Forschungsgruppen
Der Lehrstuhl für Vernetzte Verkehrssysteme teilt sich in vier Forschungsfelder ein, je mit ihrem eigenen Fokus, Werkzeugen, und Personal.
This research group focuses on human factors, their impacts on transport, and their interactions within different aspects of the transportation industry.
Key areas of investigation:
- Driving behavior (driving simulation, naturalistic driving)
- Travel behavior (gender impact, socio-demographics)
- Survey design
- Acceptance of disruptive transport technologies (e.g., UAM, Hyperloop)
- User experience evaluation, including comfort assessment in different transportation modes
- Behavior modeling for transportation planning and policy
Current projects:
Past projects:
Members:
- Christelle Al Haddad (Lead)
- Mohamed Abouelela
- Arkadiusz Drabicki
- Arunava Putatunda
- Filippos Adamidis
- Jumana Al-Weshah
- César Núñez
- Hao Wu
Open thesis topics:
- Modelling public transport choices in long-distance (intercity) trips. Mentoring: Dr. Arkadiusz Drabicki. Download description (release date 25.11.2024).
Key areas of investigation:
- DTA model calibration
- Redistributing metro demand to alleviate the effects of over capacity
- Optimizing and modeling dynamic van-pooling services
- Optimisation-based transportation operations
- Optimisation-based multimodal freight operations
Members:
Open thesis topics:
This research group focuses on modelling and simulating inter/multimodal transportation systems, emerging mobility and vehicle technologies.
Key areas of investigation:
- Transport demand and supply modeling (traditional and agent-based modeling)
- Modeling multimodal transportation systems
- Modeling emerging/on-demand mobility systems
- Modeling autonomous/connected autonomous vehicles
Current projects:
Past projects:
Tools and frameworks:
Members:
- Vishal Mahajan (Lead)
- Filippos Adamidis
- Qinglong Lu
- Santhanakrishnan Narayanan
- Arunava Putatunda
- Hashmatullah Sadid
- Ramandeep Singh
- Hao Wu
Open thesis topics:
- Simulation-Based Comparative Analysis of Synthetic Population Generation Methods: A Framework for Travel Diary Validation in Transport Simulation. Mentoring: Hao Wu and Cheng Lyu. Download Description. (release date: 17.02.2025)
- Graph neural networks for strategic transport modelling. Mentoring: Santhanakrishnan Narayanan. Thesis scope is open for discussion (release date: 17.06.2024)
- Demand-driven Vertiport Siting by Machine Learning and Agent-based Transport Simulation for UAM Network Expansion. Mentoring: Tao Guo and Hao Wu. Download description. (release date: 01.11.2024)
- Using MATSim-UAM Extension to Simulate the Charging Behavior of UAM Vehicles for Further Scenarios. Mentoring: Hao Wu. Download description. (release date: 23.11.2024)
The group focuses on identifying and using publicly available data for analytics and modeling applied to transport. Taking advantage of the diversity of datasets available, the research topics are not limited to a specific application but cover a wide range of problems in travel demand and behavior, traffic safety, and transportation supply, among other emerging topics.
Key areas of investigation:
- Demand calibration using opportunistic data.
- Collection of trip attributes and mobility information from opportunistic sources.
- Data fusion of multiple data sources for transportation modeling.
- Travel behavior modeling and safety analysis using naturalistic driving data.
- Transport supply modeling using OSM and GTFS data.
- Data-driven modeling of traffic prediction.
Current projects:
Past projects:
Members:
- Mohamed Abouelela (Lead)
- Saleh Ardameh
- Laura Gualda
- Soban Lone
- Cheng Lyu
- Santhanakrishnan Narayanan
- Ramandeep Singh
- Shahriar Iqbal Zame
- Hao Wu
Open thesis topics:
- Tabular Data Imputation for Synthetic Population with Diffusion Models. Mentoring: Hao Wu and Cheng Lyu. Download Description. (release date: 19.03.2025)
- Simulation-Based Comparative Analysis of Synthetic Population Generation Methods: A Framework for Travel Diary Validation in Transport Simulation. Mentoring: Hao Wu and Cheng Lyu. Download Description. (release date: 17.02.2025)
- Demand-driven Vertiport Siting by Machine Learning and Agent-based Transport Simulation for UAM Network Expansion. Mentoring: Tao Guo and Hao Wu. Download description. (release date: 01.11.2024)
- Data imputation using machine learning approaches. Mentoring: Santhanakrishnan Narayanan. Thesis scope is open for discussion (release date: 17.06.2024)
- Graph neural networks for strategic transport modelling. Mentoring: Santhanakrishnan Narayanan. Thesis scope is open for discussion (release date: 17.06.2024)
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