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.

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 City-Wide Real-Time Traffic Management System: Enabling Crowdsensing in Social Internet of Vehicles

2018 ◽  
Vol 56 (9) ◽  
pp. 19-25 ◽  
Author(s):  
Xiaojie Wang ◽  
Zhaolong Ning ◽  
Xiping Hu ◽  
Edith C.-H. Ngai ◽  
Lei Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Internet Of Vehicles ◽  
Real Time Traffic ◽  
Traffic Management System

scholarly journals Traffic Controlling System

2021 ◽  
Vol 9 (10) ◽  
pp. 1507-1512
Author(s):  
Rajvi Chokshi
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Reference Image ◽  
Present System ◽  
Real Time Traffic ◽  
Traffic Management System ◽  
On The Road ◽  
Evaluation Matrix

Abstract: In the present era, the population of people living in cities and the number of vehicles on the road is growing by the day. The necessity to govern lanes, thruways, and streets has become a significant concern as the urban population and, as a result, the number of vehicles has grown. Today's traffic framework places minimal emphasis on real-time traffic conditions, resulting in inefficient traffic management systems. Therefore, to overcome such limitations or drawbacks of the present system, the current research proposes a smart and efficient traffic management system that can analyze real-time traffic and take appropriate action. This is achieved by the application of an image processing technique, that would capture the real-time pictures of the paths to compare with the reference image of the path. The evaluation matrix is created to decide the amount of time each light must be on. In addition, an evaluation matrix is created. The purpose of the evaluation matrix is to determine how long each light must be turned on. The MATLAB 7.8 was used to perform the study.

Link Flow Evaluation Using Loop Detector Data: Traveler Response to Variable-Message Signs

1996 ◽  
Vol 1550 (1) ◽  
pp. 58-64 ◽  
Author(s):  
Youngbin Yim ◽  
Jean-Luc Ygnace
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Preliminary Investigation ◽  
Traffic Information ◽  
Mean Flow ◽  
Variable Message Signs ◽  
Real Time Traffic ◽  
Operational Test ◽  
Paris Region ◽  
Message Signs

Système d'Information Routière Intelligible aux Usagers (SIRIUS) is the largest urban field operational test of the advanced traveler information and automated traffic management system in Europe. With variable-message signs, SIRIUS has been in operation in the Paris region for 3 years. A preliminary investigation of the effectiveness of the SIRIUS system in traffic management is presented. The extent to which drivers respond to real-time traffic information and the consequential changes in link flow under SIRIUS is also presented. Time-series traffic data were analyzed to measure changes in mean flow rates at a selected link. It was found that variable-message signs influence drivers to choose less congested routes when drivers are provided with real-time traffic information, and that a driver's decision to divert is closely associated with the information pertaining to the level of congestion. In the Paris region, drivers received information on the length of the queue at the time of this study. As congestion becomes heavier, drivers are more likely to respond to variable-message signs. According to the data analysis, a queue length of 3 km seems to be a threshold at which a significant number of drivers choose to use an alternative route.

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