PhD position in Congestion-informed dynamic space allocation for different transport modes

The Traffic Engineering group (SVT) of the Institute for Transport Planning and Systems (IVT) at ETH Zurich intends to design tools for modeling of multi-modal traffic dynamics at macroscopic level with a goal to develop novel methodologies for optimal traffic assignment and dynamic space allocation.

Transport policy is currently not finding a way out of its dilemma; the imminent need to decarbonize a sector fast which has barely moved in the recent past and the social requirement to maintain and increase accessibility across all modes, but not encourage sprawl while still allowing further decreases in the generalised cost of travel by new technologies and business models. The project is based on the design idea to reallocate 50% of the existing urban road space to e-bikes. The main task is to assess what the change could achieve in terms of global accessibility, generalised costs of travel, changes in daily life and reductions in emissions and CO2, and local traffic flow performance. The project will integrate careful involvement of the various interested partners from citizens, cities, firms to interest groups.

The role of the SVT within the project regards the design and implementation of a decision tool for assignment and optimal space allocation modeling. This tool should be based on the ideas of multi-modal dynamic macroscopic fundamental diagram to be determined prescriptively, based on simulated or recorded data.

The doctoral researcher is encouraged to conduct research in the following areas:

• Derivation of M-MFD
• Traffic assignment using M-MFD between network regions
• Optimal dynamic space allocation using M-MFD

We envisage for a comprehensive assessment of the interconnected aspects of the design of an e-bike-city and how it will fulfil the mobility needs of the citizens and other users. The goal is to achieve a tangible step towards sustainable cities, by achieving net-zero emissions and accessibility levels as today. We thus expect a doctoral student being able to have regular frequent interaction and presence on relevant research groups at the University and possibly with other interested partners.

You ideally have a Master’s Degree in engineering, applied mathematics, computer science or related fields. You are highly motivated, determined, you have excellent communication and writing skills (proficient spoken and written English is required).

Moreover, the following skills are expected of a promising candidate:

• Hands-on experience with programming and data analysis.
• Experience on traffic simulation and modeling and ideally familiarity with the MFD.
• Mathematical optimization (MILP, LP, IP), and control sciences (QPC, NMPC, LQC).
• Team working and communication skills. Knowledge of German is a plus.

The applicant is expected to:

• Publish in top journals and scientific conferences.
• Guide/follow semester projects at BSc/MSc level.
• If applicable, teach within the SVT course programme.
• Contribute to the operation of the group and the Institute.

You enjoy working in an active international environment with other doctoral students, post-docs and senior scientists, referring continuously to practical problems and solutions. You have a keen curiosity about traffic engineering. This position will be available as of September 2022 or upon agreement.