- Work on research projects studying mobility fleets
- Build on existing and bring in your own ideas
- Present your work at project meetings, conferences and publish in journals
- Discuss and collaborate with researchers from TUM and other universities
- Be involved in all project phases (working, reporting, and later on proposing new projects)
- Learn more about transportation science and become involved in teaching
- Interest and capabilities in modeling
- Understanding of data analysis and optimization
- Creativity to develop new models and solution approaches
- Teamwork and communication skills (preferably English and German)
- Programming (preferably knowledge in Python)
- M.Sc. in Computer Science, Physics or Mathematics or a similar subject area
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PhD position - Munich, Deutschland - Technical University of Munich
Beschreibung
PhD position (m/f/d) on Modeling of Mobility Fleets; Chair of Traffic Engineering and Control, Full time, TUM Campus Munich
07.05., Wissenschaftliches Personal
A new PhD position opened up at the Chair of Traffic Engineering and Control. We are looking for a researcher interested in optimization, programming for extending and improving our current simulation framework for on-demand fleets named FleetPy written in Python.
On-demand services usually offer spontaneous and flexible transportation for customers (and/or goods). Operators offering the service utilize a fleet of vehicles to serve these customers. Depending on the service design, this requires solving complex dynamic and stochastic routing problems to assign routes to up to thousands of vehicles that serve the customers. Exploiting demand forecasts allows implementing proactive vehicle rebalancing algorithms, while additionally control strategies for maintenance (i.e. charging) or pricing have to be considered.
In recent years, the focus has been on modeling, controlling and simulating on-demand fleets. Currently, real-world implementations of these services are gaining more attention but are often rather small stand-alone systems. Especially with the upcoming introduction of autonomous driving, on-demand fleets are expected to disrupt the present mobility system. We envision that automation of vehicles enables new integrated mixed system designs, where the mobility service provider can switch between line-based and on-demand operation mode based on their advantages and disadvantages.
The modeling approach in our simulation framework FleetPy is modular; on the one hand, FleetPy should be capable of representing real-world processes like charging, interacting with customers, picking-up people or parcels, on the other hand, it should be possible to focus on the most important aspects and simplify the model to allow integration into large-scale transportation system simulation models. Our objectives are to use parts of our modules within transportation models to simulate and evaluate the impact of future demand fleets on whole transportation systems and within real-world applications to help building an operating system and provide a test bed for the respective providers.
Your responsibilities:
Your qualifications:
We encourage you to apply even if your profile does not meet all of the requirements for the role yet. Your profile is expected to grow during the course of your PhD program.
Our offer: We offer a full-time position as academic staff with the opportunity to pursue a doctoral degree. Payment will be based on the Collective Agreement for the Civil Service of the Länder (TV-L). The actual salary depends on academic experience, family situation, tax classification, etc. Travel support for attending conferences, workshops, and summer schools is of course available. The contract is initially limited to two years with the possibility of extension.TUM strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women. Applications from disabled persons with essentially the same qualifications will be given preference.
