PhD Position Design and Control of Mixed Fixed-Flexible Transport Networks

Would you like to work at the intersection of transportation, robotics and machine learning to design mixed fixed-flexible transport networks?

PhD Position: Design and Control of Mixed Fixed-Flexible Transport Networks

The increase of public transport usage has clear potential in transforming our environment to be more liveable, sustainable and convenient. However, to ensure economic viability during off-peak times and in relatively remote locations, while increasing attractiveness to users, we need innovative designs where fixed and flexible services support each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning, and behavioral modeling methodologies.

In the FlexMobility project, we propose a holistic approach to designing a public transport network that includes both traditional fixed lines and flexible on-demand services, while considering the underlying travel behaviour. In the future, these mixed transportation systems may include fleets of autonomous cars, vans, and buses.

This PhD position within FlexMobility will focus on the underlying assignment and routing algorithms for real-time operation of the vehicle fleet and the multi-objective design of the mixed transportation network. Our key hypothesis is that it is possible to design a mixed network by simulating how to serve a given demand with an on-demand ridepooling service, tracking the vehicles’ routes, and allocating fixed lines wherever vehicles concentrate the most. For the implementation of the system, users will be allocated, in real time, to either the fixed lines or pooled on-demand vehicles. This requires efficient methods for large-scale task assignment and routing, leveraging combinatorial optimization and machine learning.

To achieve a holistic system, the developed methods will be enhanced with behavioral representations researched by another PhD candidate in the project. The developed methods could be applicable across many multi-agent coordination domains, from mobility, to logistics, and multi-robot systems.

In this work, we will consider two use cases:

• A mobility network considering both fixed-line buses and on-demand vehicles
• A network with water-taxis

For both use cases, there will be interaction with project partners for generating/obtaining the needed data as well as for setting up realistic case studies.

The position is available with a flexible start date to be agreed upon. The PhD candidate will join the Autonomous Multi-Robots Lab at the Cognitive Robotics Department and will be supervised by both Javier Alonso-Mora and Bilge Atasoy. Thanks to this synergetic collaboration, the PhD candidate will be able to collaborate with various researchers working on robotics and adaptive transport systems through methodologies of dynamic and predictive optimization, behavioral modeling, and machine learning. There is vivid interaction within the group to foster collaboration both with scientific and social activities.

As part of the PhD position, there will be opportunities to gain teaching experience in relevant courses and/or supervising MSc students.

More information about our research group can be found at: https://autonomousrobots.nl/.

Job Requirements

• Master of Science (MSc) diploma in Transportation, Robotics, Computer Science, Logistics, Operations Research, Industrial Engineering, Applied Maths, or any other related field.
• Knowledge in operations research, discrete planning, robotics, or machine learning, and an appreciation of the interaction between operations research and machine learning.
• Drive for excellence in research and the ability to work independently and as part of a team.
• Willingness to conduct multidisciplinary research in collaboration with both scientific and industrial partners.
• Excellent problem-solving and analytical skills.
• TOEFL or IELTS English proficiency tests for all applicants except those graduated from an MSc program that was taught in English. The minimum requirement is a TOEFL score of 100 or IELTS of 7.0 per sub-skill (writing, reading, listening, speaking).

About 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 Mechanical Engineering

From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focus on fundamental understanding, design, production including application and product improvement, materials, processes, and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education, and (inter)national cooperation.

Conditions of Employment

• Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1.5-year contract with an official go/no go progress assessment within 15 months, followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met.
• Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from Promovendus gross per month, from the first year to the fourth year based on a full-time contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.
• As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff, and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related, and research skills.
• The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Additional Information

For more information about this vacancy, please contact Prof. J. Alonso-Mora at j.alonsomora@tudelft.nl.