All Things Urban

As one of the world’s leading training grounds for these engineers, TU Delft views its role in society as supplying technological solutions that take us significantly further along the road towards sustainability and a flourishing economy.

The Faculty of Civil Engineering and 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. The research covers global social issues and is closely connected to education as well as the work of a wide range of knowledge institutions. CEG is convinced that Open Science helps to realise these goals 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. TU Delft was ranked the first in the Shanghai ranking on Transportation science & Technology in 2017. The Transport and Planning Department (T&P) at the faculty of Civil Engineering and Geosciences (CiTG) has been awarded the maximum score for all research assessments for the last 15 years. The faculty was ranked 4th place in the latest QS world university ranking. T&P (with about 120 members) has a strong track record in traffic flow theory, traffic simulation, dynamic traffic management and intelligent transport systems of all transport modes, including railway, pedestrians and urban public transport. A trademark of the department is the use of empirical data, incorporating human factors and advanced modelling tools. This PhD studentship is part of the SAMEN project funded by the Netherlands Organisation for Scientific Research (NWO). The project ‘Safe and efficient operation of AutoMated and human drivEN vehicles in mixed traffic (SAMEN)’ is open for 2 PhD candidate positions and 1 postdoc. The gradual deployment of Automated Vehicles (AV) in traffic will result in a transition period, in which vehicles with various levels of automation and Human Driven Vehicles (HDV) co-exist. As a consequence, new types of interactions will emerge between vehicles at different levels of automation. Proper understanding of how human drivers will respond to AVs, and how AVs could interact with HDVs rather than responding to them is urgent but lacking. This lack of understanding may result in unsafe and inefficient traffic situations. The unique aspect and aim of this project is its focus on understanding and modelling the interactions between human-driven and automated vehicles based on empirical data. In this project behavioural theories and models will be developed and validated for the interactions between AVs and HDVs using a hybrid approach for data collection. We will underpin the behavioural theory using empirical data that we will collect from field tests using AVs. We will use advanced interactive driving simulators to study the interactions between AVs and HDVs. We will scale up the resulting interaction models in a dedicated traffic flow simulation platform to evaluate the implications of mixed traffic on traffic flow and safety. In this project several industrial partners, vehicle manufacturer, road authorities, and knowledge institutes are involved.

The operational design domain is defined as the operating conditions under which a given driving automation system or feature thereof is specifically designed to function. To increase AVs capabilities we need to understand how to expand their operational design domain considering their interaction with the infrastructure, as well as, with other vehicles in complex traffic situations. The main objectives of this PhD position are to: (1) to develop accurate and reliable algorithms for infrastructure and traffic conditions features’ extraction, recognition and prediction using data driven approach; (2) to examine and evaluate the implications of different driving strategies and driving styles of AVs on human-drivers’ behaviour of nearby vehicles. In this part of the project you will collect and use data from driving simulators as well as from field tests. You are expected to collaborate with vehicle manufacturers.

Requirements for the PhD position: MSc in Computer science and/or applied mathematics. Skills required: good analytical skills, image-processing and computer-vision, working with big data, good communication skills, open minded, team player, and excellent English level (speaking, reading, and writing).

The duration of the PhD position will be for four years (48 months). As a PhD you will enrol in the CEG Graduate School and have as well the opportunity to join the TRAIL Research School. Both platforms provide a stimulating research environment and an ample support during your PhD. The project will commence in the Autumn of 2019. TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The minimum salary is your salary in your first year. The salary mentioned as the maximum will be your salary in your fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills.

2325 - 2972 EUR (full-time basis)

This job is available for international candidates.