International Journal of Computer Engineering and Applications, Volume XII, Special Issue, March 18, ISSN

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1 AUTONOMOUS TRAFFIC SIGNAL MANAGEMENT 1 Department of Computer Engineering 2 Department of Computer Engineering, MITCOE, SPPU Pune, India ABSTRACT: Vehicular traffic congestion has been a major problem in India. The current traffic control system (TCS) in the metro cities of India is inefficient due to randomness in the traffic density pattern throughout the day. The traffic signal timers have a fixed time period to switch traffic between different directions. Due to this, the vehicles have to wait for a long time span even if the traffic density is very less. In this paper we have proposed a method which makes use of RFID technology to calculate traffic density and our algorithm M-SPY ACTS focuses on switching the traffic lights according to vehicle density on road, thereby aiming at reducing the traffic congestion on roads dynamically which will help lower the number of accidents. In turn it will provide safe transit to people and reduce fuel consumption and waiting time. It will also provide significant data which will help in future road planning and analysis. In further stages multiple traffic lights can be synchronized with each other with an aim of even less traffic congestion and free flow of traffic. Keywords: RFID Reader, RFID Tag, Raspberry Pi 3 microcomputer. [1] INTRODUCTION A. RFID Technology In this, each individual vehicle is equipped with unique radio frequency identification (RFID) tag to track the vehicle and we use RFID reader to read the RFID tags attached to the vehicle's windshield [1]. It counts the number of vehicles using IR sensor that passes in a particular 1

2 AUTONOMOUS TRAFFIC SIGNAL MANAGEMENT direction of the road during a specified duration and set time dynamically for the traffic signal. [1][3] B. M-SPY Algorithm The M-SPY ACTS is designed to take traffic vehicle count from RFID and calculates traffic density according to which it decides signal timing length for each light at cross junction road. It ensures that no two traffic signals turn green at the same time in any scenario and neither there is any ambiguity in processing parameters that could lead to any possible accident. It can also provide quality of service to emergency vehicles like ambulance, fire brigade or police and also special vehicles like MLA, minister vehicles. When such vehicles with unique RFID tag is read by the RFID reader at the traffic junction then green light will be turned ON for a specific duration. C. Features of the project Built on Vehicle Actuated Platform Self Calibrating High Scalability Possible to network on different media, including 3G Availability of Artificial Expertise D. Contribution Average travel speed increase Reduction in average delay Substantial reduction in annual fuel consumption Increase in overall time saving Increase in overall money saving per person E. Problem Statements To find an adaptive technique to manage vehicular traffic at a single traffic signal junction which will reduce the waiting time of vehicles in the lane, Also use existing technology to monitor the traffic in lane and for this we propose a signal control method to optimize the signal split at a critical intersection using the data of vehicular count obtained from the RFID system. Signal split is the most important parameter at critical intersections where traffic congestion often occurs, and the real-time adjustment of the split is expected to offer a high efficiency in simple control logic [2] ARCHITECTURE 2

3 Architecture of proposed system: The system consists of Raspberry pi 3 microcomputer to receive the input of traffic count by rfid reader. The rpi 3 can control the traffic signal lights based upon the count and the proposed algorithm. [2] The system is based on the RFID tags attached to the vehicles that are tracked when the vehicles are standing on the traffic signal, during the red light [1]. The vehicle count is then generated for each lane that can be used by the algorithm to manage the traffic signal/ green light time depending upon the traffic density dynamically. This system is extremely efficient compared to the other techniques available to reduce waiting time as well as the overall traffic congestion in the city. There is a lot of future scope for this system as it can be uniquely used to identify all possible traffic violation that can occur over a signal, due to uniqueness in RFID the information about the violator can be easily obtained and penalties can be imposed autonomously by the system. The system can ensure complete traffic discipline over a signal junction. The system consists of following components: 1. RFID tag 2. RFID reader 3. RASPBERRY PI 3 microcomputer 4. The other design components 5. The underlined algorithm [3] ALGORITHM 1) Start 2) Consider the signal junction and divide it into four parts with respect to the flow of direction. The 4 directions with lane numbers are: 2.1) east (1) 2.2) west (1) 2.3) north (1) 2.4) south (1) 3) Divide the signal cycles of all signals into 4 phases 3.1) phase1 - east signal and west signal will be green either simultaneously or one after another according to congestion 3.2) phase2 - all read. Calculating the queue length in lane 3.3) phase3 north signal and south signal will be green either simultaneously or one after another according to congestion 3.4) phase4 all read. Calculating the queue length in lane 4) Calculate queue length by using image processing. Each signal runs for 60 sec with 40 sec reserved for red light and 20 sec reserved for green light. While (true) 3

4 AUTONOMOUS TRAFFIC SIGNAL MANAGEMENT else Add lane 1, 2. Add lane 3, 4. If ((1+2)> (3+4)) // we enter first phase1. a) Check which lane between 1 and 2 has more number of vehicles. b) By how much percent it is more. c) Increase the green light timing of that lane with the same percent as calculated in the first step. Reduce the red light time with the same percent. d) Start the green time of latter lane with default time after the termination of signal time of the previous lane. e) All red phase-calculate vehicle queue length in all lanes. a) Check which lane between 3 and 4 has more number of vehicles. b) By how much percent it is more. c) Increase the green light timing of that lane with the same percent as calculated in the first step. Reduce the red light time with the same percent. d) Start the green time of latter lane with default time after the termination of sign time of the previous lane. e) All red phase-calculate vehicle queue length in all lanes. 5) Reset to default cycles (60 sec with 40 sec for red light and 20 sec for green light) on any kind of failure. 6) END. [4] IMPLEMENTATION The Raspberry pi is used to manipulate the signals. Vehicles are equipped with RFID tags that will be read by the RFID reader at the signal junction. The algorithm will count the number of Vehicles that will approach the junction from the different RFID tag ids that it receives from different vehicles. LED lights have been interfaced with each road to represent the signal. The reader will read all the different RFID tags that are in its proximity and send them to the computer or server via raspberry pi, where the number of vehicles at the signal junction will be calculated. Depending on the maximum count of the vehicle the signal of the denser lane turns green to allow the traffic in that lane to pass. This algorithm will provides default time as well as the time cycle is divided in phases so that no signal has starvation of vehicles. It considers two opposite lanes at a time that is north-south and east-west. If one of the pairs of lanes is having one or more prospects to discharge its traffic incessantly then eventually after some cycles it is bound to have less denser vehicular traffic than the other pair and hence automatically the other pair of lane receives a chance to deploy its vehicular traffic. In any case of faulty functioning of the algorithm the signal time cycles can reverted to its default timings 4

5 Figure. 1: Representation of Project [6] CONCLUSION In this paper we briefly discusses the vehicular traffic problem at signals in metro cities. It proposes to use RFID technology. The proposed system works effectively with higher accuracy in managing the traffic at junctions compared to the existing infrastructure. An algorithm (M - SPY ACTS) which dynamically calculates the waiting time of signal is designed. This system can also be developed to provide emergency services to ambulance, police vehicles, fire brigades and also stolen vehicles. REFERENCES [1] AN INTELLIGENT TRAFFIC CONTROL SYSTEM USING RFID - Anuran Chattaraj, Saumya Bansal, and Anirudhha Chandra.(IEEE). [2] INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECH NOLOGY An Adaptive Traffic Control System Using Raspberry PI S.Lokesh, T.Prahlad Reddy Department of ECE, Sir Vishveshwariah Institute of Science and Technology,Madnapalli ,India. [3] An image processing system to measure vehicular queues and an adaptive traffic signal control by using the information of the queues - Y. Iwasaki IEEE Conference Publications. DOI: /ITSC