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Description
We are seeking a PhD researcher for a 4-year contract in a multidisciplinary research project to improve the safety of bicyclists and automated vehicles. Transportation of the future will include a mixture of automated vehicles (AVs) and vulnerable road users (VRUs), like bicyclists and pedestrians. Unregulated mixing of automated vehicles into urban areas has the potential to cause a rise in transportation related death and injury. This mixing also exacerbates safety concerns for vulnerable road users. Current VRU detection and its associated trajectory planning are based on information that is collected solely from AV sensors which is not sufficient to accurately predict the near-future behavior of vulnerable road users. We want to validate the hypothesis that digital information sharing among all road users combined with physiologically and dynamically realistic predictive models can guarantee overall safety. Our project goal is to achieve safe and socially acceptable interactions among automated vehicles and vulnerable bicyclists in dense urban environments by leveraging information shared in a two-way vehicle↔bicycle (V2B/B2V) communication system.
One portion of this project involves the development of neuromusular derived control models of bicyclists during traffic maneuvers.
You will be supervised by Dr. Jason K. Moore, Dr. Azita Dabiri, Dr. Frederik Schulte, and Dr. Ir. Riender Happee. You will work with BSc, MSc, and PhD candidates in the involved research groups that span the BioMechanical Engineering, Cognitive Robotics, Delft Center for Systems and Control, and Maritime and Transport Technology departments. Specifically, the PhD candidate will have the opportunity to collaborate with others for human in the loop evaluation in terms of acceptance and perceived safety.
Opportunities for growing your academic career will be available, such as mentoring BSc/MSc Students, conference presentations, networking, and teaching.
We are looking for candidates that can start during the summer of 2022.
Requirements
You should have:
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.
To Apply
Submit:
Visit TU Delft's website to find more employment details and apply for the position (vacancy number: TUD02119):
Applications Due April 14, 2022
Additional information
For more information about this vacancy, please contact Jason Moore, email: j.k.moore@tudelft.nl.
For information about the selection procedure, please contact Anita van Vianen, HR Advisor, email: application-3mE@tudelft.nl.
We are seeking a PhD researcher for a 4-year contract in a multidisciplinary research project to improve the safety of bicyclists and automated vehicles. Transportation of the future will include a mixture of automated vehicles (AVs) and vulnerable road users (VRUs), like bicyclists and pedestrians. Unregulated mixing of automated vehicles into urban areas has the potential to cause a rise in transportation related death and injury. This mixing also exacerbates safety concerns for vulnerable road users. Current VRU detection and its associated trajectory planning are based on information that is collected solely from AV sensors which is not sufficient to accurately predict the near-future behavior of vulnerable road users. We want to validate the hypothesis that digital information sharing among all road users combined with physiologically and dynamically realistic predictive models can guarantee overall safety. Our project goal is to achieve safe and socially acceptable interactions among automated vehicles and vulnerable bicyclists in dense urban environments by leveraging information shared in a two-way vehicle↔bicycle (V2B/B2V) communication system.
One portion of this project involves the development of neuromusular derived control models of bicyclists during traffic maneuvers.
You will be supervised by Dr. Jason K. Moore, Dr. Azita Dabiri, Dr. Frederik Schulte, and Dr. Ir. Riender Happee. You will work with BSc, MSc, and PhD candidates in the involved research groups that span the BioMechanical Engineering, Cognitive Robotics, Delft Center for Systems and Control, and Maritime and Transport Technology departments. Specifically, the PhD candidate will have the opportunity to collaborate with others for human in the loop evaluation in terms of acceptance and perceived safety.
Opportunities for growing your academic career will be available, such as mentoring BSc/MSc Students, conference presentations, networking, and teaching.
We are looking for candidates that can start during the summer of 2022.
Requirements
You should have:
- MSc in engineering or similar discipline by the start date of the position
- Experience with simulation
- Experience with a programming language (e.g., Python, Java, Matlab, etc.)
- Good written and oral communication skills in English
- Thriving in multidisciplinary environments
- Self-motivation
- Curiosity-driven working attitude
- Knowledge of control theory, transportation systems, machine learning, or vehicle dynamics
- Prior experience with SUMO (https://www.eclipse.org/sumo/)
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.
To Apply
Submit:
- Motivation and CV.
- A 1-page original research proposal with your ideas for addressing the problems described in the description.
- Abstract of your MSc thesis
- Contact information for up to 3 references
- List of grades
Visit TU Delft's website to find more employment details and apply for the position (vacancy number: TUD02119):
Applications Due April 14, 2022
Additional information
For more information about this vacancy, please contact Jason Moore, email: j.k.moore@tudelft.nl.
For information about the selection procedure, please contact Anita van Vianen, HR Advisor, email: application-3mE@tudelft.nl.