Contacts: Lara CODECA [[email protected]], Jerome HAERRI [[email protected]]
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
- In case there are problems with multi-threading, check that Issue #4518 has been solved in your target version.
Please refer to the SUMO wiki for further information on the simulator itself.
How to cite it: BibTeX
L. Codeca, J. Härri, "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. Härri, "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
MoST Scenario can be lunched directly with its configuration file.
sumo -c most.sumocfgorrun.shfrom the scenario folder.
See tools HOWTO for further details on how to chance and rebuild the scenario.



(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
- 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 [email protected] with your name and affiliation (if any).
