scholarly journals Intelligent Emergency Vehicle Preemption Using A Density Based System

2018 ◽  
Vol 7 (3.12) ◽  
pp. 572
Author(s):  
Voruganti Anirudh ◽  
M Neelaveni Ammal ◽  
Datla Suryatej ◽  
A V Satvik
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Emergency Vehicle ◽  
Fire Brigade ◽  
Traffic Jams ◽  
Signal Light ◽  
The World ◽  
Emergency Vehicles ◽  
Traffic Prioritization

Transit by road is one of the crude methods of transportation in various parts of the world as of today. The abundance of vehicles utilizing the street is expanding in an ascending order consistently. Because to this reason, traffic congestion in urban areas is becoming inescapable these days. The normal purpose behind traffic blockage is because of poor traffic prioritization, wherein a portion of the paths may have less traffic than the others with measure up to signal light length for both the paths. This Inefficient administration of traffic leads to wastage of crucial time, contamination, wastage of fuel, expenditure of transportation and worry to drivers, and so on however more vitally emergency vehicles like rescue vehicle stall out in traffic. Our project is on density based traffic control with the need to prioritize vehicles like emergency vehicle and fire brigade. In this way, it is especially important to plan a system to keep away from the setbacks. In this way counteracting mishaps, impacts, and traffic jams.  

scholarly journals GSM And IoT Based Smart Traffic System With Geofencing

10.31645/16 ◽  
2020 ◽  
Author(s):  
Muhammad Fahees Ghouri ◽  
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Location Based Services ◽  
Daily Routine ◽  
Emergency Vehicle ◽  
Traffic System ◽  
The Road ◽  
The World ◽  
Cloud Computation ◽  
Smart Traffic

Abstract— This project is aimed at resolving severe traffic congestion in most cities across the world by using latest technologies. The world is heading towards IoT and shifting daily routine manual processes to automatic systems. Current traffic control system is based on fixed timer which becomes one of the main reasons of transport blockage. In order to overcome this problem, a framework has been designed to introduce the concept of smart traffic system which includes Internet of Things. The road side sensors attached to the Arduino Mega send information to the cloud using NodeMCU where decision is taken based on density, hence involving cloud computation to turn a particular signal green. Moreover, we have also dealt with emergency vehicles which bears the facility of turning signal green using either RFID system or GSM based mobile. Sound sensors are placed to confirm that the signal return to normal condition once the emergency vehicle has crossed the signal. Lastly, a geofencing based marketing app called “Brando” has been designed using android studio to provide location-based services from the nearest stations like shopping malls to the people on road on their respective mobile phones.

scholarly journals Density based Traffic Control System Embedded with Patient Weightage Method

2019 ◽  
Vol 8 (10S) ◽  
pp. 377-381
Keyword(s):  
Control Systems ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Detection System ◽  
Raspberry Pi ◽  
Emergency Vehicle ◽  
Dynamic Flow ◽  
Smooth Flow ◽  
Emergency Vehicles ◽  
Traffic Control System

Every now and then traffic congestion has always been a hindrance in everyone’s normal life routine. This traffic congestion hindrance is very much problematic in case of high priority emergency vehicles namely ambulances, VIP vehicles, fire engines etc. So, traffic control has to be made proficient to provide smooth flow of vehicles. However, efficient synchronization of traffic at multiple junctions is complex. Conventional control systems do not handle the dynamic flow of traffic which results in chaos. In this project, implementation of an emergency vehicle detection system is done. The main objective is to provide a traffic-free route to the vehicles in order to save life. In this paper two cases are considered, in the initial case, the lane density at the junction will be calculated using ultrasonic sensors by Raspberry pi (Rpi) and the lane with minimal density route will be directed to the emergency vehicle NodeMcu in this case. Considering the assumption that hospital is present near to every lane. And in the second case, the conflict arises when two emergency vehicles are encountered at the same time at a junction, so this conflict is resolved in thispaper.

scholarly journals IoT Based Automated Traffic Light Control System For Emergency Vehicles Using LoRa

2019 ◽  
Author(s):  
Divij N ◽  
Divya K ◽  
Anuradha Badage
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Accurate Solution ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Lane ◽  
Emergency Vehicles ◽  
Scheduled Traffic ◽  
Cost Efficient

There is a serious issue of Emergency Vehicles being stuck at intersections due to traffic congestion or scheduled traffic signal. This may result in delay in motion or the Emergency Vehicle may remain in statutory position. Otherwise, if the emergency vehicle ever tries to override the signal, it may result in accident or traffic congestion. To overcome this problem automated traffic control system is proposed. The system is designed to find a cost efficient and accurate solution to save lives. In the system, siren of the approaching emergency vehicle is priorly sensed by using smart objects and the traffic lane in which the emergency vehicle isapproaching is made free by halting the traffic in other lanes of the intersection.

scholarly journals Density-Based Traffic Control System for Emergency Vehicles using Artificial Intelligence

2020 ◽  
Vol 9 (5) ◽  
pp. 1217-1221
Keyword(s):  
Artificial Intelligence ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Human Life ◽  
Traffic Signals ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Bearing Angle ◽  
Control Traffic

Fire brigade officers, health care personnel, police are often delayed due to traffic congestion, across major cities in India. Considering the predicament, Artificial Intelligence has the potential to enable us to solve such problems by adopting a number of unique perspectives and approaches, especially in this domain. The solution developed by us enables an emergency vehicle driver to select the route to reach the destination as quickly as possible. As cameras are deployed at most of the traffic signals today, especially in cities where traffic congestion is a major pain point, Video Analytics can be used for calculating vehicle count, which will be streamed and updated continually. We create effective algorithms to alter the time of the traffic signals based on this real-time vehicle count, the distance of the vehicle from the signal, the bearing angle made by the vehicle with the signal and also by making sure that the traffic congestion doesn’t increase exponentially and multiple emergency vehicles do not put the system in a deadlock. The loss of life due to accidents and the delay in getting the required treatment must be avoided. The designed system will automatically control traffic light intervals based on vehicle density. This solution will allow an emergency vehicle to reach its destination during emergencies, plying on the best possible route, in the most decongested traffic conditions, which will be facilitated by specifically developed algorithms. To save human life from accidents and unnecessary delays due to traffic congestion, is the main aim of our system.

scholarly journals Review of traffic control techniques for emergency vehicles

2019 ◽  
Vol 13 (3) ◽  
pp. 1243
Author(s):  
Wan Mohd Hafiz bin Wan Hussin ◽  
Marshima Mohd Rosli ◽  
Rosmawati Nordin
Keyword(s):  
Control System ◽  
Radio Frequency Identification ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Control Technique ◽  
Emergency Vehicle ◽  
Control Techniques ◽  
Emergency Vehicles ◽  
Traffic Control System

<span>Traffic control system play an important role to manage traffic congestion on the road especially during peak hours and peak seasons. One of the main challenges is to control the traffic when there are emergency cases at traffic light intersection especially peak hours. This could affect the route for emergency vehicles such as ambulance, fire brigade and police car to reach their destination. Due to the increase of traffic congestion during peak hours and peak seasons in Malaysia, there is a need for further evaluation of traffic control techniques. This paper reviewed and consolidated information on the different types of the existing traffic control system for road traffic management such as Radio Frequency Identification (RFID), wireless sensor network and image processing. This paper analysed and compared on the design, benefits and limitations of each technique. Through the reviews, this paper recommends the best traffic control technique for emergency vehicle that offers low price, low maintenance and can be used in various areas of applications.</span>

Smart Ambulance System Using Internet of Things: A Rumination

2019 ◽  
Vol 16 (10) ◽  
pp. 4249-4254
Author(s):  
Neelam Dahiya ◽  
Meenu Garg ◽  
Sheifali Gupta ◽  
Deepali Gupta
Keyword(s):  
Internet Of Things ◽  
Comparative Study ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Movement Control ◽  
Ambulance Service ◽  
Emergency Vehicle ◽  
The World

Currently, the traffic management is a foremost concern all over the world. Particularly in India, due to expanding urban populace and the quantity of vehicles, traffic congestion issues are increasing rapidly. Traffic congestion has become a major problem which affects the ambulance service to reach the hospital on time. With the advancement of technology, many solutions have been developed to curb this serious issue to save patient life. The IoT has the capacity to improve the scenario. The goal of this paper is to examine different IoT techniques for movement control and the different approaches to assist the emergency vehicle to reach nearby healing facility on time. The main focus is on finding the best techniques to reduce the traffic congestion. To discover the appropriate response of this issue, comparative study of the literature of last few years has been reviewed.

scholarly journals INTELLIGENT TRAFFIC CONTROL DEVICE MODEL USING AD HOC NETWORK

2019 ◽  
Vol 01 (02) ◽  
pp. 68-76
Author(s):  
Robert Bestak
Keyword(s):  
Traffic Flow ◽  
Automobile Industry ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Communication Systems ◽  
Ad Hoc ◽  
Road Traffic ◽  
Control Device ◽  
Device Model

The advancements in the technologies related to the wireless communication systems has made the vehicular adhoc networks prominent area of research in the automobile industry. The absolute volume of road traffic affects the safety, convenience and the efficiency of the traffic flow in the urban areas. So the paper scopes in developing an intelligent traffic control device model using the adhoc network to ameliorate the traffic flow. The proposed system enhances the convenience in travel by gathering the information of the vehicles along with the density of the vehicles and the movement of the vehicles on road. The device is modelled using the MATLAB and examined over the traffic flow on the peak hours as well as the normal hours and the holidays to understand its intelligent traffic control. The results obtained shows that the performance improvement in optimizing the traffic congestion through the proposed method is better compared to the existing methodologies used in traffic controlling.

scholarly journals Intelligent Recommendation module for more than one emergency vehicles node to destination node

2018 ◽  
Vol 6 (12) ◽  
Author(s):  
Farah Younus Safar ◽  
Emad I. Abdul Kareem
Keyword(s):  
Traffic Congestion ◽  
Optimal Path ◽  
Destination Node ◽  
Emergency Vehicle ◽  
Traffic Incident ◽  
Emergency Vehicles ◽  
Long Time ◽  
Real City

Traffic congestion may impede the power of emergency vehicles to arrive at the site of a traffic incident or other catastrophe in a fast and true way. Id's may not be a short one, but it is the optimal path that leads to the scene without passing in con-gested streets. Streets may be congestion for a long time and lead to not reach emergency vehicles to the destination place while other emergency vehicles can reach to the same destination place in fast which is far from the destination with uncrowded streets. This makes the emergency vehicle to reach the destination in fast. In this paper, The proposed module rep-resented in a map to show the algorithm for more than one source nodes to the destination node. In addition, a case study of a real city in Baghdad has been used to evaluate the proposed module. The results show the proposed module ability to find the optimal path with 27 to 204 seconds to give a clear recommendation for which vehicle must be moved to the destination node.

scholarly journals An Optimised Traffic Control Scheme with Preference to Emergency Vehicles Leveraging RFID

2021 ◽  
pp. 74-89
Author(s):  
Kenneth Akpado ◽  
Samuel Usoro ◽  
Nneka Ezeani
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Research Work ◽  
Control Points ◽  
Emergency Vehicle ◽  
Test Bed ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Traffic Control System ◽  
New System

Emergency Vehicles (EV) such as ambulances, fire fighting vehicles, Road safety vehicles and other emergency vehicles encounter delays on their missions at traffic light control points due to traffic jams. The direct consequence of these delays results in unwarranted loss of lives and properties.  This research work proposes and implements an improved traffic control system with preference to emergency vehicles leveraging RFID technology and a novel Dynamic Traffic Sequence Algorithm (DTSA). Atmega 328 was used to actualize the novel DTSA, control the RFID and the entire traffic control system. The distance of RFID signal transmitted by the emergency vehicle was determined by physically measuring the distance of clearer signal obtained at various distances from the test bed. MATLAB was used to plot the response time of the RFID, thereby helping in the choice of RFID used. It was observed at 100 meters distance between the RFID transmitter in the emergency vehicle (EV) and the traffic light system, a clearer signal was obtained. Therefore at 100 meters the emergency vehicle will be detected and the traffic system will reset its normal routine to give right of way to the particular lane that the emergency vehicle is detected. Comparing the old and the new system it was observed that in the new system the EV will be 12minutes faster than the EV in the old system. From the result obtained, the RFID best suited for this application is active RFID. The results obtained proved that the system will effectively mitigate and almost completely eradicate the delay encountered by emergency vehicles at traffic control points.  The system will be deployed in any many cities in Nigeria that have traffic control systems installed.

scholarly journals Prediction of Bike Sharing Demand

2017 ◽  
Vol 10 (1) ◽  
pp. 219-226 ◽  
Author(s):  
Purnima Sachdeva ◽  
K N Sarvanan
Keyword(s):  
New York ◽  
Linear Combination ◽  
Random Forests ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Machine Learning Techniques ◽  
Health Consciousness ◽  
Learning Techniques ◽  
The World ◽  
Bike Sharing

Bike sharing systems have been gaining prominence all over the world with more than 500 successful systems being deployed in major cities like New York, Washington, London. With an increasing awareness of the harms of fossil based mean of transportation, problems of traffic congestion in cities and increasing health consciousness in urban areas, citizens are adopting bike sharing systems with zest. Even developing countries like India are adopting the trend with a bike sharing system in the pipeline for Karnataka. This paper tackles the problem of predicting the number of bikes which will be rented at any given hour in a given city, henceforth referred to as the problem of ‘Bike Sharing Demand’. In this vein, this paper investigates the efficacy of standard machine learning techniques namely SVM, Regression, Random Forests, Boosting by implementing and analyzing their performance with respect to each other.This paper also presents two novel methods, Linear Combination and Discriminating Linear Combination, for the ‘Bike Sharing Demand’ problem which supersede the aforementioned techniques as good estimates in the real world.

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