial intelligence techniques with a traffic performance model based on HCM equations. Preliminary evaluation of the control system using traffic microsimulation demonstrates that it has the potential to improve system conditions during traffic incidents. In addition, several enhancements were identified which will make the system more robust in a real traffic control setting. An assessment of the control system elements indicates that there are no substantial technical barriers in implementing this system in a large traffic network.

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Rishitha, Ch, M. Bhavana, P. Sriya, and Dr Y. Sreenivasulu. "Arduino Based Congestion Control System for Ambulance." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 522–29. http://dx.doi.org/10.22214/ijraset.2022.43793.

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Abstract: Congestion problem is a fact which contributed large impact on the transport system in the country. because many problems especially when there are emergency cases at traffic light junctions which are always busy with so many vehicles. A congestion control system is designed in order to solve all these problems. This system was designed in such a way that it should be activated when it receives a signal from an ambulance based on radio frequency (RF) transmission and uses a microcontroller to change the sequence back to the normal sequence before the emergency mode is activated. This system will lessen what often happens at the traffic light intersections because other vehicles have to gather together for giving a special route to an emergency vehicle. As a result, this project is successful and the implementation of wireless communication i.e. the radio frequency (RF) transmission in the traffic light control system for emergency vehicles like an ambulance is made possible. The main aim of this project is to design a system that is capable to identify an emergency situation in an ambulance and automatically controls the traffic at the signal. In the future, this system can be improved by controlling real traffic congestion, in fact improving the present traffic light system technology. The existing traffic control system has a lot of limitations because of its fixed time method used. The traffic signal will not alter based on the real-time traffic on road near the junction of two or more roads. Due to this, the traffic congestion cannot be controlled efficiently and the utilization of roads cannot be done to its maximum limit.

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Dubey, Kajal. "Adaptive Traffic Control System: The Smart and Imperative Traffic Monitoring System for India." International Journal for Research in Applied Science and Engineering Technology 7, no. 12 (December 31, 2019): 210–18. http://dx.doi.org/10.22214/ijraset.2019.12035.

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