More than 1,350,000 people die in traffic every year. Automated vehicles (AVs) are expected to improve road safety. However, a challenge is that future traffic will be mixed, with AVs, vulnerable road users (VRUs), such as pedestrians and cyclists and motorcyclists, and manually-driven cars sharing the roads and pursuing conflicting interests. Also, AVs will have different forms, differing in capabilities, driving speed, operational design domain (ODD) and technological capabilities. Also, some vehicles may be privately owned, offering the driver to sometimes drive in AV-mode, or maybe another form of automated transport, such as robotaxis or automated shuttles, where the user is not the owner.

It is not clear how AVs can assess VRU's situation awareness (SA). According to the theory of Distributed Situation Awareness (DSA), safety arises through shared knowledge of the collective. However, no mechanism exists for assessing DSA in complex traffic, as DSA misses multidirectional information exchange between multiple agents, and the theory has not been tested in complex and connected traffic. Also, current empirical research on AV-VRU interactions focuses on either sending or receiving data, instead of multidirectional exchange. It is unknown how an AV should adapt to the knowledge provided by multiple vehicles and VRUs with different SA.

The aim of this PhD project will be to update DSA with the multidirectional exchange between multiple agents. A computational system will be developed to intelligently decide how to distribute SA. Together with other colleagues in the Future Everyday group of Industrial Design, you will explore how multiple AVs can communicate with multiple other road users (includingVRUs) and investigate how AVs can ensure that the conveyed information is compatible with the behaviour of other road users.

You will develop further the coupled simulator for human factors research (https://github.com/bazilinskyy/coupled-sim). With help of the simulator, the candidate will conduct experiments, where multiple participants will meet and interact in the same virtual world. Through simulator and on-road experiments, the candidate will investigate how AVs can assess road users' SA from movements and posture, communicated through connected portable sensors (equipped on AVs, cars and VRUs) and explore mechanisms of assessing SA.

The results of the project will be used by automotive manufacturers and governments to coordinate the actions of future traffic participants. There will be close interaction with other researchers at the Department of Industrial Design and with the industry. There will be opportunities to conduct joint experiments with other PhD candidates. The candidate will work very closely with Dr. Bazilinskyy, who has a background in Computer Science and Human Factors. It is a challenging technical project that promises to revolutionise the field of Human Factors of automated driving. If you're an ambitious person who's not afraid of tackling a complicated challenge, this is the project for you!

The department of industrial design of the TU/e is looking to hire a candidate with expertise in software development and AI, and strong motivation to work in the domain of human factors of automated driving. The candidate should have (and will develop further in this project) strong professional and communication skills in order to work together with partners in a multi-national and multi-disciplinary research team. The following lists additional requirements.

The candidate has:

• Experience with Unity and C.
• Experience with the design and development of multiplayer games and/or multi-agent simulations.
• Experience with IoT.
• Experience with the development of complex IT projects.
• Completed a Master's in Computer Science, Human-Computer Interaction Transportation, AI or has a mixed educational background.
• Desire to share gathered knowledge with society through peer-reviewed journal and conference publications.
• Willingness to practise the principles of open science, keep code open-source, and share all (anonymised) data.
• Excellent communication skills, including a fluent command of English. Knowledge of Dutch is welcomed, but not strictly required.

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities.
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.