Real-Time Simulations Based on Live Detector Data – Experiences of Using SUMO in a Traffic Management System

2014 ◽  
pp. 136-145 ◽  
Author(s):  
Mario Krumnow ◽  
Andreas Kretschmer
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Traffic Management System ◽  
Real Time Simulations

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 Verification of the European Rail Traffic Management System in Real-Time Maude

2018 ◽  
Vol 154 ◽  
pp. 61-88 ◽  
Author(s):  
Ulrich Berger ◽  
Phillip James ◽  
Andrew Lawrence ◽  
Markus Roggenbach ◽  
Monika Seisenberger
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Traffic Management System ◽  
Rail Traffic

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.

Design and Implementation of an Intelligent Traffic Management System

2019 ◽  
pp. 58-79 ◽  
Author(s):  
Shamim Akhter ◽  
Sakhawat Hosain Sumit ◽  
Md. Rahatur Rahman
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Route Planning ◽  
Efficient Solutions ◽  
The Road ◽  
Decision Attributes ◽  
Software Modules ◽  
Traffic Management System

Intelligence traffic management system (ITMS) provides effective and efficient solutions toward the road traffic management and decision-making problems, and thus helps to reduce fuel consumption and emission of greenhouse gases. Software-based real-time bi-directional TMS with a neural network was proposed and implemented. The proposed TMS solves a decision problem, dynamic road weights calculation, using different environmental, road and vehicle related decision attributes. In addition, the development of the real-time operational models as well as their solving challenges has increased in a rapid manner. Therefore, the authors integrate the design and development of a neural-based complete real-time operational ITMS, with the combination of software modules including traffic monitoring, road weight updating, forecasting, and optimum route planning decision. Collecting, extracting the insights and inherit meaning, and modeling the tremendous amount of continuous data is a challenging task. A discussion is also included with the future improvements on ITMS.

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