Lectures
Computer Programming & Data Science – An Introduction with Python (101-0720-00L)
- 2025 Spring Semester
Microscopic Modelling and Simulation of Traffic Operations (101-0492-00L)
- 2024 Autumn Semester
- 2025 Autumn Semester
Projektübung Verkehr / Transportation Engineering Lab (103-0230-00 G)
- 2025 Spring Semester
Deterministische Signale und Systeme / Signal Processing (Prof. Dr. A. Klein, Prof. Dr.-Ing. M. Pesavento)
- 2016 Autumn Semester
Students / Thesis
Topic: (Ongoing)
Abstract: (Ongoing)
Profile: https://www.linkedin.com/in/omar-alami-badissi-97489920b/
Topic: Diffusion Modelling of Air Quality and Noise - Impacts from Detour Traffic on Uri Residents A Simulation-Based Case Study of Villages near the Gotthard Road Tunnel in Uri, Switzerland
Abstract: Traffic congestion near the northern entrance of the Gotthard Road Tunnel in the Swiss canton of Uri often leads to significant detours onto cantonal roads, diverting traffic through residential areas and raising concerns about the well-being of residents. While previous research and federally funded projects have largely focused on traffic flow optimisation, the perspective of affected residents has remained under-explored. This thesis addresses that gap by laying the foundation for a quantitative, resident-oriented assessment of the environmental externalities caused by traffic detours. Using traffic data generated by the SUMO simulation software, extended with a novel post-processing pipeline developed specifically for this work, the model estimates exposure levels of CO, NO2, PM2.5, and noise across six affected villages in the canton of Uri. The implementation is based on an explicit forward Euler scheme with central finite differences. Simulations were conducted over the course of a day for different dates, capturing both low- and high-congestion scenarios. The results show substantial variation in pollutant and noise exposure depending on the village and discuss what a reduction of traffic in Uri would change quantitatively.
Topic: Fairness on Ramp Metering - Extending ALINEA for Equitable Access and Congestion Reduction
Abstract: Ramp metering systems effectively reduce freeway congestion but often face public opposition due to inequitable delay distribution among users. This study addresses this challenge by introducing EqALINEA, a fairness-enhanced extension of the ALINEA algorithm designed to balance efficiency and equity in freeway access. Using microsimulations in SUMO, we evaluate ALINEA, Upstream ALINEA, and EqALINEA across both a simplified network and a real-world case study of Barcelona’s Ronda de Dalt corridor. Results indicate that traditional ALINEA prioritizes mainline throughput at the expense of spatial equity, disproportionately delaying on-ramp users near bottlenecks. EqALINEA mitigates these disparities by incorporating fairness constraints, including maximum waiting thresholds and proactive queue management. This approach leads to a more balanced distribution of delays while maintaining overall traffic efficiency within the simulation time. The algorithm adapts effectively to urban environments such as the Ronda de Dalt, where infrastructure limitations and evolving mobility policies require equitable traffic management solutions. This study demonstrates the feasibility of integrating fairness into decentralized ramp metering strategies to improve public acceptance and align with sustainable urban planning objectives.
Topic: Esslingen‘s Traffic Light Upgrade: An Evaluation
Abstract: Seven traffic light signals received new control systems in the city of Esslingen am Neckar in Germany. This thesis investigates the performance and efficiency during peak hours of the old and new traffic light control system using SUMO simulations. The older traffic light control system is a signal control system that operates based on a predefined Signal Phase and Timing (SPaT) schedule but adapts its parameters in response to real-time inputs from traffic detectors. The new system is a signal control system that dynamically determines traffic signal phases using real-time detector data and an algorithm. The evaluation focuses on three critical metrics: travel time, waiting time, and delay. The data for the old system was provided in the form of a VISSIM simulation while the data for the new system was provided in form of detector data. The simulation runs on SUMO demonstrate that the newer traffic light signal control system outperforms the existing system across all evaluated metrics, indicating an overall improvement in traffic flow efficiency. These findings underscore the benefits of implementing the updated traffic light control system to enhance urban mobility and reduce congestion during peak traffic periods.