An Efficient Cloud-Based Traffic Signal Manipulation Algorithm for Path Clearance

2020 ◽  
Vol 11 (2) ◽  
pp. 32-44
Author(s):  
Aamir Wali ◽  
Khansa Tanveer ◽  
Samreen Fatima ◽  
Ayeza Tanveer ◽  
Sara Iftikhar
Keyword(s):  
Cloud Computing ◽  
Developing Countries ◽  
Real Time ◽  
Shortest Path ◽  
Traffic Management ◽  
Traffic Signals ◽  
Grid System ◽  
Traffic Light ◽  
Traffic Conditions ◽  
Emergency Vehicles

Beside many challenges that urban cities have to face, one of them is increasing traffic. Unfortunately, in developing countries like, for example, Pakistan, the traffic management infrastructure does not scale accordingly. This leads to two types of problems: congestion and long queues at traffic signals. This makes it difficult for emergency vehicles (EV) such as ambulances to reach their destination on time. Therefore, in this article, the authors have developed an intelligent path clearance system for emergency vehicles. The particular focus is on long queues at traffic signals. Given the GPS coordinates of an EV, a destination, a map, and the traffic light grid system, our system provides a signal free corridor to the priority vehicle by automatically manipulating traffic signals that fall in its path using cloud computing. The idea is to clear the path of the vehicle. The proposed system also makes decision based on the time of the day and current traffic conditions in real time. In case of multiple options, it also calculates the shortest path to the destination.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

An Advanced Fuzzy Logic Based Traffic Controller

2014 ◽  
Vol 5 (1) ◽  
pp. 31-40
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Urban Traffic ◽  
Image Processing Technique ◽  
Traffic Light

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

scholarly journals Traffic Light Controller using Image Processing

2021 ◽  
Vol 12 (2) ◽  
pp. 405-411 ◽  
Author(s):  
Lakshmanan M, Et. al.
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Signals ◽  
Daily Basis ◽  
Traffic Density ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Systems

Traffic congestion at junctions is a serious issue on a daily basis. The prevailing traffic light controllers are unable to manage the different traffic flows. Most of the current systems operate on a timing mechanism that changes the signal after a particular interval of time. This may cause frustration and result in motorist's time waste. Traffic congestion is a major problem in the currently existing systems. Delays, safety, parking, and environmental problems are the main issues of current traffic systems that emit smoke and contribute to increasing Global Warming. Sensor-based systems reduce the waiting time and maximize the total number of vehicles that can cross an intersection. Our proposed system can control the traffic lights based on image processing without the need for traffic police. This can reduce congestion, delay, road accidents, need for manpower. Under image processing, we use sub techniques like RGB to Gray conversion, Image resizing, Image Enhancement, Edge detection, Image matching, and Timing allocation. A real-time image is captured for every 1 second. After edge detection procedure for both reference and real-time images, these images are compared using SURF Algorithm. Then the amount of traffic is detected and the details are stored in the server. Arduino is used for a traffic signal in the hardware part. It consists of a Wi-Fi module. The micro-controller used in the system Arduino. Four cameras are placed on respective roads and these cameras are used to capture images to analyze traffic density. Then the traffic signals are decided according to the density of traffic. Our technique can be effective to combat traffic on Indian Roads. A lot of time can be saved by deploying this system and also it conserves a lot of resources as well as the economy

scholarly journals Traffic Light Optimization using OpenCV

2020 ◽  
Vol 6 (12) ◽  
pp. 171-175
Author(s):  
Aditya Lahoty
Keyword(s):  
Real Time ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Computer Software ◽  
Green Light ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Traffic Signal ◽  
Traffic Light ◽  
Real Time Traffic

Traffic Light Optimization aims to find the solution for an increased amount of unnecessary waiting time on traffic signals. Traffic Signal Optimization is the process of changing the timing parameters relative to the length of the green light for each traffic movement and the timed relationship between signalized intersections using a computer software program. Our project aims to set the timer of green light based on real-time traffic congestion i.e. number of vehicles in a particular direction of the traffic light. To work in this project, we are using the OpenCV method to detect vehicles and then perform our calculation in the algorithm to predict the time for the green light to be in an active state.

scholarly journals Detecting anomalous road traffic conditions using VGG19 CNN Model

2021 ◽  
Vol 309 ◽  
pp. 01226
Author(s):  
M. Rajeshwari ◽  
CH. MallikarjunaRao
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Road Traffic ◽  
Dynamic Mode ◽  
Static Mode ◽  
Vehicle Accidents ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Street Traffic ◽  
Vehicle Movement

Detection on the real time road traffic has tremendous application possibilities in metropolitan road safety and traffic management. Due to the effect of numerous factors, for example: climate, viewpoints and road conditions in real-time traffic scene, Anomaly detection actually faces many difficulties. There are many reasons for vehicle accidents, for example: crashes, vehicle on flames and vehicle breakdowns, which exhibits distinctive and obscure behaviours. In this paper, we approached with a model to identify oddity in street traffic by monitoring the vehicle movement designs in two unmistakable yet associated modes which is 1. The vehicle’s dynamic mode and 2. The vehicle’s Static mode. The vehicle’s static mode investigation is gained using the background modelling after the detection of a vehicle, this strategy is useful to locate the unusual vehicle movement which keep still out and about. The dynamic mode vehicle examination is gained from identified and followed vehicle directions to locate the strange direction which is distorted from the predominant movement designs. The outcomes from the double mode investigations are at long last fused together by driven a distinguishing proof model to get the last peculiarity. For this research we are using traffic-net Dataset, VGG19 CNN model along with ImageNet weights and OpenCV.

Dynamic Routing of Emergency Vehicles with Traffic Management System and Implementation on CupCarbon for Smart Cities

2021 ◽  
Vol 9 (11) ◽  
pp. 1407-1412
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Smart Cities ◽  
Maximum Speed ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Traffic Management System ◽  
On The Road

The traffic congestion is one of the major problems in crowded cities, which causes people to spend hours on the road. In traffic congestion situations, finding alternate routes for emergency vehicles, which provides shortest travel time to nearby hospital is critically life-saving issue. In this paper, we propose a traffic management system and an algorithm for routing of an emergency vehicle. The algorithm uses distance between source and destination, maximum vehicle count, maximum speed, average speed, traffic light conditions on the roads, which are assumed to support vehicle-to-infrastructure (V2I) communication in 5G IoT network. Simulations are performed on CupCarbon IoT simulator platform for various test scenarios. The performance of the proposed emergency vehicle routing algorithm is compared against well known Link State algorithm. And, the results demonstrate the effectiveness of the proposed method.

An Advanced Fuzzy Logic Based Traffic Controller

2015 ◽  
pp. 1490-1499
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Traffic Light ◽  
Logic Control

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

Smart Traffic Light Systems

2018 ◽  
Vol 6 (7) ◽  
pp. 243
Author(s):  
A. Vinidha Roc ◽  
P. R. Banuprakash ◽  
G. Paul Asir Nixon Raj ◽  
L. Prasad
Keyword(s):  
Traffic Signals ◽  
The Other ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Smart Traffic

Traffic signals are the most efficient way of controlling traffic in a busy junction. But, we can see that these signals fail to control the traffic effectively when a particular lane has got more traffic than the other lanes. The idea behind this project is to implement a system which would easily control the traffic and helps for the emergency vehicles to reach at their destination easily and quickly. In our project, a system of cameras are used to regulate traffic. They obtain information in their respective places and coordinate with other cameras in the system to change traffic signals and suggest green signal for that route to avoid maximum traffic. Emergency vehicle can be detected with the help of sound sensors placed in the junction, which coordinates with the microcontroller and makes the particular Lane free.

CITRAM - Citizen Science for Traffic Management

2020 ◽  
Author(s):  
Benedikt Gräler ◽  
Christoph Doll ◽  
Jürgen Mück ◽  
Albert Remke ◽  
Diana Schramm ◽  
...  
Keyword(s):  
Real Time ◽  
Citizen Science ◽  
Traffic Management ◽  
Combustion Engine ◽  
Open Data ◽  
Field Tests ◽  
Driving Behavior ◽  
Traffic Light ◽  
Floating Car Data ◽  
German Cities

&lt;p&gt;The CITRAM project aims at improving traffic quality in cities with the help of floating car data provided by citizens. During CITRAM, the citizen science platform enviroCar (https://www.enviroCar.org) has been extended and is used to collect floating car data in three German cities. Citizens are invited to collect data in designated field tests while driving their day-to-day routes. These collected trajectories are anonymised, stored and published under an open data policy in a central server.&lt;/p&gt;&lt;p&gt;Dedicated postprocessing services using new concepts for evaluation and visualization analyze the data on a daily basis deriving traffic quality characteristics. The raw data and the processed reports are used by the cities and their planners to assess the traffic quality and to deduce actions to improve traffic management.&lt;/p&gt;&lt;p&gt;The project also raises the awareness of an environmentally improved driving behavior through the collection of floating car data enriched with individual energy and fuel consumption along the recorded routes of electric and internal combustion engine driven cars. Through the integration of municipal information infrastructure into a dedicated real-time Smart City platform and a model accounting for the dynamic control of traffic light systems, a traffic light phase assistant app (ECOMAT) further supports the driver in a foresighted and energy optimized driving behavior by providing Green Light Optimised Speed Advisory (GLOSA) and Time To Green (TTG) information in real-time.&lt;/p&gt;&lt;p&gt;The motivation of CITRAM is the coupling of system components that enable scientists, traffic engineers and citizens to collaborate on knowledge acquisition concerning driving in motorized traffic. We will present the developed tool set and the results from the analysis of floating car data collected by citizens. The analysis assess the quality of traffic flow within the municipality as well as characteristics of individual trajectories or dedicated routes.&lt;/p&gt;

scholarly journals Reservation-based traffic management for autonomous intersection crossing

2019 ◽  
Vol 15 (12) ◽  
pp. 155014771989595 ◽  
Author(s):  
Myungwhan Choi ◽  
Areeya Rubenecia ◽  
Hyo Hyun Choi
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Traffic Management ◽  
Optimization Problem ◽  
Traffic Signals ◽  
Scheduling Scheme ◽  
Speed Range

A scheduling scheme for autonomous intersection crossing is proposed and evaluated. The scheduling scheme determines the flow of autonomous vehicles into an intersection without traffic signals. The objective of the scheduling scheme is to schedule the vehicles’ entrances into the intersection such that there will be no collision among vehicles and the intersection is efficiently utilized. Our scheduling scheme uses reservation-based scheduling approach, and the scheduling is formulated as an optimization problem to find the best sequence of vehicles’ entrances into the intersection. Our scheme is made more practical by allowing the vehicles to move at any speed within a speed range, and it is shown that it is fast enough to be used in real time. Through simulation, it is also shown that our scheduling scheme significantly outperforms the first-come, first-served approach, which is the approach used by other reservation-based scheduling schemes.

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