SUMO - Simulation of Urban MObility An Overview

By Michael Behrisch, Laura Bieker, Jakob Erdmann, Daniel Krajzewicz. 2011

1,961 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4fd72cf38d951b2ae92fb1d9b705111335ef84ce

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Citations in the corpus

Smart Transportation: An Overview of Technologies and Applications (2023, methodology): “SUMO [76] is used for data collecting in a trafﬁc simulation scenario.”
A Survey on Recent Advances in Vehicular Network Security, Trust, and Privacy (2019, methodology): “SUMO [110] employs an extension of car-following model proposed by Stefan Krau β [111].”
A Survey on Platoon-Based Vehicular Cyber-Physical Systems (2016, background): “Some typical traffic mobility simulators include VISSIM [134], VanetMobiSim [135] and SUMO [136].”
Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey (2020, unknown): “To test the performance of the model, Luxembourg city map is used on SUMO with 196 intersections, which is the largest test environment for RLbased TSC up to now.”
A Review of Machine Learning and IoT in Smart Transportation (2019, methodology): “For the data collection a traffic simulation environment, SUMO [41] is used.”
Mobile fog: a programming model for large-scale applications on the internet of things (2013, methodology): “EVALUATION To show the bene.ts of Mobile Fog over a cloud based approach, in terms of communication cost, we conducted a network simulation using OMNeT++ [8] with realistic traf .c patterns generated by SUMO [1].”
Recent Development and Applications of SUMO - Simulation of Urban MObility (2012, background): “SUMO (“Simulation of Urban MObility”) [1][2] is a microscopic, inter- and multi-modal, space-continuous and time-discrete traffic flow simulation platform.”