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Digitalisation and automation provide huge potential to increase performance and reduce costs of railway transport, and thus enhance its strengths in future sustainable mobility. In particular, Automatic Train Operation (ATO) is applied in many metro systems around the world to achieve high frequencies. Also for mainline railway networks it is expected that ATO will contribute to increased capacity, punctuality and energy savings. However, its performance depends on the quality of the timetable and the connection to a traffic management system (TMS) that may adjust the timetable considering disturbances. Hence, a TMS should interact seamlessly with ATO, which are complementary systems. The TMS adjusts the timetable in case of disturbances and delays focusing on optimal track capacity allocation of the railway traffic on the network level. On the other hand, ATO regulates the trains by computing feasible and energy-efficient speed trajectories over the assigned routes within the margins contained in the real-time timetable. These margins must be distributed to the various trains in so-called train path envelopes, which may contain both target times and time windows at successive timing points to offer sufficient flexibility while guaranteeing conflict-free and punctual train operation. The interaction should lead to a balanced usage of ATO train-centric optimisation, complying with the network optimisation of the TMS.
In this PhD project you will develop methodology and algorithms to achieve optimal interaction between TMS and ATO for optimised railway operations. In particular, (1) you will develop models and algorithms for dynamically optimizing real-time timetables and train path envelopes considering operational and signalling (ETCS) constraints and multiple objectives of capacity, punctuality and energy consumption in both normal and disturbed operations. (2) You will investigate the potential of dynamic feedback loops between the TMS and ATO, such as actual train positions and predicted train trajectories from the ATO on-board algorithms. (3) You will analyse the impact of different levels of decentralisation of both traffic management and ATO trackside areas. (4) You will assess the developed algorithms using microscopic railway operation simulation.
This PhD research will use mathematical optimization, control and simulation in a railway context. The research is funded by the Dutch rail infrastructure manager ProRail and will be carried out in the Digital Rail Traffic Lab of the Department of Transport and Planning at Delft University of Technology under the supervision of Prof. Rob Goverde and Dr. Egidio Quaglietta in close collaboration with ProRail. The research is part of Europe’s Rail project MOTIONAL. You will therefore also collaborate with international partners within this European project.
You satisfy the following profile:
If your mother language is not English and you do not hold a degree from an institution in which English is the language of instruction, you must submit proof of English proficiency from either TOEFL (minimum total score of 100) or IELTS (minimum total score of 7.0). Proof of English language proficiency certificates older than two years are not accepted.
Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.
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 € 2541 per month in the first year to € 3247 in the fourth year. 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
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.
At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
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.
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