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).
