Intelligent Traffic Light Control System

Abstract

The \"Intelligent traffic light control system \" project introduces an innovative approach to traffic management, aiming to expedite emergency vehicle passage. Utilizing Zigbee and Radio-Frequency Identification (RFID) technology, this system assigns a unique RFID tag to each vehicle, enabling precise tracking and control at traffic junctions. The scenarios involving emergency vehicle clearance, the system\'s responsiveness shines. When an emergency vehicle clearance approaches, the system rapidly receives the signal from zigbee transmitter associated with it and promptly triggers a green signal at the traffic junction. This prioritization ensures that emergency vehicles can navigate the traffic with minimal delays, potentially saving lives. Another remarkable feature of the system is stolen vehicle detection capability. In the event that a vehicle with a specific RFID tag is reported as stolen, the system is programmed to take action. It sends immediate SMS notifications to relevant authorities, such as law enforcement or the vehicle owner. This proactive response enhances the chances of recovering stolen vehicles and contributes to overall security. The hardware components of this system include Arduino Uno. Arduino Uno serves as the central control unit, processing RFID data and executing signal adjustments, while the GSM module facilitates real-time communication, enabling SMS alerts and notifications. The \" Intelligent traffic light control system \" project exemplifies how RFID technology and zigbee technology can revolutionize traffic management. By incorporating data analysis and automation, this system offers a multifaceted solution to common traffic-related challenges.

Introduction

I. INTRODUCTION

 India as highest population and it as rapid rise in economy. Urban traffic congestion represents challenge that significantly impacts economic efficiency, environmental sustainability, and it impacts the overall quality of urban life. This issue is aggravated by rapid urbanization, an increase in vehicle ownership, and lacks in existing road infrastructure and urban planning. The resultant effects are far-reaching, displaying having considerable extent delays, increased fuel consumption and stolen vehicle detection.  Technologies like ZigBee Along with Encoder & Decoder, RFID technology and GSM Module  is utilized among traffic management for the problems.It utilizes wireless technologies like RFID and Zigbee. RFID Technology utilizes radio frequency electromagnetic waves for carrying information among RFID tag and RFID reader.

They get operated in different frequency ranges across the area. ZigBee is a standards wireless  technology and developed to enable low-cost,low power and it utilizes radio signal between any two devices. Data is transmitted from transmitter end and it gets received by receiver module at the receiver end. GSM Module is a device that connects to a mobile network using sim cards and allows communication through voice, sms and data.

Urban traffic congestion represents a multifaceted challenge that significantly impacts economic efficiency, environmental sustainability, and the overall quality of urban life. This pervasive issue is exacerbated by rapid urbanization, an increase in vehicle ownership, and inadequacies in existing road infrastructure and urban planning. The resultant effects are far-reaching, manifesting as extensive delays, increased fuel consumption, elevated stress among commuters, and a rise in greenhouse gas emissions and pollutants.

Within this complex scenario, the need for emergency vehicle prioritization emerges as a critical concern. Emergency response vehicles, crucial for public safety and health, often find their paths obstructed by congested traffic, leading to potentially life-threatening delays.

Traditional traffic management systems, characterized by fixed signal schedules, fail to accommodate the urgent requirements of these vehicles, underscoring the necessity for an intelligent traffic control mechanism capable of dynamically facilitating their movement. Concurrently, the challenge of stolen vehicle tracking presents a significant dilemma for law enforcement and vehicle owners. The efficiency of recovering stolen vehicles is critically dependent on the timeliness of the response, a task complicated by the sophisticated methods employed by criminals to evade detection. While technologies such as RFID and GMS offer promising solutions for real-time vehicle tracking.

II. LITERATURE SURVEY

In [6], the authors proposed an intelligent traffic control system based on the design of a wireless sensor network in order to collect data at junctions  and to know available parking spaces. In addition, the proposed system has innovative approach that allow drivers to view the traffic  and the number of  parking spaces available at  destinations  using an Android mobile application to avoid traffic jams and to take another alternative route to avoid congestion  and to make it easier for drivers looking for a free parking space to avoid parking charges. This  system integrates three smart systems connected to each other  in order to connect citizens to a smart city application [6].

In [7], a new intelligent traffic control system is presented, which is based on the deployment of wireless sensor networks on roads, on traffic lights, and on specific places (such as hospitals and petrol pumps) in order to monitor road traffic in the city and find the shortest route to the destination in terms of time and distance, avoiding traffic jams. This system employs intelligent cameras on the roads to identify the vehicle numbers and send this information to the central system to monitor the cars in the city. The proposed system uses more recent technologies which allow the interconnection of the various urban services between them by creating a smart city.

However, the deployment of smart cameras can be expensive and also less effective, especially when detecting the numbers of cars in cases where there are visibility problems such as the reflection of light from car headlights, given that there are other cheaper and efficient solutions such as RFID technology which interacts with WSN networks and which allows vehicles to send this information to the central system in a sustainable and efficient way

The authors in [8] propose a system for monitoring road traffic  based on mobile devices and Bluetooth beacons with low energy consumption. The vehicle detection offered by this system uses mobile devices (for example, smartphones) installed on the side of the road to measure the strength of the RSSI signal when receiving radio frequency frames emitted by Bluetooth beacons on the other across the street.

Bluetooth beacons are installed along the road at different heights in order to identify and classify the type of vehicles traveling on the road (cars or trucks). The RSSI values detected by mobile devices on each route as well as their positions are sent via a cellular network or Wi-Fi communication to a server in order to measure the density of road congestion and monitor traffic on the roads. On the other hand, Bluetooth technology can cause major synchronization problems and communication breakdowns between the BLE beacon and the smartphone, which negatively affect the feasibility of the system, especially in the case of heavy traffic. So, an agent must be on-site to pair the two devices to resume communication.

The authors in [9] present a new intelligent traffic monitoring and traffic light control system based on wireless sensor networks. These sensor nodes are installed along the roads constituting a road intersection.

The data captured by the sensors is sent to a two-traffic signal controller to assess the congestion conditions of traffic on each road at an intersection and to predict the state of traffic jams. This system uses a self-organization protocol (Alg5) which creates a star topology between the different nodes of the network.

However, the algorithm adopted by this system will create dark areas for certain nodes far from their associated central node which they will not be able to communicate with it and which will cause degradation in the quality and in the feasibility of this system. This solution makes it possible to dynamically manage the traffic lights according to the states of traffic congestion obtained in an intersection and also makes it possible to optimize the synchronization phase of traffic light control in order to avoid traffic jams before its formation.

The intelligence of this system remains beyond the reach of drivers and citizens because they do not interact with the remote system and also do not connect to roads in real time.

The authors in [10] describe a new intelligent system of adaptive traffic light control based on the deployment of the wireless sensor network (WSN) in the roadways leading to an intersection. These nodes are magnetic sensors installed in the ground along all the paths that form an intersection. These sensors form a cluster-type network topology in which each node detects the presence of vehicles and sends the data to the nearest head cluster to reach the base station. The data collected by the WSN is used by the base station by running an algorithm to detect the rate of traffic congestion in each lane and dynamically control the traffic lights at the road intersection.

In [11], use of  Bluetooth ,the arrival of the emergency vehicle  will be informed  when it is too close to a particular junction that there will be less time in order of seconds which is not useful in clearing of traffic signals. So there is a need to develop a new system which is cheaper as GPS and also more efficient than the Bluetooth. Thus using ZIGBEE module is the best way  for system.

V. FUTURE ENHANCEMENT

The future scope of this system lies in its adaptability to emerging technologies and the evolving needs of urban environments. As technology continues to advance, integrating the system with autonomous vehicles, 5G communication, and environmental monitoring will further enhance its capabilities.

Conclusion

In conclusion, the Intelligent Traffic Control System is a proactive solution for addressing the complex challenges associated with urban traffic. Its continued development and integration with cutting-edge technologies will contribute to the creation of more sustainable, efficient, and livable cities in the years to come. With automatic traffic signal control based on the traffic density in the route, the manual effort on the part of the traffic policeman is saved. As the entire system is automated, it requires very less human intervention Emergency vehicles like ambulance, fire trucks, need to reach their destinations at the earliest. If they spend a lot of time in traffic jams, precious lives of many people may be in danger. With emergency vehicle clearance, the traffic signal turns to green as long as the emergency vehicle is waiting in the traffic junction. With stolen vehicle detection, the signal automatically turns to red, so that the police officer can take appropriate action, if he/she is present at the junction. Also SMS will be sent so that they can prepare to catch the stolen vehicle at the next possible junctions. The signal turns to red, only after the emergency vehicle passes through. The Intelligent Traffic Control System with congestion control, ambulance clearance, represents a significant step towards creating smarter and more efficient urban transportation systems. By leveraging advanced technologies such as artificial intelligence, machine learning, and real-time data analytics, the system addresses critical issues in traffic management, emergency response, and public safety.

References

[1] Aasif Attar, PurvaDhuri and et.al (2015), “Intelligent Traffic Management SystemInternational Education & Research Journal [IERJ]”,Vol. 1, Issue. 4, pp. 1-3. [2] AnshuAdwani, RohitHande and et.al (2015), “Smart Highways Systems for Future Cities”, Vol. 3. Issue. 7, pp. 7292-7298. [3] D.Jayakumar, J.Omana, M.Siva kumar, B.Senthil, “A safe guard system for mine workers using wireless sensor networks”, International Journal of Applied Engineering Research , vol.10, no.8, pp.21429-21441,2015. [4] Bilal Ahmed Khan and NaiShyan Lai (2014), “An Advanced Fuzzy Logic based Traffic Controller”, Vol. 5, Issue. 1, pp.31-40. [5] Dinesh Rotake1 and SwapniliKarmore (2012), “Intelligent Traffic Signal Control System using Embedded System ? Innovative Systems Design and Engineering”, Vol. 3, Issue. 5, pp. 11-20. [6] Fahri Soylemez giller (2013), “A Traffic Congestion Avoidance Algorithm with Dynamic Road Pricing for Smart Cities”, pp. 2571-2575. [7] K. Vidhya and A. Bazila Banu (2014), “Density based Traffic Signal System”, Vol. 3, Issue. 3, pp. 2218 – 2223. [8] R. Sundar, S. Hebbar and V. Golla, \"Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection,\" in IEEE Sensors Journal, vol. 15, no. 2, pp. 1109-1113, Feb. 2015, doi: 10.1109/JSEN.2014.2360288. [9] Kulkarni, S. S., & Ade, D. R. (2017). 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(2), pp. 57–71. [10] Adil Hilmani, Abderrahim Maizate, Larbi Hassouni, \"Automated Real-Time Intelligent Traffic Control System for Smart Cities Using Wireless Sensor Networks\", Wireless Communications and Mobile Computing, vol. 2020, Article ID 8841893, 28 pages, 2020. https://doi.org/10.1155/2020/8841893

Copyright

Copyright © 2024 Md Reshma , N V N Sai Eshwari , M Nikhila , R Bhavana , Sai Ganesh Reddy. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.