PhD scholarship in Micro-Mobility Safety

Friday 01 Jul 22

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DTU Management’s Transport Division would like to invite applications for a 3-year PhD position starting on 1 January 2023 or earlier. The successful candidate will join the Transport Demand Modelling Group and will work under the supervision of Professor Jeppe Rich.

We are looking for excellent applicants with an MSc background from Computer Science, Transportation, Applied Mathematics, Statistics or related, and with the interest and ambition to carry out a PhD study.

The successful applicant will work on research focused on investigating perceived and actual safety of micro-mobility transport modes and the influence of safety on the demand for micro-mobility modes.

This position is funded under DTU’s strategic alliance with the five Nordic technical Universities (Nordic Five Tech) about funding and exchange of PhD students. This study will be carried out in collaboration with Professor Marco Dozza from the Chalmers University, Sweden, who will co-supervise and host the PhD student’s six month stay at Chalmers University.

Background
Micro-mobility transport modes such as bicycles and e-scooters are gaining interest in transport and urban planning. However, micro-mobility modes are involved in an increasing number of crashes with consequences for society and people. Moreover, many crashes are never reported to the police or hospitals. This makes it difficult to identify the factors (e.g., infrastructure design, surface quality, socio-economic variables, and weather) that may be associated with bicycles and e-scooter crashes.

The PhD project will use advanced tracking equipment and software to monitor a fleet of bicycles and e-scooters over time to identify crashes and near crashes. In addition, the space-time data collection will be combined with tailored survey questionnaires distributed to bicyclists to also explore perceived safety concerns. Such concerns may prevent people and especially school children of using the bicycle in environments which are perceived to be unsafe. This represents a situation with a potential underlying demand for bicycling which may not be exploited due to safety concerns. 

The PhD project will be conducted in collaboration with Chalmers University which will run a parallel project with focus on e-scooters. The focus of both projects is to leverage state-of-art tracking technologies to get insight into micro-mobility in use. The data analysis will utilize methods from simulation and mathematical modelling to understand and generalize results. The study will also apply state-of-the-art survey questionnaires to understand the underlying behavioral issues and causes for such behavior. In this context, the study will consider crashes from a multi-faceted perspective which includes observed crashes, perceived crashes, and near crashes.

Specifically, the project will address the following research topics:

  • Data-driven modelling of crashes and near crashes to understand the link between risk and context.
  • Importance and degree of perceived safety compared to observed safety. How much micro-mobility demand is suppressed due to perceived safety concerns and which segments are mostly affected?
  • Linkage between surface quality/smoothness and crashes as well as travel speed and accessibility.
  • The societal welfare effect from improved infrastructure and suggestions with respect to infrastructure prioritization schemes.
  • Identification of focus areas from a planning perspective with the aim of improving safety for micro-mobility modes.
  • Socio-economic risk profiling of subgroups which are most prone to crashes.
  • Comparison of risk-profiles between e-scooters and bicycles.
  • Use of methods from data science to extract information from high-frequency accelerometer data.
  • Linkage between all types of crashes and other external factors such as bicycle type, weather, slope, urbanization, and time of year.

The impact of the project has the potential to be huge as it may point to novel ways of designing our micro-mobility network and ways to prioritize the way we invest in infrastructure locally. This might help increasing the bicycle use, which may induce significant health effects in the long run.

Overall, the research lies in the intersection between transport safety, infrastructure design and transport and data modelling. The project will be anchored in the Transport Demand Modelling Group of the Transport Division of the Department of Management at the Technical University of Denmark (DTU). The project will be supervised by Professor Jeppe Rich and co-supervised by Marco Dozza from the University of Chalmers to establish a link between the tracking of e-scooters and bicycles.

We are looking for an excellent applicant to join the Division, starting on 1 January 2023 or earlier.

Qualifications for our new PhD student
The following qualifications are required for the position:

  • MSc degree (120 ECTS points) in Transportation Modelling, Quantitative Traffic Safety, Computer Science, Applied Mathematics and Statistics or related;
  • Programming capabilities in at least one scientific language (preferably Python);
  • Good background in statistics and in data-science;

The following skills are also desirable or important:

  • Transportation Modelling disciplines in the education background;
  • Knowledge about traffic safety;
  • Experience with Machine Learning techniques;
  • Curiosity and interest about current and future mobility challenges and EV charging in particular;
  • Good communication skills in both written and oral English;
  • Willingness to engage in group-work with a multi-national team.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education

Assessment
The assessment of the applicants will be made by 15 September 2022.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.


Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about career paths at DTU here.

Further information
For more information, please contact Prof. Jeppe Rich, rich@dtu.dk.

You can read more about the DTU Management at www.man.dtu.dk/english

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than 1 September 2022 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

The Transport modelling group belongs to the Transport division of the Department of Technology, Management and Economics (DTU Management) at DTU. The division conducts research and teaching in the field of traffic and transport planning, with a particular focus on behavior modelling, machine learning and simulation.

DTU Management conducts high-level research and teaching with a focus on sustainability, transport, innovation, and management science. Our goal is to create knowledge about the societal aspects of technology - including the interaction between technology and sustainability, business growth, infrastructure, and prosperity. Therefore, we explore and create value in the areas of management science, innovation and design thinking, business analytics, systems and risk analyses, human behavior, regulation, and policy analysis. The department offers teaching from introductory to advanced courses/projects at BSc, MSc, and PhD level. The Department has a staff of app. 350.

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