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

Krumnow, Mario; Kretschmer, Andreas

doi:10.1007/978-3-662-45079-6_10

Cited by 2 publications

(1 citation statement)

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“…SUMO [4][5] is a simulation framework that is used for microscopic and continuous road traffic simulation package designed to handle large road networks. It applies to develop different applications, including online traffic monitoring system [17], traffic light games [18], and etc. Two different modules Sumo-net-convert and Sumo-route, and they are added to get the best routing decision.…”

Section: Related Workmentioning

confidence: 99%

Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System

Akhter¹,

Ahsan²,

Quaderi³

2019

IJACSA

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This paper focuses on Sumo Urban Mobility Simulation (SUMO) and real-time Traffic Management System (TMS) simulation for evaluation, management, and design of Intelligent Transportation Systems (ITS). Such simulations are expected to offer the prediction and on-the-fly feedback for better decision-making. In these regards, a new Intelligent Traffic Management System (ITMS) was proposed and implemented-where a path from source to destination was selected by Dijkstra algorithm, and the road segment weights were calculated using real-time analyses (Deep-Neuro-Fuzzy framework) of data collected from infrastructure systems, mobile, distributed technologies, and socially-build systems. We aim to simulate the ITMS in pragmatic style with micro traffic, open-source traffic simulation model (SUMO), and discuss the challenges related to modeling and simulation for ITMS. Also, we expose a new model-Ant Colony Optimization (ACO) in SUMO tool to support a multi-agent-based collaborative decisionmaking environment for ITMS. Beside we evaluate ACO model performance with exiting built-in optimum route-finding SUMO models (Contraction Hierarchies Wrapper)-CHWrapper, A-star (A*), and Dijkstra) for optimum route choice. The results highlight that ACO performs better than other algorithms.

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Section: Related Workmentioning

confidence: 99%

Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System

Akhter¹,

Ahsan²,

Quaderi³

2019

IJACSA

View full text Add to dashboard Cite

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A SUMO Based Simulation Framework for Intelligent Traffic Management System

Akhter¹,

System²,

Ahsan³

et al. 2020

jtle

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Continuous increments in world population demands transportation with essential vehicle facilities and directly effect on road traffic volume or congestion, mostly in metropolitan cities, and thus it needs significant investigation, analysis, and maintenance. In these regards, an Intelligent Traffic Management System (ITMS) with a Deep-Neuro-Fuzzy model was proposed and implemented. Dijkstra algorithm is used to select optimum path from source to destination on the basis of calculated road segment weights from Deep-Neuro-Fuzzy framework. However, Deep-Neuro-Fuzzy framework needs some comprehensive analysis, other means some simulation or emulation, and etc, to proof the efficiency and workability of the model. In this paper, we are going to explore the Deep-Neuro-Fuzzy model in pragmatic style with an open-source traffic simulation model (SUMO) and helps to explore traffic-related issues including route choice, simulate traffic light or vehicular communication, etc in our ITMS. In addition, a new GUI is developed to control the simulation input attributes and presents the feedbacks into the traffic flow in SUMO environment. Results highlight that the proposed SUMO model can realistically simulate ITMS based on the road segment weights from Deep-Neuro-Fuzzy model. Different built-in routing algorithms are also used to proof the workability of this model.

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

Cited by 2 publications

References 1 publication

Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System

Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System

A SUMO Based Simulation Framework for Intelligent Traffic Management System

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