Mobility Sim Lab
Berlin Project
Simulation Overview
The simulation was developed entirely using open-source software and publicly available data.
It covers central areas of Berlin commonly referred to as “downtown,” including Mitte, Charlottenburg, Kreuzberg, and other nearby districts. All infrastructure elements featured in the simulation (such as roadways, railways, etc.) as well as components of the public transportation system (buses, trams, S-Bahn, U-Bahn, stops, and stations) were modeled using up-to-date and accurate real-world data.
The color scheme used in the simulation to represent different modes of transport is as follows: Orange: Buses Turquoise: Trams Red: S-Bahn trains Blue: U-Bahn trains.
The simulation was designed to represent the morning rush hour period between 06:00 and 09:00. Accordingly, all simulation outputs and visualizations are based on this time window.
Video Description: In the video, a selection of vehicles from the simulation is shown, each illustrating a 3-stop segment of its route. These vehicles were chosen at random from various transport modes. A full inspection of the simulation shows that all vehicles correctly follow their designated routes. However, in order to keep the video concise, only one example from each transport mode was included, and only three stops per vehicle are shown.
0:00–1:00: An overview of the entire simulation
From 1:30: Visualization of the movement of bus line 100. A comparison of the bus’s stop pattern with its actual timetable confirms accurate route modeling.
From 2:30: A segment from tram line 21 is presented. The route is shown to be consistent with real-world data and timing.
From 3:15: A portion of the U-Bahn line U8 is featured. The vehicle follows its expected path, matching the real timetable.
From 4:00: Footage of S-Bahn line S1 is shown. Like the other modes, this line closely matches real-world conditions. The corresponding timetable is not displayed in the video due to it occupying the full screen.
Conclusion: The simulation results suggest that, provided certain limitations are addressed and sufficient computing power is available, Berlin’s public transportation system can be accurately modeled. This opens up the possibility for more in-depth data analysis, enabling performance assessments and targeted improvements to the public transit network.
Note: The simulation was developed using only SUMO and OSM software, along with their respective open-source tools and data. While this simulation was developed using scientific methods, it is not part of a formal academic or peer-reviewed research project. Additionally, no commercial revenue has been generated from this work.
Yours sincerely,
1. Departure – Arrival:
This graph shows the correlation between the departure and arrival times of trips in the simulation. The different colored dots likely represent different routes or buses.
2. Acceleration vs Distance:
This graph visualizes the acceleration and deceleration of public transport vehicles over distance. Frequent speed changes reflect stops, traffic lights, and pedestrian crossings. The clustering of values around zero indicates a generally stable driving profile. Sudden changes may signal potential safety or comfort issues.
3. Network Allocation:
This graph displays the distribution of routes or bus lines across the network in the simulation. Each color likely represents a different route. The network’s center-focused structure suggests that transportation radiates from the center to the periphery.
3. Speed Distribution:
Road speeds are represented using a color scale; red indicates the fastest areas, while blue shows the slowest. The values are given in meters per second (m/s).
2. Location of the Traffic Lights:
This map shows the positions of traffic lights, marked by red dots, overlaid on the road network.
The public transportation schedules used here were obtained from BVG (Berliner Verkehrsbetriebe), Berlin’s main public transport operator.
