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MoSTScenario
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Monaco SUMO Traffic (MoST) Scenario
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MoSTScenario
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# Monaco SUMO Traffic (MoST) Scenario Contacts: Lara CODECA [lara.codeca@gmail.com], Jerome HAERRI [haerri@eurecom.fr] This project is licensed under the terms of the GPLv3 license. MoST Scenario is meant to be used with SUMO (Simulator of Urban MObility). * The master is tested with [SUMO 1.14.0](https://github.com/eclipse/sumo/tree/v1_14_0) * In case there are problems with multi-threading, check that [Issue #4518](https://github.com/eclipse/sumo/issues/4518) has been solved in your target version. Please refer to the [SUMO wiki](http://sumo.dlr.de/wiki/Simulation_of_Urban_MObility_-_Wiki) for further information on the simulator itself. ## How to cite it: [BibTeX](cite.bib) L. Codeca, J. Hรคrri, *"Towards Multimodal Mobility Simulation of C-ITS: The Monaco SUMO Traffic Scenario"* VNC 2017, IEEE Vehicular Networking Conference November 27-29, 2017, Torino, Italy. or L. Codeca, J. Hรคrri, *"Monaco SUMO Traffic (MoST) Scenario: A 3D Mobility Scenario for Cooperative ITS"* SUMO 2018, SUMO User Conference, Simulating Autonomous and Intermodal Transport Systems May 14-16, 2018, Berlin, Germany ## How To MoST Scenario can be lunched directly with its configuration file. * `sumo -c most.sumocfg` or `run.sh` from the _scenario_ folder. See [tools HOWTO](tools/HOWTO.md) for further details on how to chance and rebuild the scenario. ### Overview  ### Mobility Example [](https://www.youtube.com/watch?v=nFVhodnJKws) (click on the image for the video) ### Traffic Light Example [](https://www.youtube.com/watch?v=Wwp_riSsLAs) (click on the image for the video) ### Public Transportation Example [](https://www.youtube.com/watch?v=r7iE3LRiSNA) (click on the image for the video) ## The master is tested with Eclipse SUMO Version 1.14.0 (Build features: Darwin-21.5.0 arm64 Clang 13.1.6.13160021 Release FMI Proj GUI SWIG GDAL FFmpeg OSG GL2PS) ``` Performance: Performance: Duration: 3407.14s Real time factor: 10.566 UPS: 352602.634584 UPS-Persons: 49427.018430 Vehicles: Inserted: 46842 Running: 31 Waiting: 0 Teleports: 99 (Jam: 29, Yield: 55, Wrong Lane: 15) Emergency Stops: 6 Persons: Inserted: 45000 Running: 26 Jammed: 3865 Statistics (avg of 43356): RouteLength: 7217.10 Speed: 6.98 Duration: 6892.62 WaitingTime: 52.51 TimeLoss: 148.27 Bike Statistics (avg of 3455): RouteLength: 1876.49 Speed: 4.53 Duration: 428.03 WaitingTime: 35.13 TimeLoss: 64.48 Statistics (avg of 46811): DepartDelay: 0.37 Pedestrian Statistics (avg of 31421 walks): RouteLength: 451.37 Duration: 387.66 TimeLoss: 58.73 Ride Statistics (avg of 45216 rides): WaitingTime: 40.07 RouteLength: 6058.59 Duration: 609.21 Bus: 5967 Bike: 3455 ``` ### Users * Vincent Terrier, Aerospace System Design Laboratory, Georgia Institute of Technology, Atlanta, GA 30332-0105 * Tianshu Chu, Civil and Environmental Engineering, Stanford University If you are using MoST Scenario, or its tools to generate a new one, we would gladly add you to the list. You can send an e-mail to lara.codeca@gmail.com with your name and affiliation (if any).
