SUMO User Conference 2023
2023-05-02..2023-05-04
Berlin, Germany
[SUMO User Conference 2021, SUMO User Conference 2022, SUMO User Conference 2023]
who it's for
transport modelers, traffic engineers, urban mobility researchers, simulation researchers, data scientists, municipal traffic managers, software developers for transport
topics
origin-destination matrix reduction; netgenerate and netdiff workflows; sub-lane bicycle modeling; social-force cyclist controller; route randomization and emissions; reinforcement learning reward design; federated learning with SUMO; mesoscopic dynamic user equilibrium assignment; trajectory-based calibration with radar; sensor-based flow optimization via TraCI and MQTT; e-bike mode-shift and LCA analysis
| title | author | length |
|---|---|---|
| Tutorial | Jakob Erdmann | 01h 12m |
Quick how-to: generate synthetic grids with the netgenerate UI, compare networks visually with the integrated netdiff view, and build an OSM-derived scenario… | ||
| Simulation-based origin destination matrix reduction: a case study of Helsinki city area | Klavdiia Bochenina, Anton Taleiko, Laura Ruotsalainen | 19m |
Workflow reduces a 2,000-zone OD matrix to a ~400-zone Helsinki core by running one extended SUMO simulation, recording vehicle trajectories and border edges… | ||
| Comparing Measured Driver Behavior Distributions to Results from CF Models using SUMO and ... | Max Schrader, Mahdi Al Abdraboh, Joshua Bittle | 18m |
High-resolution roadside radar trajectories (50–200 ms) and piecewise linear fitting feed SUMO (v1.16, 0.1 s step) using IDM, EIDM and Krauss; supplying… | ||
| Development, calibration, and validation of a large-scale traffic simulation model: Belgium network | Behzad Bamdad Mehrabani, Luca Sgambi, Sven Maerivoet, Maaike Snelder | 21m |
A probabilistic travel demand model generates hourly OD matrices from four inputs (city populations, intercity distances, yearly vehicle‑km, yearly truck… | ||
| Keynote: e-bike-city: An answer to our transport dead-end? | Kay W. Axhausen | 32m |
Argues that reallocating 50% of road space to cycles and micromobility can preserve accessibility while cutting transport emissions, backed by mode choice and… | ||
| The state of Bicycle Modeling in SUMO | Mirko Barthauer, Aboozar Roosta, Heather Kaths, Jakob Erdmann, Yun-Pang Flötteröd, Michael Behrisch | 14m |
SUMO currently simulates bicycles by reusing car-following models such as IDM car-following used for bikes, with a sub-lane approach allowing side-by-side… | ||
| A Framework for Simulating Cyclists in SUMO | Heather Kaths, Aboozar Roosta | 19m |
Proposes a guideline approach that links SUMO’s sublane car-following framework with a two-dimensional social-force style controller (uses the Nomad model)… | ||
| The Effects of Route Randomization on Urban Emissions | Giuliano Cornacchia, Mirco Nanni, Dino Pedreschi, Luca Pappalardo | 13m |
SUMO simulations on Milan test a non‑deterministic routing scheme that samples k-path selection alternatives and injects route randomization from 0% upward in… | ||
| Challenges in Reward Design for Reinforcement Learning-based Traffic Signal Control | Christian Medeiros Adriano, Max Schumacher, Holger Giese | 21m |
Claim: a direct emission signal is a poor reward for bounded DRL agents. Experiments use SUMO with the default emission model, a DQN agent backed by a tiny… | ||
| Sensor-based Flow Optimization on connected real-world intersections via a SUMO Feature Gap Analysis | Ingo Trautwein, Emanuel Reichsöllner, Andreas Freymann, Jessica Schöps Kraus, Mirco Sonntag, Thomas Schrodi | 19m |
Project models real intersections in Erlangen to test whether SUMO can support a 5G-enabled, sensor-driven traffic light optimizer and proposes how to close… | ||
| SUMO Simulations for Federated Learning in Communicating Autonomous Vehicles | Levente Alekszejenkó, Tadeusz P. Dobrowiecki | 18m |
Uses the Monaco SUMO Traffic Scenario (MoST) to record parking occupancy with 60 simulation repeats producing about ~0.25 TB data, 60 runs, trains identical… | ||
| Analysis and Modelling of Road Traffic Using SUMO to Optimize the Arrival Time of Emergency Vehicles | Shamli Soni, Karsten Weronek | 14m |
Microscopic simulation using SUMO with QGIS Excel and Python reproduces Mörfelder Landstraße (3.3 km, five junctions) and calibrates OD matrices from induction… | ||
| Evaluating the benefits of promoting intermodality and active modes in urban transport … | Souhir Bennaya, Moez Kilani | 23m |
Microsimulation of a Mons‑style radial network uses a gravitational-like OD model and SUMO tools (import via netgenerate, routing with DUAROUTER and one‑shot… | ||
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