Junior Researcher in Modelling Autonomous Mobility-on-Demand Systems

Help shape the next generation of urban traffic models by developing parsimonious, multi-modal frameworks for autonomous mobility-on-demand. Join TU Delft and develop advanced traffic models!

Junior Researcher in Modelling Autonomous Mobility-on-Demand Systems

Job description

Emerging technologies have enabled new solutions and services for urban travel, including on-demand for-hire vehicles (e.g., Uber, Lyft) and connected and automated vehicles, which are increasingly part of the urban landscape. To design effective policy and management strategies, it is essential to understand how these emerging mobility systems interact with traditional transportation modes, such as buses and privately owned vehicles. This requires traffic models that can realistically describe multi-modal dynamics and support the evaluation of congestion, empty mileage, and the distribution of costs and externalities.

In this position, you will work on the development of advanced multi-modal traffic flow models that explicitly incorporate Autonomous Mobility-on-Demand (AMoD) services. You will build on so-called bathtub models, which are network-level macroscopic traffic models that abstract the whole network as a reservoir with a capacity that represents the maximal outflow. These bathtub models, also known as macroscopic fundamental diagram (MFD)-based models, can capture aggregate congestion evolution in the network efficiently. You will work on the extension of these bathtub models to represent interactions between demand, congestion, routing decisions, and AMoD operations.

Your main objective will be to extend existing macroscopic traffic models towards a multi-modal framework that captures:

• Dynamic mode choice and departure-time choice, and
• Mode-specific, congestion-dependent trip distances that evolve over time.

These extensions will enable the modelling of within-day detours as well as day-to-day equilibration processes in urban traffic systems.

To achieve this, you may develop an agent-based (trip-based) simulation framework that incorporates the impact of AMoD operations on dynamic trip distances and mode choice or, depending on your background and interests, explore analytical and numerical solutions using partial differential equation (PDE) formulations. Your work will connect theoretical modelling with computational implementation. You will collaborate closely with fellow researchers in the project who will analyse how demand patterns and network characteristics shape shortest-path trip distance distributions, which you will use as inputs for your modelling framework. The position also offers the opportunity to interact with industrial partners, including Haskoning, and to contribute to scientific publications.

This position is embedded in the Transport & Planning department at TU Delft. Research at T&P is conducted across a multitude of relevant research themes, organized via collaborative labs. You will join the hEAT lab whose mission is to develop innovative and sustainable solutions to challenges involving electric and automated transport systems at different spatial and temporal scales. You will work in a collaborative and international team that encourages you to develop your skills, expand your network, and grow in your career.

Job requirements

We are looking for a motivated and curious candidate who enjoys working on analytical and computational problems in an international research environment. You have:

• A MSc degree in Transportation Engineering, Civil Engineering, Applied Mathematics, Computer Science, or a closely related field.
• Basic knowledge of traffic flow theory and/or choice modelling (e.g., logit models)
• Analytical skills and experience with numerical modelling and/or simulation.
• Good programming skills (e.g., Python).
• Fluent communication skills both spoken and written in English.

Nice-to-haves (one or more of the following):

• Experience or interest in bathtub models, network fundamental diagrams, or macroscopic traffic flow theory.
• Familiarity with mode choice, departure time choice, or equilibrium modelling.
• Experience with agent-based models or PDE-based formulations.
• Experience with or interest in transport simulation tools (e.g. Aimsun, Omnitrans, or similar).
• Interest in shared mobility, on-demand mobility, automated vehicles, and sustainable transport systems.

If you are interested in this topic and you already have a PhD, you may consider applying for the postdoctoral position.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

Faculty of Civil Engineering and Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Conditions of employment

• Duration of contract is 16 - 18 months. Temporary.
• A salary based on Scale 10 of the CAO for Dutch Universities with a salary between €3546 - €5538 gross per month based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%. Salary will be aligned with the candidate's experience and expertise and in line with our internal salary framework.
• An excellent pension scheme via the ABP.
• The possibility to compile an individual employment package every year.
• Discount with health insurers on supplemental packages.
• Flexible working week.
• Every year, 232 leave hours (at 38 hours). You can also sell or buy additional leave hours via the individual choice budget.
• Plenty of opportunities for education, training and courses.
• Partially paid parental leave
• Attention for working healthy and energetically with the vitality program.

Additional information

For more information about this vacancy, please contact Irene Martínez Josemaría (I.Martinez@tudelft.nl).