Recruitment

15 Early Stage Research (PhD) positions on Human Interaction with Automated Vehicles in Cities

Applications are invited for 15 Early Stage Research (ESR) positions in the European project SHAPE-IT: Supporting the interaction of Humans and Automated vehicles: Preparing for the Environment of Tomorrow. The positions will be funded by a European Commission Horizon 2020 program for research and innovation: Marie Skłodowska-Curie Action (MSCA) Innovative Training Network (ITN).

Candidates should have an MSc degree in psychology/behavioural sciences or an engineering discipline, with knowledge in one or more of the following fields: human factors, cognitive psychology, neuroscience, ergonomics, human-machine interfaces, cognitive modelling, artificial intelligence, machine learning, statistics, automotive technology, driver assistance systems, software engineering, computer science, control theory, transport modelling, and safety analysis.

Employment is expected to start between October 2019 and March 2020. The ESRs will be hired for a period sufficient to obtain a PhD degree at each respective host University (ranging from 36-54 months). All ESRs will work towards the PhD degree at their host institution, which will be assessed following a successful publication of their research in international journals, relevant to their field.

Candidates cannot hold a doctorate degree and should be within 4 years of obtaining their Master’s qualification (see point 2 of the Eligibility Criteria).

All ESRs are expected to undertake trans-national mobility (i.e. move from one country to another). Hence, candidates can only apply for positions in countries where they have stayed less than 12 months during the last 3 years (typically, that are away from their current country of residence; see point 3 of the Eligibility Criteria).

Project summary

The overall goal of this project is to enable rapid and reliable development of safe and user-centred automated vehicles (AVs) for urban environments. Vehicle automation has been identified as a game-changer in transport, promising substantial reductions in road-traffic fatalities while improving mobility. However, the processes to integrate automation in transport have been primarily technology-focussed, with insufficient consideration given to how users both inside and outside of the AVs will interact with AVs.

The main objective of SHAPE-IT is to facilitate the safe, acceptable (and, ideally, desirable) integration of user-centred and transparent AVs into tomorrow’s mixed urban traffic environments, using both existing and new research methods, designing advanced interfaces and control strategies.

This project spans three complementary facets of AV/human factors research:

  1. understanding the behaviour of different road-users (inside and outside AVs) when interacting with AVs, investigating cognitive processes, predictability, trust, acceptance and safe interaction following an initial, and long-term exposure to AVs;
  2. researching design strategies for the interfaces used for communication and interaction between AVs and humans (inside and outside AVs), and;
  3. integrating knowledge on human/AV interactions into models to perform prospective mixed traffic-AV safety assessments.

As Artificial Intelligence (AI) is a core technology for AV development, in this project, we will also seek to integrate knowledge of human factors with that of AI in AV development, reducing the gap between human-factors and AI scientists, and AV software developers.

The project aims to deliver a future generation of human factors researchers with an excellent multidisciplinary (cognitive and behavioural psychology, human factors, computer science, and engineering) education in human factors, experimental and modelling methods, human-AV interaction, human factors requirements for AI-based AVs, and safety analysis for AV design. All recruited ESRs will conduct 1-4 months long secondments with at least two of the associated partners of SHAPE-IT (based in industry, research institute or academia; see below).  

Participants in SHAPE-IT (hosts/employers of the ESRs)

Chalmers University of Technology (Sweden; project coordinator: jonas.bargman@chalmers.se)
University of Leeds (United Kingdom)
Delft University of Technology (The Netherlands)
Technical University Munich (Germany)
University of Gothenburg (Sweden)
Ulm University (Germany)

Associated Partners of SHAPE-IT (offering secondments):

Volvo Car Corporation (Sweden)
VW (Germany)
Veoneer (Sweden)
Toyota Motor Europe (Belgium)
Bosch (UK)
SWOV (The Netherlands)
Ludwig-Maximilians-Universität München (Germany)

The application procedure

A short description of each individual PhD/ESR’s project is provided below. This includes the objectives of each project, the expected candidate profile, and details of the main supervisor, and hosting organisation.   

Applications should be submitted for each individual ESR position you are interested in, either via the hyperlinks to the host universities recruitment web sites, when available below, or, when no hyperlink is provided, send your application to the host recruitment contact email.  You may apply to multiple positions. If we identify you as particularly interesting and suitable for one of the positions you have not applied for, we may forward your contact details to the corresponding host (pending your consent to do so), but direct application is recommended. Each application should include, your CV, and a motivation letter, highlighting your relevant experience, and your motivation for applying. The letter should be tailored to the individual positions you apply for. Note that submission requirements may differ between ESR hosts. 

We strongly encourage female candidates to apply for any of these multi-disciplinary research positions, where working together and sharing knowledge and experience across a diverse group of people is fundamental for reaching the project goals: building safe, usable and trusted vehicle automation for future cities.

Individual ESR project descriptions

ESR1: Understanding AV Predictability Using Neuroergonomics

Host institution: University of ULM
Objectives: This PhD Candidate will derive recommendations for driver-AV interaction strategies by improving the understanding of cognitive mechanisms of drivers’ predictions of AV behaviour. This understanding will be achieved by developing and using neurophysiological measurement in, for example, AV-driving simulator studies. 
Candidate profile: Psychologist or engineer with knowledge of and an interest in human factors.
Supervisor names (main/co): Prof Olga Pollatos (ULM) / Prof Martin Baumann (ULM)
Host recruitment contacts: olga.pollatos@uni-ulm.de; martin.baumann@uni-ulm.de

ESR2: Long-Term Effects of Automation Exposure on User Behaviour

Host institution: Technical University Munich
Objectives: This PhD candidate will use advanced driving simulators as a basis for improving understanding of how AV users’ experience, trust, and acceptance of AVs change with long-term/repeated use in urban traffic. An evaluation of AV interaction design strategies will be performed, and patterns of learning strategies of AV users (“drivers/passengers”) by user types will be established.
Candidate profile: Familiarity with and interest in human factors of automated vehicles, comfortable with studies with human participants. From engineering or psychology.
Supervisor names (main/co): Prof Klaus Bengler (TUM) / Prof Natasha Merat (Leeds)
Host recruitment contact: bengler@tum.de

ESR3: Classifying and Predicting Interactions Between AV and VRUs Using AI

Host institution: University of Gothenburg
Objectives: This PhD candidate will develop and evaluate methods from artificial intelligence (AI) such as machine learning (ML) to identify, classify, and predict behaviours of VRUs in interactions with cars (operated in manual and automated mode). Results will be used to predict VRU behaviour (including intent) in more complex interactions (e.g., VRUs crossing road and turning (left) in front of the manual/automated car).
Candidate profile: Knowledge/experience in applying ML methods to data-heavy problems. Experience with Python, C++, Linux. Preferably having experience with sensors and systems for automotive systems.
Supervisor names (main/co):  Dr Christian Berger (UGOT; christian.berger@gu.se) / Prof Marco Dozza (Chalmers)
Host recruitment page: Link

ESR4: Long-Term Effects of Automation Exposure on AV/VRU Interactions

Host institution: University of Leeds
Objectives: Using the state of the art facilities at Leeds, including the newly established HIKER lab this project will investigate how Vulnerable Road Users’ experience, trust, and acceptance of AVs change with long-term/repeated exposure to the vehicles, as their exposure to the AV increases in urban traffic. The work will also determine whether these effects are influenced by user characteristics such as gender, age and personality.  This project is a continuation of our work currently taking place in the interACT project and will investigate how different vehicle trajectories and externally presented Human Machine Interfaces affect long term behaviour and reactions of VRUs.
Candidate profile: familiarity with human factors of automated vehicles, comfortable with studies using human participants, good people skills, familiarity with (or interest in) conducting human-in-the-loop simulation studies, interest in understanding the impact of automated vehicles on society.
Supervisor names (main/co):  Prof Natasha Merat (Leeds) / Prof Klaus Bengler (TUM)
Host recruitment page: Link

ESR5: Developing more acceptable, pleasant and transparent AV-kinematic cues for drivers

Host institution: University of Leeds
Objectives: Understand whether human-like control models of driving are more acceptable and desirable for users of AVs. Use physiological and subjective measures to assess driver acceptance of different kinematic cues from the vehicle, considering how different driver characteristics may affect comfort, pleasure and acceptance. Assess how different road environments affect user preferences for different AV kinematic characteristics. Understand how kinematic cues can be used to provide transparent communication of AV capabilities and limitations. This PhD will be linked to the currently funded HumanDrive project.
Candidate profile: familiarity with human factors of automated vehicles, comfortable with studies using human participants, good people skills, familiarity with (or interest in) conducting human-in-the-loop simulation studies, interest in understanding the impact of automated vehicles on society. Interest or experience in using quantitative physiological measures such as heart rate and skin conductance, experience in using qualitative measures for assessing human subjective preferences.
Supervisor names (main/co): Prof Natasha Merat (Leeds) / Prof Marjan Hagenzieker (TU Delft)
Host recruitment page: Link

ESR6: Internal Interface for Transparent and Agile Automation

Host institution: University of Ulm
Objectives: Based on existing models and theories in cognitive psychology the PhD candidate will develop and validate a cognitive model of dynamic task sharing between driver and automation in complex urban traffic situations. Based on this model the PhD will develop driver-adaptive interaction strategies for dynamic task sharing considering effects of gender, age, and personality and validate these strategies in simulator studies. This will lead to descriptions of drivers’ information needs in complex urban traffic and a cognitive model of dynamic task sharing between AV and driver in complex urban traffic.
Candidate profile: Experience in traffic and cognitive psychology, experimental methods, driving simulation, basic programming skills, ideally some background in cognitive modelling; MSc in Psychology, or Cognitive Science or Human Factors or comparable.
Supervisor names (main/co):  Prof Martin Baumann (UULM) /  Prof Klaus Bengler (TUM)
Host recruitment contact:  martin.baumann@uni-ulm.de

ESR7: Assessing AV Transparency

Host institution: Technical University Munich
Objectives: This PhD candidate will develop and validate methods for assessing transparency of AVs, to answer the question, “How well does the AV convey its capabilities and intent to interacting humans?”. Specifically, the Wizard of Oz (WoZ) paradigm will be used and evaluated in the context of AV design and evaluation. Here, WoZ experiments include a human experimenter that simulates the behaviour of AV functionality that has not yet been implemented (or has limitations), having participants believe they are driving/riding in an AV with that functionality. Contributions to guidelines for achieving transparent in-vehicle AV interface strategies is expected.
Candidate profile: Psychologist or engineer with knowledge of and an interest in human factors.
Supervisor names (main/co): Prof Klaus Bengler (TUM) / Prof Martin Baumann (UULM)
Host recruitment contact: bengler@tum.de

ESR8: Human Factors in AI-based Automation Design

Host institution: University of Gothenburg
Objectives: This PhD candidate will be considering human factors from a software (AI development) requirement perspective, with the aim to understand and describe how AI-based AV design can account for human factors. Methods will be developed to incorporate results from studies on acceptance which will improve AI-based AV-designs, taking human behaviour into account.  Recommendations on what information should be communicated between AV human factors researchers and AI-based AV designers to improve road-user acceptance, AV transparency, and vehicle safety, will be produced.
Candidate profile: The candidate must have a background in software engineering and/or artificial intelligence. Good technical skills, practical programming skills, as well as good knowledge of the English Language (both oral and written) is required. The candidate must be interested in interacting in a multi-disciplinary team with other students and researchers from psychology, behavioral science, human factors and machine interface design, software engineering, and artificial intelligence.
Supervisor names (main/co):  Dr Eric Knauss (UGOT; eric.knauss@cse.gu.se ) / Dr Jonas Bärgman (Chalmers)
Host recruitment page: Link

ESR9: Assessing Interactions between AVs/VRUs using Virtual/Augmented Reality

Host institution: Delft University of Technology
Objectives: The PhD candidate will develop virtual reality (VR) and augmented reality (AR) methods to investigate the interaction between automated vehicles (AVs) and vulnerable road users (VRUs). Furthermore, he or she will develop and test external HMIs (eHMIs) that inform the VRU about the AV’s intentions. Accordingly, the candidate will advance knowledge about AV-VRU interaction on topics such as safety, expectancy, acceptance, and trust.
Candidate profile: Engineer with knowledge of human factors.
Supervisor names:  Dr.ir. Riender Happee (TU Delft; R.Happee@tudelft.nl) / Dr.ir. Joost de Winter (TU Delft; J.C.F.deWinter@tudelft.nl)
Host recruitment page: Link

ESR10: HMI on bicycles, promoting Transparent AV interactions

Host institution: Delft University of Technology
Objectives: The PhD candidate will examine how communication from AVs to bicyclists can be enhanced using on-bicycle human-machine interfaces (HMIs). He or she will establish what modalities are useful for the HMI, and how the HMI should interact with the bicyclist. Apart from direct AV-to-cyclist communication, the HMI will also incorporate communication from road infrastructure, such as traffic lights. The candidate will evaluate bicyclist’s safety, transparency of interactions, trust, and acceptance among different cycling groups. Experiments will be conducted in virtual environments and the real world.
Candidate profile: Psychologist or Engineer with knowledge of human factors.
Supervisor names:  Prof.dr. Marjan Hagenzieker (TU Delft; M.P.Hagenzieker@tudelft.nl) / Dr.ir. Joost de Winter (TU Delft; J.C.F.deWinter@tudelft.nl);
Host recruitment page: Link

ESR11: Cooperative Interaction Strategies Between AVs and Mixed Motorized Traffic

Host institution: University of Ulm
Objectives: The PhD candidate will focus on investigating the interaction between drivers in urban traffic situations. Based on the analysis of behavior in prototypical situations the PhD student will develop, analyze and test interaction and cooperation patterns using the state of the art driving simulators at Ulm University. Based on these results the PhD student will formulate recommendations for safe, efficient, and cooperative AV behavior in mixed urban traffic, resulting in a set of analyzed cooperation situations in complex urban traffic, and a set of validated cooperation patterns between drivers in complex urban traffic.
Candidate profile: Experience in traffic psychology, in experimental methods, driving simulation, basic programming skills. MSc in Psychology or Human Factors or comparable.
Supervisor names (main/co):  Prof Martin Baumann (UULM) / Dr Jonas Bärgman (Chalmers)
Host recruitment contact: martin.baumann@uni-ulm.de

ESR12: AV Occupants’ Perception of Safety in relation to AV behaviour

Host institution: Delft University of Technology
Objectives: The PhD candidate will develop models to predict perceived safety and trust in vehicle automation. The models will capture different levels of driver involvement, driving speeds, interaction with other road users, and infrastructure characteristics. Driving simulator and on-road experiments will be performed to systematically evaluate trust and perceived safety, in order to obtain the model parameters. Furthermore, he or she will investigate how trust and perceived safety can be enhanced by adapting the automated driving style and by informing occupants about the current and anticipated actions of the automated vehicle.
Candidate profile: Engineer with a focus on system dynamics and statistics, and an interest in human perception.
Supervisor names:  Dr.ir. Riender Happee (TU Delft; R.Happee@tudelft.nl) / Dr.ir. Meng Wang (TU Delft; M.Wang@tudelft.nl)
Host recruitment page: Link

ESR13: Computational AV/Pedestrian Interaction Models

Host institution: University of Leeds
Objectives: Building on existing experimental methods (e.g., virtual reality experiments) and models developed in the research group, the PhD candidate will investigate and model interactions between cars/AVs and pedestrians in selected situations. The PhD candidate will also apply these models in computer simulations to study how AVs should behave, taking pedestrian intentions and expectations into account. A specific research question of interest is how AVs can achieve efficient progress toward own goals, while at the same time not transgressing human comfort boundaries.
Candidate profile: Strong quantitative and programming skills, combined with an interest (or ideally formal training) in psychology / cognitive science / behavioural sciences.
Supervisor names (main/co):  Dr Gustav Markkula (Leeds) / Prof Marco Dozza (Chalmers)
Host recruitment page: Link

ESR14: Computational AV/Cyclist Interaction Models

Host institution: Chalmers University of Technology (Chalmers)
Objectives: Building on state-of-the-art methods for modelling human behaviour, this PhD candidate will investigate how cyclists communicate their intentions in traffic, and which cues they use to predict the behaviour of other road-users and to communicate their intent. This will include modelling cyclist behaviour, to enable AVs to predict cyclist intent, enabling AVs to meet human expectations and not transgressing human comfort boundaries.
Candidate skills: An engineer with an interest in human behaviour or a behaviour scientist, having good communication and programming skills. A background in mathematical modelling is beneficial
Supervisor names (main/co):  Prof Marco Dozza (Chalmers; marco.dozza@chalmers.se) / Dr Gustav Markkula (Leeds)
Host recruitment page: Link  

ESR15: Safety Evaluation of Automation Using Counterfactual Simulations

Host institution: Chalmers University of Technology (Chalmers)
Objectives: Based on previous research into safety assessment, this PhD candidate will develop, improve, and evaluate methods for virtual (simulation based) assessment of the crash risks associated with the combination of the AV driver, the AV, and VRUs interacting with the AV. It will include integrating models from other students in the project, and developing and using a Bayesian statistics framework to improve current assessment methods.
Candidate profile: An engineer with an interest in human behaviour, preferably having prior experience in mathematical simulation, and being comfortable with adopting new analysis techniques (e.g., in statistics).
Supervisor names (main/co):  Dr Jonas Bärgman (Chalmers; jonas.bargman@chalmers.se) / Dr András Balint (Chalmers; andras.balint@chalmers.se)
Host recruitment page: Link

Conditions

The Marie Skłodowska-Curie Action (MSCA) program offers attractive salary and working conditions, in accordance with the MSCA regulations for early stage researchers. All ESRs will participate in a wide-range of educational programmes, including secondments, summer schools, and project workshops. Each ESR will complete 2 or 3 secondments with the associated partners of SHAPE-IT (see list above), with each secondment lasting between 1 and 4 months. The specific rules, regulations and benefits of the programme are based on the specific host country offering the PhD position

Requirements and eligibility criteria

  1. English language: It is a requirement that fellows will be able to express themselves in English at a high level, both verbally and in writing (for example, for the UK, this includes an average score of 6.5 for IELTS).
  2. An early stage researcher (ESR) means a researcher who, at the time of recruitment by the beneficiary, has not yet been awarded a doctorate degree and is in the first 4 years (full-time equivalent[1]) of his/her research career (measured from the date when they obtained a Masters degree, which formally entitles them to embark on a doctorate).
  3. ESRs are required to undertake transnational mobility (i.e. move from one country to another). At the time of recruitment, the researcher must therefore not have resided or carried out their main activity (work, studies, etc…) in the country of the host institution for more than 12 months in the 3 years immediately prior to their recruitment under the project.
  4. A valid visa for research at the host’s country must be attained (the visa process will be handled by each host university).

[1] “As an example, a candidate who obtained their degree entitling them to embark on a doctorate five years ago and spent the equivalent of two years attending taught classes and three years gaining research experience is still eligible as ESR. They are considered to have three years’ research experience as the time enrolled in formal taught classes is not counted as research experience.” EC Marie Curie information