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LITERATURE REVIEW ON TRAFFIC SIGNAL CONTROL SYSTEM BASED ON WIRELESS TECHNOLOGY 1
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3 A.Rajani P.Rajesh Assistant Professor Associate professor Department of ECE Department of ECE Annamacharya Institute of Technology and Sciences,Tirupati,India-517520
G.Krishnaiah M.Tech(DSCE), Student
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sreekrishna.g@gmail.com rajanirevanth446@gmail.com 3 rajeshpatur.aits@gmail.com
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Abstract – This paper presents a literature review on different types of techniques used in the traffic signal control system. We known to the fact one of the main issues to be addressed by the today’s traffic management schemes is, traffic congestion on city road neetworks. Traffic congestion on city roads many times leads to delay of our works. All these heavy traffic in these day’s is due to the known fact that, number of vehicles are increasing exponentially, and the limited technology using for traffic control on roads. Traffic police at cross roads and automatic traffic signal scheme are the most used traffic control schemes in India. Contrast to the regular schemes, intelligent traffic management schemes based on Image processing and Wireless sensor networks are using to control traffic, from last five years. But besides their advantagesthese schemes has some limitations. It is found that using wireless system along with embedded system has benefits over the existing techniques. Key words: Automatic traffic signals, Intelligent traffic management schemes, Image processing, Wireless sensor networks, Wireless communication technology.
I. INTRODUCTION The continuous increase in the congestion level, especially at rush hours, on public roads , is a critical problem in many countries and is becoming a major concern to transportation specialists and decision makers. The existing methods for traffic management, surveillance and control are not adequately efficient in terms of the performance, cost, and the effort needed for maintenance and support. Many techniques has been used including, ground level sensors like video image processing, microwave radar, laser radar, passive infrared, ultrasonic, and passive acoustic array. But, these systems have a high equipment cost and their accuracy is depends on environment conditions [1].
At another widely-used technique in conventional traffic surveillance systems is based on intrusive and non-intrusive sensors with inductive loop detectors, in addition to video cameras for the efficient management of public roads [2][3]. Among them, intrusive sensors may cause disruption of traffic upon installation and repair, and may result in a high installation and maintenance cost. non-intrusive sensors, On the other hand, tend to be large size, power hungry, and affected by the road and weather conditions; thus resulting in degraded efficiency in controlling the traffic flow. Main problem occurs, when this traffic congestion costs life of someone, if in case any emergency vehicles like ambulance strucks in traffic. This paper gives a brief review of few techniques that has been implemented in one or more than one country around the world. In this paper traditional traffic management schemes has been discussed, below sub-section explains the traditional methods used in traffic control system. 1.1 Traditional Traffic Control Scystem We have different traditional traffic control schemes, in our world, used around the world. A traffic police standing at junction and later automatic traffic control signals are among them.Each of which are explained below. A. Traffic Police standing at junction roads A traffic police standing at junctions, or at cross roads, is the simplest and the oldest method used for the traffic management. It includes a human in the traffic ssytem. A trffic officer is placed on each and every cross sections of roads, and he manually controls the traffic. A police officer stands at middle of the road and monitoring the flow of traffic is shown in fig.1. The police officer gives signals to the vehicle driver whether to drive or start. And he always monitors the every road, and decides which lane has to give first priority. Based on his own
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INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ENGINEERING RESEARCH, ICDER - 2014
knowledge on his own takes the decisions, that which lane has to allow and which one to stop.
system is it cannot identify the amount of traffic in one particular line, so there is a chance of traffic jam.
Fig.2. Automatic traffic signals Fig.1. A Traffic poile officer standing in middle of the road and controling the traffic. This method is the most efficient among all other ssytem, if traffic police officer monitors traffic without error. As it includes a human as part of the system, the efficiency depends on, that particular officer. So, this might not be good for heavy traffic conditions and all the day, as we know humans always make mistakes. B. Automatic Traffic signals The drawback of the above system will be removed with this automatic traffic signals system. As like we seen every day, the automatic traffic signal system includes simple 3 color traffic signals. Normally 120 seconds of green light is onfor each lane. A yellow light will be flashes, before the blue light, for 20 seconds, sigling the vehicle owners to strat their vehiles and be ready to go. When the green light is on in one lane then all other lanes will display a redlight, The automatic traffic signalling system is shown in the fig.2. Where red signal indicates stop, yellow light signal indicates ready to go, and green light signal indicates go. The major problem with this
II. RELATED WORK 2.1 Existing Traffic control schemes A. Controling traffic lights by Image Processing Scheme In this scheme the number of vehicles are detected by the system through images rather using electronic sensors. And along side the traffic lights, cameras will be fixed, these cameras captures the images of vehicles. It shows that it can avoid the time being wasted by green light on an empty road, and so decreases traffic congestion. Image processing based on Intelligent traffic controller, vikramaditya dangi, ss. Rathode and Amol parab[4], a camera is fixed on tall poles to monitor the traffic. Images are extracted from cameras will be analysed to detect number of vehicles on the road, on each lane, And depend on the signal cycle time is allotted to each lane. For this traffic control signaling system using image processing requires matlab to perform the opertaion on the images captured by the cameras
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Fig.3. Block diagram of traffic control using image processing.
fixed on the tall poles. Image acquisition, edge detection and Image enhancement are the major steps in this scheme. The procedure of image processing scheme is can be clearly understand with the fig.3. Following 4 steps are the main blocks involved in the process of traffic control: 1. Image acquisition 2. RGB to gray conversion 3. Image enhancement 4. Edge detection ( Image matching)
Image acquisition, primarily, is done with the help of web camera. Initially image of the road is captured when there is no traffic on the road, and that empty road image is saved as reference image in the specified program. On the reference image RGB to gray conversion will be done. Then the images of road, while traffic, is captured. On the captured images, image acquisition is performed and rgb to gray conversion as well.Then
after the edge detaction method the reference image and original (traffic on road), are mtched. Based on the percent of matching the time duration of the green light will be allocated. Green light is on for 90 seconds, if the matching is between 0 to 10% . Green light is on for 60 seconds, if the matching is between 10 to 50%. Green light is on for 30 second, if the matching is between 50 to 70%. Green light is on for 20 seconds, if the matching is between 70 to 90%. And Red light is on for 60 seconds, if matching is between 90 to 100%.
B. Wireless Sensor Networks Many studies suggested the use of WSN[5] technology for traffic control [6, 7, 8, 9]. In [7], a dynamic vehicle detection method and a signal control algorithm to control the state of the signal light in a road intersection using the WSN technology was proposed. In [9], energyefficient protocols that can be used to improve traffic safety using WSN were proposed and used to implement an intelligent traffic management system. In [10], Inter-vehicle
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communication scheme between neighbouring vehicles and in the absence of a central base station (BS) was proposed. In this paper, an intelligent and novel traffic light control system based on WSN is presented. The system has the potential to revolutionize traffic surveillance and control technology because of its low cost and potential for large scale deployment. The proposed system consists of two parts: WSN and a control box (e.g. base-station) running control algorithms. The WSN, which consists of a group of traffic sensor nodes (TSNs), is designed to provide the traffic communication infrastructure and to facilitate easy and large deployment of traffic systems.
used to model the traffic flow between these multiple intersections. In the mesh topology, the intersections that are at the boundary are called edge intersections while the remaining intersections are called receiving and forwarding intersections. The average speeds for all intersections are assumed to be constant. All queues' lengths for all active directions are initialized to zero. The distances (horizontal or vertical) between any pair of the intersections are assumed fixed and equal to a predefined base distance (d).
In this section, we present the system model including some definitions and assumptions. We assume a single intersection at urban areas with each side having two legs. A configuration example for the system is given in Fig. 4 for an urban intersection. Vehicles arrive to the traffic light intersection (TLI) according to certain random distribution and depart after waiting for some time, which also follows a certain random distribution. For simplicity, and without loss of generality, we assume that each side of the TLI is modeled as M/M/1 queue. Fig.5. The in-house built traffic sensor node The vehicle detection system requires four components: a sensor to sense the signals generated by vehicles, a processor to process the sensed data, a communication unit to transfer the processed data to the BS for further processing, and an energy source. We adopt a simple time division multiple accesses (TDMA) scheme at the MAC layer since it is more power efficient as it allows the nodes in the network to enter inactive states until their allocated time slots. The scheme embodies a simple scheduling algorithm that minimizes the time needed for collecting data from all nodes back at the BS. The algorithm assigns a group of non-conflicting nodes to transmit in each time slot, in such a way that the data packets generated at each node reaches the BS by the end of the scheduling frame.
Fig. 4. Single intersection configuration example of WSN
To streamline our presentation, we present some useful notations and definitions that will be used throughout the paper presented in the following bulletins:
For urban areas with multiple intersections, we assume a mesh network of intersections with rectilinear topology. An open queuing network is
Traffic Phase: defined as the group of directions that allow waiting vehicles to pass the intersection at the same time without any conflict.
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Traffic Phase Plan: defined as the sequence of traffic phases in time. The Traffic Cycle: defined as one complete series of a traffic phase plan executed in a round robin fashion. The Traffic Cycle Duration (T): is the time of one traffic cycle needed for the green and red time durations for each traffic signal.
The design of WSN that is used as communication infrastructure in the proposed traffic light controller. We have designed, built, and implemented a complete functional WSN and used it to validate our proposed algorithms. Fig. 5 shows the final product of the in-house developed TSN. The functional TSN was built using some available of the-shelf components (NB. commercial sensor nodes like MICA motes were not available). The entire TSN is encased in such a manner to be placed on pavement made on the testing roads. For the system components to be able to communicate (e.g., traffic control box and the BS), a traffic WSN communication and vehicle detection algorithms were devised. To be specific, two algorithms are developed, namely, the traffic system communication algorithm (TSCA) that is presented in this section and the traffic signals time manipulation algorithm (TSTMA), which is presented in the next section. These algorithms interact with each other and with other system components for the successful operation of the control system. The process starts from the traffic WSN (which includes the TSNs and the traffic BS), the TSCA, and the TSTMA, and ending by applying the efficient time setting on the traffic signals for traffic light durations. The TSCA is developed to find and control the communication routes between all. The power restrictions of sensor nodes are raised due to the their small physical size and lack of wires. Since the absence of wires results in lack of a constant power supply, not many power options exist. Power limitations greatly affect security, since encryption algorithms introdces a communication over head between the nodes. III. CONCLUSION In this paper different existing traffic control schemes(using Image Processing, using Wireless Sensor Netwotks) are dicussed.
The new traffic control system based on wireless communication have proposed . In the urban road traffic control system generally includes signal control machine, traffic lights, variable message signs(VMS) and othe detectors. The wireless traffic signal control system composed by master node and slave node. The master node is the center of system, it is a signal ccontrol machine and could provide control signal to slave nodes; the slave node is the end point devices of system, it recieves and executes instructions from master node and then returns a report. All of these devices communicated by wireless communication models. The performance of the proposed scheme for traffic control sheme has benefits over the all other existing schemes.
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Electrical Science and Engineering, Massachusetts Institute of Technology, June 2000.
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