SESAM – Mobility Simulations in the Cloud
SESAM is a collaborative platform for building digital twins and mobility simulations in the cloud. Benefit from ready-to-use scenarios or create your own. Run your simulations on our dedicated compute cluster to get your simulation results faster.
Build Mobility Simulations
Build large-scale simulation scenarios in an easy to use web interface within a few minutes time. Simply select the simulation area within a map, add some traffic patterns (e.g. vehicles, bicycles or pedestrians) and let SESAM do the rest for you. After creation, the scenario will be stored in your personal workspace within SESAM. Ready to run on our compute cluster or to download as a ZIP Archive.
Simulate and Analyze
Run simulations from your workspace on our cluster of high-performance computing nodes. SESAM uses the Eclipse SUMO mobility simulation toolkit for the computation of the dynamic models for all agents in your scenario.
Analyze your simulation results visually, share key figures and KPIs with your team, your customers or public stakeholders. Trigger multiple simulation runs with varying parameters to gain more insights on the sensitivity of your results.
City Planners &
Policy Makers
Rapidly assess the benefits of new mobility technologies for smart cities. Conduct feasibility studies for new public transport plans or significant changes in the infrastructure. Share results with public stakeholders in a secure cloud environment.
Traffic and Mobility Engineers
Analyze the traffic impact of construction sites and road closures. Evaluate the effectiveness of traffic light controllers for complex intersections and corridors. Gain valuable insights on mobility patterns and traffic bottlenecks – especially for major public events.
Automotive Software Engineers
Validate automated driving functions and AI algorithms in a realistic and multimodal traffic simulation. Quickly identify critical situations for further and more detailed testing. Evaluate realistic vehicle ranges and vehicles emissions based on a realistic driving profile that is impacted by a realistic traffic demand.