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conf paper1

Paper type: Essay
Pages: 11 (2596 words)
Categories: Society, Traffic Light, Transport
Downloads: 19
Views: 1

Density-Based Traffic Congestion Control Using Image ProcessingTabassum AraAssistant Professor Shazad Hai, Shifa Department of computer Science Shruthi S, Vijay Raj,8th Sem, BE HKBK College of Engineering, Bangalore HKBK College of Engineering, Bangalore Abstract – In the contemporary world, urban mobility is one of the unprecedented challenges to be tackled in the administration of a big city. As we consider the number of traffic problems in group urban development at present, such as the increase in the number of vehicles, the decrease in the speed of vehicles, traffic light delays, and pollution due to traffic, etc, this paper presents an Adaptive traffic strategy for urban development.

The Adaptive traffic control strategy has basic design characteristics, namely avoiding the accidents, reducing the time of the individuals, and protection of the urban environment. The target of this development strategy is to provide an “efficient, safe, convenient and clean” transportation service. It clearly includes the way of thinking the rule of maintaining the traffic light supported the density of vehicles in city- based transportation development.

Consequently, it effectively solves a variety of current traffic congestion problems in group urban development, and it provides validity with extensive applications.Keywords: Traffic congestion, Image Processing, Density of Vehicles, Traffic Signals. INTRODUCTIONDue to increase in population the use of the vehicle has also become extensive which leads to an increase in traffic congestion. This is because the current transportation infrastructure is too general and there is a need for change in the traffic control system. To overcome these problems, the IoT with image processing can be used. Internet of Things (IoT) is an area which allows communicating between the physical objects through internet connectivity. IoT simplifies our daily routines simply using embedded devices such as sensors, software etc. It helps us to connect the devices through a remote area over a networkconnectionImage Processing has become one of the vital areas in vehicle detection which helps in recognizing the type of vehicle and its density. Object recognition technology within the field of computer vision to seek out the articles within the image or video sequences Image process helps in recognizing the object although there are stalemated from human’s purpose of reading. The image can be scaled, rotated and translated using imageprocessing.Urban Road configuration is described in urban areas made up of some definite groups. Each group will have its own roadway system, highway systems and also lane systems that are convenient in traffic congestion control. This may vary from different metropolitan cities. However new Traffic problems are constantly arising. So here wepropose a density-based traffic control system using image processing which will count the number of vehicle- based on the image captured and thenwill adjust the green light based on the traffic priority. The main purpose of this system is to reduce the traffic jam among lanes by increasing the green light timer of the similar highest density vehicle lane.EXISTING SYSTEMAccording to the various papers published on Intelligent Traffic Congestion control, few of them have been discussed below.In this paper [1] the proposed system has a better capability of reflecting the heterogeneity of traffic flow, especially the heterogeneous traffic flow mixed by vehicles and non-motor vehicles. The social force models can be used for any boundary shape of the passable area.In the next paper [2] the author has proposed a system with Traffic flow models based on Eulerian LWR (Lighthell-Whitham-Richards) model have the benefit of using the physical phenomenon to predict the traffic with fewer data and lower computational cost. The paper uses adaptive probing of vehicles which improves prediction accuracy compared to non-adaptive probing In this paper [3] Traffic signals are operated according to this density of traffic. Some of the present systems also operate in line with traffic density, however, the novelty lies in the way the traffic quantity is calculated. Differential priorities can be appointed to vehicles ” (a) Ambulances, Fire Brigades and very important person vehicles will be given unrestricted passage no matter volume of traffic, (b) Scooters and cars can be given higher priorities throughout college and workplace rush hours, (c) Heavy vehicle will be given higher priority at night time.In this paper [4] It uses the microcontroller, Infrared sensor, counter flag, display semiconductor diode. Infrared sensors are used to realize its close objects by victimization actinic ray. It also capable of measuring the heat being emitted by AN object and detective work motion of auto and its direction of movement. IR sensor sight the variety of vehicles on all sides then that count is kept in counter flag variable, which is sent back to the microcontroller to initialize the stoplight. The microcontroller is programmed to perform the entire task of control supported info that it’s got information from the Infrared device. The Infrared sensor can sight the traffic on the road and indicate that traffic as serious traffic or traditional traffic. Traffic can be cleared with efficiency victimization this technique. The author uses [5] ZigBee Module CC2500, GSM Module SIM 300, RFIDReader”125kHz”TTL, Micro-controller (PIC16F877A) for automatic signal control and purloined vehicle detection it can additionally clear the emergency vehicle mechanically exploitation ZigBee transmitter put in in vehicles like the automobile. In the last paper [6] the author uses the road boundary of every input image detected by a semantic FTC level set algorithmic rule. The scene model is roughly composed of “left wall,” “right wall,” “back wall,” “road plane” and “foreground polygons.” These are enough for giving users convincing walk-through expertise. It basically simulates the traffic congestion from road imagesequences.(B)(C)(D)Fig1: A) Sketch of the intersection with island work zone B) Probing vehicles in pair C) RFID D) IR Sensorb.) Disadvantages in Existing systemIf the information from the stochastic model [1] is uncertain than the whole model will be atfault.Only one type of relationship between an intersection and a work zone, namely, the island workzone [2].So far the possibility of taking a turn at the crossing [3] has not been carefully thought about.Usage of Sensors [4] isexpensive.PROPOSED SYSTEMThe use of Image Processing and Embedded technology has tried to be terribly helpful in Traffic Light Controller (TLC), that will minimize the waiting time of auto and conjointly manage traffic load. In this project we exploit the emergence of latest technology known as an Intelligent light controller, this makes the use of Segmentation of images in conjunction with embedded technology. Where traffic light is showing intelligence set supported the whole traffic on all adjacent roads. Thus optimization of traffic [1] light shift will increase road. Capacity, [4] traffic flow and can forestall traffic congestions.The traffic control system is separated in following four stageImage acquisition: The cameras are placed on the traffic signals to capture the image of vehicles on particular lane. Capturing the vehicle density using a camera and further transferred for image enhancementRGB to gray conversion: it involves the conversion of the color image into a gray image. Based on the RGB value in the image, it calculates the value of the gray image and obtains the gray image at an identicaltimeImage enhancement: the acquired image of the vehicle is enhanced using brightness enhancementtechniquesImage matching using edge detection: matching the acquired image to the database image using edge detection techniquesa.) System Overview4391025237490Fig.2: Process to control the timing of green signal using density of vehiclesMicrocontroller ARDUINO : The Arduino is ATmega328 based micro-controller. It has 14 agenda input/output pins (of which 6 can be acclimated as PWM outputs), 6 analog inputs, a 16 Megahertz bowl resonator, a USB connection, an ability jack, an ICSP header, and a displace button. It contains aggregate bare to abutment the microcontroller; artlessly affix it to a computer with a USB cable or ability it with a AC-to-DC adapter or array to get started. The Uno differs from all above-mentioned boards in that it does not use the FTDI USB-to-serial disciplinarian chip. Instead, it appearance the Atmega16U2 programmed as a USB-to-serial converter. The Arduino Uno has an amount of accessories for communicating with a computer, additional Arduino, or added microcontrollers.USB to UART Converter : This board appearance innovation that set it afar from added USB to Consecutive Converter boards. Innovations features like 256 byte accept receiver and 128-byte address transmitter advance new absorber cutting technology to acquiesce for top abstracts throughput. The TX and RX pins from the USB-SER can be affiliated anon to RX and TX pins of your adopted microcontroller or consecutive appliance for a simple consecutive cable backup connection.The USB-SER board is absolute for embedded systems that crave a consecutive affiliation to a computer. The board attaches anon to the USB bus via a accepted blazon mini B receptacle connector. It shows up on any Windows computer as a accepted consecutive COM port. Any applications that allocution to this COM port is automatically changed to USB and aback to UART to your respective boardLEDs :The light emitting diode merely, we grasp as a diode. When the diode is forward biased, then the electrons & holes are moving quick across the junction and they are combining perpetually, removing one or the other out. Soon once the electrons are moving from the n-type to the p-type element, it combines with the holes, then it vanishes. Hence it makes the atom a lot of stable and it offers the little burst of energy within the small packet or photon The principle of the Light emitting diode is predicted on the quantum theory. The quantum theory approach says that if the electron comes down from the high energy level to the lower energy level then, it will result in emitting energy from the photon. The photon energy is based on the activity gap amid these two activity levels. If the PN-junction diode is in the forward biased, then the current flows through the respective diodeThe flow of current within the semiconductors is caused by the both flow of holes within the other way of current and flow of electrons in the direction of the present. There can be recombination thanks to the flow of those charge carriers in opposite directions. It indicates that the electrons in the conduction band jump all the way down to the valence band. When the electrons jump from one band to another the electrons will emit the EMF energy within the form of photons and also the photon energy is adequate to the forbidden energy gap. (B) (C) Fig.3: A) Microcontroller ARDUINO B) USB to UART Converter C) LEDsc.) Software SpecificationEmbedded C : Embedded c is in fact the addendum of c language. It consists of c language sets that can be used for various functions. It was extending by the standard c committee in 2008 for solving the problems given by c language. It uses the syntax and customary c linguistics. This language has so several options as compared to c language like it used the fixed arithmetic, spaces between address and hardware, addressing. As we see around ourselves, we have such a big amount of embedded systems like washer, digital camera and mobile phones of these the samples of embedded system, in all this stuff embedded c language is employed. So several additional characteristics have intercalary in embedded c like operation or mapping register, number of memory space and illustration of fastened purpose.MATLAB : MATLAB is a performance based language for computing the data technically. It involves computation, computer visualization, and programming in an easy-to-use ambiance area where problems and solutions are bidding in accustomed algebraic notation. The uses of MATLAB include:Computation in MathsDeveloping Algorithms exploration, Visualization and graphicsGraphical User Interface building in app developmentMATLAB is associate interactive system whose basic information part is an array that will not need orientating. This allows us to unravel several technical issues, especially with matrix and vector formulations, during a fraction of the time. It might want write a program in a other language like C or Fortran.MATLAB stands for matrix laboratory. MATLAB was written to provide quick access to matrix code developed by the LINPACK and EISPACK projects, which together represent the progressive in code for computation of matrix.ARDUINO SUITE : Arduino suite is an open-source electronics software based on easy-to-use hardware and software. Arduino boards are able to apprehend inputs – ablaze on a sensor, and turn it into an output – activating a motor, switching on an LED, publishing something online. You can tell your board what to do by sending a set of instructions to the microcontroller on the board. To do so you use the HYPERLINK ” programming language and the Arduino Software (IDE), based on process.d.) Flow DiagramFig.4: Flow DiagramAs shown in above fig the system works as followsWe have a reference image and the image to be captured is continuously captured using camera that is installed at the junction.The images are preprocessed in 2 stepsimages are scaled to 300×300 pixelsthen above scaled images are converted from RGB to grayWe will convert the grayscale image to binary image to remove excess noise.We will enhance the image and set the propertiesLabel the regions using x and y co ordinatesDetection of vehiclesCount the vehicleBased on vehicle count increase or decrease the timing of green signalThe algorithm used is RGB to gray which as shown below For Each Pixel in Image { Red = Pixel.Red Green = Pixel.Green Blue = Pixel.Blue Gray = (Red + Green + Blue) / 3 Pixel.Red = Gray Pixel.Green = Gray Pixel.Blue = Gray}Based on pixel values we can convert the red, green and blue colored values to grayscale.e.) Advantages of the Proposed systemThis system will scale back the waiting time as traffic signals light can modification accordingly to density to reduce trafficjam. Easy to implement and reduced cost compared to the use of sensors. It helps the ambulance to move through the traffic easily.CONCLUSIONThe proposed system will help in reducing the traffic jam by calculating the density of vehicles. It will increase the time of the green light where the vehicle density will be high. It will also let the ambulance to move through the high traffic jam. This framework will give the vehicle a chance to go through the high automobile overload utilizing most effortless way i.e; utilizing image processing. The road with high vehicle density will be cleared first then the second populated one. It will clear the traffic and save the valuable time of theindividuals.ACKNOWLEDGEMENTI want to express gratitude towards Professor and Head Dr. Loganathan. R., Department of CSE, HKBKCE, Bangalore for his constant encouragement. I would specially like to thank my guide, Assistant Prof. Tabassum Ara, Department of Computer Science and Engineering for her interminable help for this work.REFERENCESLakshmi Chaitanya, P. Sreelatha, M. tech A Smart Traffic Congestion Control System IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1524-9050© 2018 IEEEAnuran Chattaraj, Saumya Bansal, Anirudhha Chandra Intelligent Traffic Control System using RFID IEEE Potentials (Volume: 28, Issue: 3, May-June 2009)Da Yang, Xiaoxia Zhou, Gang Su, and Sijing Liu “Model and Simulation of the Heterogeneous Traffic Flow of the Urban Signalized Intersection With an Island Work Zone” IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1524-9050 © 2018 IEEEKang-Ching Chu, Romesh Saigal, and Kazuhiro Saitou, Senior Member, “Real-Time Traffic Prediction and Probing Strategy for Lagrangian Traffic Data” IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1524-9050 © 2018 IEEERajeshwari Sundar, Santhosh Hebbar, and Varaprasad Golla “Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection” IEEE SENSORS JOURNAL, VOL. 15, NO. 2, FEBRUARY 2015Yaochen Li, Student Member, IEEE, Yuehu Liu, Member, IEEE, Yuanqi Su, Member, IEEE, Gang Hua, Senior Member, IEEE, and Nanning Zheng, Fellow, IEEE Three- Dimensional Traffic Scenes Simulation from Road Image Sequences IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1524-9050 © 2016 IEEE.

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