scholarly journals Enhanced Traffic Management System using Artificial Intelligent Congestion Control

2020 ◽  
Vol 9 (8) ◽  
pp. 1015-1018
Keyword(s):  
Urban Communities ◽  
Traffic Congestion ◽  
Smart City ◽  
Traffic Management ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Suitable Site ◽  
Traffic Management System ◽  
Online Traffic ◽  
The Internet Of Things

The smart city proposed by government is providing better infrastructure with possible automated device. Every smart city proposes to provide smart transport through automated traffic management .The peak hours face the congestion road and many traffic irregularities. The congested road aids in poor Travel experience, environmental pollution and health hazards by vehicular fuel. The solution to aforesaid issues leads to traffic Automation in urban communities. To implement the traffic automation need access to real time traffic congestion information, best possible route and alternate strategy with online traffic information applicable to specific traffic stream. An more suitable site visitors manipulate and MF has been mentioned to finish short information transmission and their corresponding motion performed via artificial intelligence. The VANET scenario, congestion manage algorithm executed through mobile agent controller uniformly organizes the traffic glide by way of heading off the congestion at the smart visitors zone ,The law-enforcement bodies ,the fire opponents and the clinical and/or paramedical teams consciousness on elevated quantity of crime in addition to lifestyles losses through site visitors irregularities. The benefits of adopting the internet of things(iot)provide a new prospect for intelligent site visitors improvement.

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>

scholarly journals A Review on Minimization of Ambulance Response Time Using Image Processing and Critical path Mapping Based on Traffic Con-trol

2021 ◽  
Vol 2 (2) ◽  
pp. 1-7
Author(s):  
Shuja Rafiq ◽  
Keyword(s):  
Image Processing ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Critical Path ◽  
Machine Learning Techniques ◽  
Emergency Vehicle ◽  
Real Time Traffic ◽  
Traffic Management System ◽  
Process Work ◽  
Economic Developments

India is a developing country; the population of India is growing exponentially. India ranks 2nd in the world in terms of population. As there will be a gradual increase in population there will be an increase in the number of vehicles, as a result of which traffic congestion is increasing and as a result, emergency vehicles such as ambulances, fire-fighters, etc. are having difficulty getting to their destination on time. Vehicle use is growing rapidly due to recent technological and economic developments, and at the same time, the lack of infrastructure against demand is leading to an increase in the number of accidents and fatalities. Minor problems in our health system have prompted us to come up with a petition to make this process work and save lives. Through book reviews and reflections, I have proposed a project in a smart traffic management system using image processing. The aim of this project is to improve simulation to determine traffic congestion, to detect a crash/accident, and to obtain an ambulance using image processing and machine learning techniques. The proposed independent work is simulated in the form of an experimental setup using Arduino and LED displays that mimic real-time traffic. These simulation results reflect the terms of the acquisition as it provides an emergency vehicle pass to catch up on peak hours.

Cloud IoT-Based Mobile Agent Framework for Real-Time Traffic Information Acquisition, Storage, and Retrieval

2019 ◽  
pp. 14-33
Author(s):  
Md Abdullah al Forhad ◽  
Md Nadim ◽  
Md. Rahatur Rahman ◽  
Shamim Akhter
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Traffic Information ◽  
Weather Data ◽  
Storage And Retrieval ◽  
Traffic Routing ◽  
Real Time Traffic ◽  
Traffic Management System ◽  
Vehicle Information

Traffic is an inevitable problem for metro cities around the globe. Intelligent traffic management system helps to improve the traffic flow by detecting congestions or incidents and suggesting appropriate actions on traffic routing. A new and dynamic internet-based decision-making tool for traffic management system was proposed and implemented in authors' previous works. The tool needs weather, road, and vehicle-related integrated information from different data repositories. Several online web portals host real-time weather data streams. However, road and vehicle information are missing in those portals. In addition, their coverage is limited to city-level congregate information but precise road segment-based information is necessary for real-time TMS decision. Internet of things (IoT)-based online sensors can be a solution for this circumstance. As a consequence, in this chapter, an IoT-based framework is proposed and implemented with several remote mobile agents. Agents are securely interconnected to the cloud, and able to collect and exchange data through wireless communication.

Communication Improvement and Traffic Control Based on V2I in Smart City Framework

2020 ◽  
pp. 1620-1636
Author(s):  
Mamata Rath ◽  
Bibudhendu Pati
Keyword(s):  
Soft Computing ◽  
Traffic Control ◽  
Traffic Management ◽  
Smart Cities ◽  
Intelligent Vehicles ◽  
Traffic Information ◽  
Congested Traffic ◽  
Intelligent Communication ◽  
Traffic Management System ◽  
Online Traffic

This article describes how soft computing techniques are tolerant of imprecision, intended on approximation, focus on uncertainty and are based on partial truth. Current real-world problems pertaining to congested traffic is pervasively imprecise and therefore design of smart traffic control system is a challenging issue. Due to the increasing rate of vehicles at traffic points in smart cities, it creates unexpected delays during transit, chances of accidents are higher, unnecessary fuel consumption is an issue, and unhygienic environment due to pollution also degrades the health condition of general people in a normal city scenario. To avoid such problems many smart cities are currently implementing improved traffic control systems that work on the principle of traffic automation to prevent these issues. The basic challenge lies in the usage of real-time analytics performed with online traffic information and correctly applying it to some traffic flow. In this research article, an enhanced traffic management system called SCICS (Soft Computing based Intelligent Communication System) has been proposed which uses swarm intelligence as a soft computing technique with intelligent communication between smart vehicles and traffic points using the vehicle to infrastructure (V2I) concept of VANET. It uses an improved route diversion mechanism with implemented logic in nanorobots. Under a vehicular ad-hoc network (VANET) scenario, the communication between intelligent vehicles and infrastructure points takes place through nanorobots in a collaborative way. Simulation carried out using Ns2 simulator shows encouraging results in terms of better performance to control the traffic.

scholarly journals Dynamic Traffic Light Control

2020 ◽  
Vol 8 (6) ◽  
pp. 3228-3231
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Monitoring ◽  
Intelligent Transport System ◽  
Light Control ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control ◽  
Traffic Management System

Intelligent Transport System (ITS) is blooming worldwide. The Traditional Traffic management system is a tedious process and it requires huge man power, to overcome this we have proposed an automatic Traffic monitoring system that has effective fleet management. The current transportation system at intersections and junctions has Traffic Lights with Fixed durations which increase the unnecessary staying time which intern harms the environment. An Adaptive traffic light control is implemented using SUMO simulator, that changes the duration of Green and Red light according to the traffic flow. This is an effective and efficient way to reduce the Traffic congestion. The traffic congestion is determined by taking the object count using deep learning approach (Convolutional Neural Network).

scholarly journals Smart cities IOT & Digital network connectivity devices: Optimization on business in Africa

2021 ◽  
pp. 064-071
Author(s):  
Makeri Yakubu Ajiji ◽  
Xi’an Jiaotong Victor Chang ◽  
Targio Hashem Ibrahim Abaker ◽  
Uzorka Afam ◽  
T Cirella Giuseppe
Keyword(s):  
Internet Of Things ◽  
Urban Communities ◽  
Information And Communication Technologies ◽  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
The Internet ◽  
City Development ◽  
Short Article ◽  
The Internet Of Things

Today the world is becoming connected. The number of devices that are connected are increasing day by day. Many studies reveal that about 50 billion devices would be connected by 2020 indicating that Internet of things have a very big role to play in the future to come Considering the perplexing engineering of Smart City conditions, it ought not to be failed to remember that their establishment lies in correspondence advancements that permit availability and information move between the components in Smart City conditions. Remote interchanges with their capacities speak to Smart City empowering advancements that give the open door for their fast and effective execution and extension as well. The gigantic weight towards the proficient city the board has triggered various Smart City activities by both government and private area businesses to put resources into Information and Communication Technologies to discover feasible answers for the assorted chances and difficulties (e.g., waste the executives). A few specialists have endeavored to characterize a lot of shrewd urban areas and afterward recognize openings and difficulties in building brilliant urban communities. This short article likewise expresses the progressing movement of the Internet of Things and its relationship to keen urban communities. Advancement in ICT and data sharing innovation are the drivers of keen city degree and scale. This quick development is changing brilliant city development with the beginning of the Internet of Things (IoT). This transformation additionally speaks to difficulties in building (Kehua, Li, and Fu ,Su et al.1). By knowing the attributes of specific advances, the experts will have the occasion to create proficient, practical, and adaptable Smart City frameworks by actualizing the most reasonable one.

scholarly journals Sistem Pengamatan Kondisi Lalu Lintas Berbasis Data GPS pada Smartphone (Studi Kasus : Kota Denpasar)

2020 ◽  
Vol 7 (4) ◽  
pp. 667
Author(s):  
Gede Herdian Setiawan ◽  
I Ketut Dedy Suryawan
Keyword(s):  
Real Time ◽  
Traffic Congestion ◽  
Data Retrieval ◽  
Traffic Information ◽  
Vehicle Speed ◽  
Observation Model ◽  
Economic Activities ◽  
Traffic Condition ◽  
Traffic Conditions ◽  
Real Time Traffic

<p>Pertumbuhan jumlah kendaraan yang semakin meningkat setiap tahunnya mengakibatkan volume kendaraan yang melintasi ruas jalan semakin padat yang kerap mengakibatkan kemacetan lalu lintas. Kemacetan lalu lintas dapat menjadi beban biaya yang signifikan terhadap kegiatan ekonomi masyarakat. Informasi lalu lintas yang dinamis seperti informasi kondisi lalu lintas secara langsung <em>(real time)</em> akan membantu mempengaruhi aktivitas masyarakat pengguna lalu lintas untuk melakukan perencanaan dan penjadwalan aktivitas yang lebih baik. Penelitian ini mengusulkan model pengamatan kondisi lalu lintas berbasis data GPS pada <em>smartphone</em>, untuk informasi kondisi lalu lintas secara langsung. GPS <em>Receiver</em> pada <em>smartphone</em> menghasilkan data lokasi secara instan dan bersifat mobile sehingga dapat digunakan untuk pengambilan data kecepatan kendaraan secara langsung. Kecepatan kendaraan diperoleh berdasarkan jarak perpindahan koordinat kendaraan dalam satuan detik selanjutnya di konversi menjadi satuan kecepatan (km/jam) kemudian data kecepatan kendaraan di proses menjadi informasi kondisi lalu lintas. Secara menyeluruh model pengamatan berfokus pada tiga tahapan, yaitu akuisisi data kecepatan kendaraan berbasis GPS pada <em>smartphone</em>, pengiriman data kecepatan dan visualisasi kondisi lalu lintas berbasis GIS. Pengujian dilakukan pada ruas jalan kota Denpasar telah mampu mendapatkan data kecepatan kendaraan dan mampu menunjukkan kondisi lalu lintas secara langsung dengan empat kategori keadaan lalu lintas yaitu garis berwarna hitam menunjukkan lalu lintas macet dengan kecepatan kendaraan kurang dari 17 km/jam, merah menunjukkan padat dengan kecepatan kendaraan 17 km/jam sampai 27 km/jam, kuning menunjukkan sedang dengan kecepatan kendaraan 26 km/jam sampai 40 km/jam dan hijau menunjukkan lancar dengan kecepatan kendaraan diatas 40 km/jam.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The growth in the number of vehicles that is increasing every year has resulted in the volume of vehicles crossing the road increasingly congested which often results in traffic congestion. Traffic congestion can be a significant cost burden on economic activities. Dynamic traffic information such as information on real time traffic conditions will help influence the activities of the traffic user community to better plan and schedule activities. This study proposes a traffic condition observation model based on GPS data on smartphones, for information on real time traffic conditions. The GPS Receiver on the smartphone produces location and coordinate data instantly and is mobile so that it can be used for direct vehicle speed data retrieval. Vehicle speed is obtained based on the displacement distance of the vehicle's coordinates in units of seconds and then converted into units of speed (km / h), the vehicle speed data is then processed into information on traffic conditions. Overall, the observation model focuses on three stages, namely GPS-based vehicle speed data acquisition on smartphones, speed data delivery and visualization of GIS-based traffic conditions. Tests carried out on the Denpasar city road segment have been able to obtain vehicle speed data and are able to show traffic conditions directly with four categories of traffic conditions, namely black lines indicating traffic jammed with vehicle speeds of less than 17 km / h, red indicates heavy with speed vehicles 17 to 27 km / h, yellow indicates medium speed with vehicles 26 km/h to 40 km / h and green shows fluent with vehicle speeds above 40 km / h.</em></p><p><em><strong><br /></strong></em></p>

An Efficient Information Services-Centric Framework for Commuter

2012 ◽  
Vol 4 (1) ◽  
pp. 22-39
Author(s):  
Wee Siong Ng ◽  
Justin Cheng ◽  
XianJun Wang ◽  
Sivakumar Viswanathan
Keyword(s):  
Mobile Devices ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Spatial Information ◽  
Urban Environments ◽  
Mobile Environment ◽  
Real Time Traffic ◽  
Efficient Information ◽  
Matching Mechanism ◽  
Information Consumers

One of the major objectives of Advanced Traffic Management Systems (ATMS) is to reduce traffic congestion in urban environments by improving the efficiency of utilization of existing transport infrastructures. Many creative and efficient technologies have been developed over the years. Although commuters, especially drivers, take a critical part in containing traffic congestion problems, they are playing a passive role in the traffic-management ecosystem. Considerably, this is due to the information asymmetry between ATMS decision makers and commuters; what is missing is a matching mechanism to create a bridge between information providers and information consumers in the mobile environment. The authors’ solution provides an efficient services-centric framework for delivering pertinent information to commuters. Probe vehicles are used to estimate the real-time traffic flow and disseminate this information effectively to users’ mobile devices. A 2-level indexing scheme is designed to effectively index the grid cells which contain the spatial information and a location-aware mobile application and back-end services are also implemented. Processed information is disseminated to users’ mobile devices through wireless means and presented in a user friendly interface. Experimental results show that this system is scalable and responsive.

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