scholarly journals Intelligent Traffic Control System

2020 ◽  
Vol 8 (6) ◽  
pp. 4693-4696
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Detection System ◽  
Human Life ◽  
Video Camera ◽  
Emergency Vehicle ◽  
The Road ◽  
Emergency Vehicles ◽  
On The Road ◽  
Processing Techniques

Managing traffic maintaining order is the most demanding tasks in the contemporary day and age. Emergency vehicles such as an ambulance face lot of hardships when they get stuck in traffic, valuable human life is lost due to poor traffic management. In this paper a model is proposed for calculating traffic heaviness on roads using processing techniques for images with ambulance detection system and controlling model for traffic signals with the information extracted from images of vehicles on roads captured by video camera. The traffic intensity depends on the total vehicles on the road. The proposed model counts the vehicles in the lane and checks for the presence of emergency vehicles , whenever an emergency vehicle is detected that particular lane is allowed to move and the signal is turned to green.

scholarly journals Use of Mathematical Morphology in Vehicle Plate Detection

2018 ◽  
Vol 11 (4) ◽  
pp. 195-200
Author(s):  
NEERAJA MOHANAN ◽  
AFAQ AHMAD ◽  
SAYYID SAMIR AL-BUSAIDI ◽  
LAZHAR KHIRIJI ◽  
AMIR ABDULGHANI ◽  
...  
Keyword(s):  
Mathematical Morphology ◽  
Traffic Control ◽  
Traffic Management ◽  
Detection System ◽  
Software Tool ◽  
Recognition System ◽  
Continuous Increase ◽  
The Road ◽  
Toll Collection ◽  
On The Road

In the past couple of decades, the number of vehicles has increased radically. A statistic which presents the number of cars sold worldwide from 1990 through 2017, forecasts for 2018, some 81.6 million automobiles are expected to be sold by the end 2018. With this continuous increase, it is becoming very tedious to keep track of each vehicle for the purpose of security, law enforcement and traffic management. This phenomenon of rapidly increasing vehicles on the road highlights the importance for a vehicle number plate recognition system. By recognizing the car plates, the drivers of the vehicle can be identified from the database. Number plate detection system are used in various applications like traffic law maintenance, traffic control, automatic toll collection, parking systems, automatic gate openers. This paper presents a unique algorithmic procedure for detecting vehicle plate number which is based on the concept of mathematical morphology. The developed algorithm is simple, efficient and flexible. The algorithm is capable of working satisfactorily even in different constraints such as like rain, smoke and shadow. This user-friendly software tool is developed on MATLAB platform which is one of the common and efficient image processing analysis tools.

scholarly journals Automatic traffic light controller for emergency vehicle using peripheral interface controller

2019 ◽  
Vol 9 (3) ◽  
pp. 1788 ◽  
Author(s):  
Norlezah Hashim ◽  
Fakrulradzi Idris ◽  
Ahmad Fauzan Kadmin ◽  
Siti Suhaila Jaapar Sidek
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Emergency Situation ◽  
Light Signal ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Light Area ◽  
On The Road

Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.

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 Design and Development of Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VI) ◽  
pp. 3247-3252
Author(s):  
G. Kalyan
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Density ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

Traffic congestion is now a big issue. Although it seems to penetrate throughout the world, urban towns are the ones which are most effected. And it is expanding in nature that it is necessary to understand the density of roads in real time to better regulate signals and efficient management of transport. Various traffic congestions, such as limited capacity, unrestricted demand, huge Red Light waits might occur. While insufficient capacity and unlimited demand are somehow interconnected, their delay in lighting is difficult to encode and not traffic dependant. The necessity to simulate and optimise traffic controls therefore arises in order to better meet this growing demand. The traffic management of information, ramp metering, and updates in real-time has been frequently used in recent years for image processing and monitoring systems. An image processing can also be used for the traffic density estimation. This research describes the approach for the computation of real-time traffic density by image processing for using live picture feed from cameras. It focuses also on the algorithm for the transmission of traffic signals on the road according to the density of vehicles and therefore aims to reduce road congestion, which reduces the number of accidents.

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.

scholarly journals DETERMINATION OF TRAFFIC FLOWS PARAMETERS ON THE MANAGEMENT NETWORK

2020 ◽  
Author(s):  
Nataliia Semchenko ◽  
Keyword(s):  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Management ◽  
Traffic Flows ◽  
The Road ◽  
Specific Intensity ◽  
Traffic Flow Management ◽  
On The Road ◽  
Basic Characteristics

The work is devoted to the actual problem of determining the parameters of dense traffic flows on the road cities network, which can be used when introducing automated traffic control systems. The subject of the study is to determine the parameters of traffic flows in the central part of the city. The purpose of the work is to develop methods for determining the parameters of traffic flows of the street and road network on the basis of empirical and analytical modeling to reduce the number of peripheral measuring devices in the automated traffic control system. Methodology. In the given thesis there was solved the applied scientific problem of short-term operational forecasting of the traffic flow intensity on the transport network using the empirical-analytical approach, in which the measurement of traffic flow parameters at the entrances to the area of traffic flow management is carried out by transport detectors, internal local objects are determined by modeling. The proposed model is based on the determination of intensities at approaches to stop lines of internal crossroads of the management area using recurrent sequences. Experimental researches of traffic flows on the network and on the crossings were carried out using video filming during periods of maximum load. A comparative analysis of the simulation results with the experimental data showed that the relative error on a network with an area of 50-60 hectares does not exceed 3%, which indicates the adequacy of the model and the possibility of using it for management tasks. Practical implications. Implementation of the empirical-analytical method in automated traffic management systems will make it possible to reduce the number of detectors by 43-46% depending on the area of traffic management and obtain a sufficient economic effect. The regularities of the movement of dense traffic flows of high specific intensity on short hauls, typical for the central parts of cities, have been investigated. Value/originality. According to experimental results there were obtained approximating models of parameters of the logarithmic normal probabilistic law of time intervals distribution in dense traffic flows, the specific intensity of which exceeds 600 vph; the changes in basic characteristics of the vehicles group in the traffic flow when driving through the road crossing taking into account its intensity and the distance from the group forming object are determined.

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 Novel Road Traffic Management Strategy for Rapid Clarification of the Emergency Vehicle Route Based on V2V Communications

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5120
Author(s):  
Radwa Ahmed Osman ◽  
Amira I. Zaki ◽  
Ahmed Kadry Abdelsalam
Keyword(s):  
Traffic Management ◽  
Management Strategy ◽  
Road Traffic ◽  
Emergency Vehicle ◽  
The Road ◽  
V2v Communication ◽  
Vehicle To Vehicle ◽  
Proposed Model ◽  
V2v Communications ◽  
On The Road

Vehicle-to-vehicle communication is a promising paradigm that enables all vehicles in the traffic road to communicate with each other to enhance traffic performance and increase road safety. Through vehicle-to-vehicle (V2V) communication, vehicles can understand the traffic conditions based on the information sent among vehicles on the road. Due to the potential delay caused by traffic jams, emergency vehicles may not be able to reach their destination in the required time, leading to severe losses. The case is more severe especially in developing countries where no emergency-vehicle-dedicated lanes are allocated. In this study, a new emergency vehicle route-clarifying strategy is proposed. The new clarifying strategy is based on vehicular traffic management in different interference medium scenarios. The proposed model aims, through V2V communication, to find the nearest vehicle with which to communicate. This vehicle plays an important role in reducing the travel time: as the emergency message is received, this vehicle will immediately communicate with all the neighboring vehicles on the road. Based on V2V communications, all the vehicles in the road will clear from the lane in the road for the emergency vehicle can safely reach its destination with the minimum possible travel time. The maximum distance between the emergency vehicle and the nearest vehicle was determined under different channel conditions. The proposed strategy applied an optimization technique to find the varied road traffic parameters. The proposed traffic management strategy was evaluated and examined through different assumptions and several simulation scenarios. The obtained results validated the effectiveness and the accuracy of the proposed model, and also indicated significant improvement in the network’s performance in terms of packet delivery ratio (PDR) and average end-to-end delay (E2E).

scholarly journals Fail to Yield? An Analysis of Ambulance Crashes in Taiwan

2021 ◽  
Vol 13 (3) ◽  
pp. 1566
Author(s):  
Rong-Chang Jou ◽  
Ming-Che Chao
Keyword(s):  
Public Education ◽  
Weather Conditions ◽  
Medical Emergency ◽  
Transportation Safety ◽  
Emergency Vehicle ◽  
The Road ◽  
Mnl Model ◽  
On The Road ◽  
Crash Injuries ◽  
The Relationship

Introduction—Medical emergency vehicles help patients get to the hospital quickly. However, there were more and more ambulance crashes on the road in Taiwan during the last decade. This study investigated the characteristics of medical emergency vehicle crashes in Taiwan from January 2003 to December 2016. Methods—The ordered logit (OL) model, multinominal logit (MNL) model, and partial proportional odds (PPO) model were applied to investigate the relationship between the severity of ambulance crash injuries and its risk factors. Results—We found the various factors have different effects on the overall severity of ambulance crashes, such as ambulance drivers’ characteristics and road and weather conditions. When another car was involved in ambulance crashes, there was a disproportionate effect on the different overall severity, as found by the PPO model. Conclusions—The results showed that male ambulance drivers and car drivers who failed to yield to an ambulance had a higher risk of severe injury from ambulance crashes. Ambulance crashes are an emerging issue and need further policies and public education regarding Taiwan’s ambulance transportation safety.

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

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