INTELLIGENT TRAFFIC LIGHT SYSTEM FOR REDUCED FUEL CONSUMPTION. Kanagavalli.G 1, Dr.M.Sangeetha 2 *

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1 Volume 116 No , ISSN: (printed version); ISSN: (on-line version) url: ijpam.eu INTELLIGENT TRAFFIC LIGHT SYSTEM FOR REDUCED FUEL CONSUMPTION Kanagavalli.G 1, Dr.M.Sangeetha 2 * 1 Assistant Professor/ECE, BIST, BIHER, Bharath University, 2* Professor/ECE, BIST, BIHER, Bharath University, 1 kanags89@gmail.com, 2* sangeetha.ece@bharathuniv.ac.in Abstract: Wireless smart embeddedsystem has its foot in Intelligent Traffic system. The consumption of fossil fuel is increasing day by day and measures are taken to reduce the fuel consumption by means of Intelligent Traffic System. Smart embedded system enabled with wireless facility serves to be the key for this problem. The vehicles consume more fossil fuel when standing in idle in a busy traffic signal. This paper proposes methodology for reducing the waiting time of the vehicles in the busy traffic signal thereby to reduce the fuel consumption of the vehicle. The simulation result shows the improvement in waiting time of a busy traffic signal. Keywords: Intelligent Transportation System; Radio Frequency Identification (RFID); Smart vehicles; Fuel consumption 1. Introduction Intelligent transport systems (ITS) are advanced applications which, without embodying intelligence as such, aim to provide innovative services relating to different modes of transport and traffic management and enable various users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks. Intelligent Transportation System consists of many smart sensors such as accelerometer, camera sensors, infrared devices and smart card system installed in the traffic signals and toll booths. These sensors serve the purpose of monitoring the traffic, traffic signal conditions and vehicle s details passing the corresponding terminal. These sensors serve as the input unit to the smart intelligent system. The data from the sensors travel to the Data Processing Unit by means of wired or wireless means and creates an ITS. In general, any of the ITS applications uses traffic management centre where data is collected and analyzed with the other operational and control concepts to manage the complex transportation problems This paper discusses the fuzzy rule based decision making for reducing the waiting time of the vehicle in a busy traffic terminal during peak and non peak hours. 2. Prelims A. Intelligent Transportation System: Intelligent Transportation system is an established route to resolve, or at least minimize traffic problems. ITS encompass all modes of transportation such as air, sea, road and rail and intersects various components of each vehicles, infrastructure, communication and operational systems. Various countries have developed strategies and techniques, based on their geographic, cultural, socioeconomic and environmental background, to integrate the various components into an interrelated system. Intelligent transportation system consists of intelligence automatic toll collection in toll gates, and traffic allocation during busy time in tight traffic conditions. The ITS mainly constitutes sensor devices for knowing the status of traffic, sensor like camera, CCTV and RFID are used for knowing the type of vehicles. B. RFID-Radio Frequency Identification Radio frequency identification is the next wave in the evolution of computing. Essentially, it's a technology that connects objects to Internet, so they can be tracked, and companies can share data about them. RFID systems Figure 1. RFID reader and tag ACTIVE RFID system Active RFID Systems Active tags are used on large assets, such as cargo containers, rail cars and large 491

2 reusable containers, which need to be tracked over long distances (in a distribution yard, for example). They usually operate at 455 MHz, 2.45 GHz, or 5.8 Ghz, and they typically have a read range of 60 feet to 300 feet (20 meters to 100 meters). Broadly speaking, there are two types of active tags: transponders and beacons. Active transponders are woken up when they receive a signal from a reader. These are used in toll payment collection, checkpoint control and other systems. When a car with an active transponder approaches a tollbooth, a reader at the booth sends out a signal that wakes up the transponder on the car windshield. The transponder then broadcasts its unique ID to the reader. Transponders conserve battery life by having the tag broadcast its signal only when it is within range of a reader. Passive RFID system Passive RFID tags have no power source and no transmitter. They are cheaper than active tags cents to 40 cents) and require no maintenance, which is why retailers and manufacturers are looking to use passive tags in their supply chains. They have a much shorter read range than active tags (a few inches to 30 feet). passive RFID transponder consists of a microchip attached to an antenna. The transponder can be packaged in many different ways. It can be mounted on a substrate to create a tag, or sandwiched between an adhesive layer and a paper label to create a printable RFID label, or smart label. Transponders can also be embedded in a plastic card, a key fob, the walls of a plastic container, and special packaging to resist heat, cold or harsh cleaning chemicals. The form factor used depends on the application, but packaging the transponder adds significantly to the cost. Tags come in many form factors Passive tags can operate at low frequency, high frequency and ultra-high frequency. Low-frequency systems generally operate at 124 khz, 125 khz or 135 khz. High-frequency systems use MHz, and ultrahigh frequency systems use a band anywhere from 860 MHz to 960 MHz Some systems also use 2.45 GHz and other areas of the radio spectrum. Semi-Active RFID system A type of RFID (Radio Frequency Identification) tag containing a battery that operates the circuitry of the microchip, but must draw power from the magnetic field created by the reader in order to communicate with the reader via radio waves. RFID is a technology in which the tag, or transponder, is attached to a variety of goods and equipment in order to provide rapid identification, inventory management, and/or numerous security features. Semi-active RFID tags are also known as semi-passive tags and are often incorporated with digitally printed applications such as smart labels and security card. ARM 11 ARM 11 has the ARMv6 architecture which is enabled with multiprocessor support and a new cache. Cache is physically addressed, solving many cache related aliasing problem and reducing context switch overhead. ARM 11 operates in the mode Bi-endian that can operate in either little-endian or big-endian. The ARM 11 used in this paper is Raspberry pi uses Linux based operating systems, which communicates with the traffic server through cloud service. 3. Proposed Model The vehicles stop and go driving at signals will consume more fuel and emit more carbon-di-oxide than constant speed driving. In the proposed system, the traffic signal is allocated based on the fuzzy logic rules. The traffic signal allocation is done in two ways; one is for peak hours and the other for non-peak hours. During peak hours, the density of the vehicles, waiting near signals is more. The traffic allocation should be done, to reduce the waiting time of the vehicles during peak hours. The side with more traffic density can be given priority, by decreasing the red time of the signal. The traffic congestion during peak hours can be reduced by this arrangement. During idling time, the fuel consumption of the vehicles is also increased. Generally, it is assumed that the heavy vehicles will consume more fuel. The proposed model, tries to reduce the fuel consumption, by giving priority to the heavy vehicles during non-peak hours. The vehicles are fixed with RFID and the receiver is near the traffic signal. The system is connected with the traffic server, to get the details about the vehicles. The information from the traffic server will be given as the input to the DPU. Based on the rules framed, the traffic signal is allocated for vehicles. The proposed model consists of radio frequency communication between the vehicles and the traffic signal. The information from the RFID is sent to the signal by wireless communication. The information obtained is processed by the Data Processing Unit, which is located near signal. The DPU is connected to the traffic server by wireless means. The details about the vehicles are obtained from the traffic server and it is sent back to the DPU for traffic signal allocation. 492

3 Figure 2. Architecture of the proposed system Active RFID system is powered using the battery in the vehicle, which communicates with the RFID receiver to the DATA processing unit. The RFID system installed in the vehicle transmitters the ID of the vehicles to the RFID reader installed in the traffic signal. The RFID reader in the traffic signal is connected to the data processing unit which collects the type of vehicle and its fuel consumption from the traffic server located in the Traffic Management Server. The data processing unit computes the red time and green time for the busy traffic signal and sends the control signal to the traffic light box. Meanwhile it starts getting request from the next side of the traffic signal and processes it for the next cycle. 4. Results and Discussion Figure 3. Time (versus) Number of vehicles in Traffic signal Fig - 3 shows the traffic density of vehicle in the busy traffic signal in Chennai. The Traffic condition in the traffic signal is monitored from morning 7 hours to 23 hours. The traffic density is more during 8-10 hours and hours and these are considered to be busy hours and traffic density is given importance at this time. Figure 4. Red time vs Observing time Fig - 4 shows the improved graph in which the waiting time of the vehicle under busy condition is minimized hence the fuel consumption of the vehicle is reduced. 5. Conclusion Its serves to be the key for creating a modern transportation system which minimizes the fuel consumption. Simulation results support our proposed work by reducing the waiting time under busy times. ITS in all busy signal throughout year can save millions and millions of fuel. References [1] Vijayaragavan S.P., Karthik B., Kiran T.V.U., Sundar Raj M., Robotic surveillance for patient care in hospitals, Middle - East Journal of Scientific Research, v-16, i-12, pp , [2] Vijayaragavan S.P., Karthik B., Kiran Kumar T.V.U., Sundar Raj M., Analysis of chaotic DC-DC converter using wavelet transform, Middle - East Journal of Scientific Research, v-16, i-12, pp , [3] Sundararajan M., Optical instrument for correlative analysis of human ECG and breathing signal, International Journal of Biomedical Engineering and Technology, v-6, i-4, pp , [4] Kiran Kumar T.V.U., Karthik B., Improving network life time using static cluster routing for wireless sensor networks, Indian Journal of Science and Technology, v-6, i-suppl5, pp , [5] Karthik B., Kumar T.K., Dorairangaswamy M.A., Logshanmugam E., Removal of high density salt and pepper noise through modified cascaded filter, Middle - East Journal of Scientific Research, v-20, i-10, pp , [6] Karthik B., Kiran Kumar T.V.U., EMI developed test methodologies for short duration noises, Indian Journal of Science and Technology, v-6, i-suppl5, pp , [7] 7Vijayaragavan S.P., Karthik B., Kiran Kumar T.V.U., Privacy conscious screening framework for 493

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