Researcher Scenario Based Assessment methodologies | Helmond

Automated Vehicles (AVs) have gained widespread popularity in recent years due to their potential to deliver several benefits, including enhanced road safety, improved traffic throughput, and increased fuel efficiency. Realizing these advantages requires assurance that AVs genuinely enhance safety. A well-established methodology for assessing the safety of AVs involves a scenario-based approach, wherein an AV is tested across a diverse range of traffic scenarios. TNO has conducted extensive research in this scenario-based assessment approach. TNO’s StreetWise program focusses on scenario-based assessment where the scenarios that are used for testing are based on traffic scenarios collected from real-world data. By leveraging this collected data, statistical analyses of encountered scenarios can be conducted. These statistical insights, when combined with simulation studies of an AV, enable the estimation of AV safety levels. TNO’s ambition is to advance research in scenario-based assessment, ensuring that the introduction of AVs on roads indeed contributes to an overall improvement in safety. To that extent, we foresee the development of an improved approach for scenario-based safety assessment, which includes identification of representative scenarios and a further analysis, and solutions for dealing with unforeseen situations that are also critical. This approach should build on the current state of the art and offer scientific advancement of the domain.

We are seeking a researcher who will study how the quality of (test) scenarios can be substantially improved, thereby contributing to the safety of AVs and, ultimately, safe traffic for all. More specifically, the research focusses on several interacting topics:

• Quality of scenario statistics: Define metrics for assessing the quality of scenarios and scenario databases. This involves determining how to estimate scenario exposure, evaluating the diversity of scenarios within a database, and measuring the extent to which a set of scenarios covers specific areas.
• Framework for merging scenario statistics from various sources: Address the challenge of integrating traffic data from various locations and diverse sources, including vehicle sensors, roadside sensors, and accident data. Develop a framework capable of merging data sets with distinct characteristics, such as those with continuous data or those that only contain certain annotated parts.
• Bias and uncertainty effects on risk quantification: Investigate the bias and uncertainty introduced in a data-driven, scenario-based framework for risk quantification. Factors contributing to this bias and uncertainty include limited data, mismatches between collected data and the intended AV operating domain, data noise, scenario characterization, and simulation inaccuracies. Further research is required to characterize these sources of bias and uncertainty in quantifying risk of an AV.
• Complex scenario space: Explore the complexity of the scenario space for data-driven, scenario-based AV assessment. It does not suffice to only use collected scenarios for testing because it must be verified that an AV can also handle scenarios that have not been previously observed. More research is needed to characterize the complexity of all (reasonably foreseeable) scenarios.

You will be part of TNO’s StreetWise team, which is an international team with diverse expertise. You will engage in innovative research on the aforementioned topics in close contact with the team as your research will be directly applied in order to contribute to real-world impact.

We are seeking a researcher with the willingness to consider a potential PhD on the aforementioned topics within TNO. It is expected that you present your work at conferences and publish in journals.

• You have a master's degree in data science, applied mathematics, AI, computer science, transportation science, or a related field.
• You have experience and are proficient with programming in Python.
• You are familiar with statistical concepts relevant to data science.
• You are eager to learn more about your research topic and keep yourself up to date with the latest developments by actively engaging with recent literature.
• You can be in the office in Helmond for a minimum of 2 days per week on average.
• You can articulate your work clearly to your colleagues, which will help with collaborating with colleagues.
• You have mature writing and presentation skills in English, enabling you to author papers and to present your work at conferences.
• You can work effectively in a team setting, collaborating with colleagues and external partners.

Challenging and varied work with a real impact. And plenty of opportunities as, at TNO, you are in charge of shaping your career. We offer a gross monthly salary between € 3.340,- and € 5.600,- (based on your knowledge and experience), 8% holiday pay, a 13th month bonus of 8.33% and a flex budget (5.58% + € 180). In addition, you will be given every opportunity to develop yourself.

TNO offers optional employee benefits, enabling you to tailor your benefits package to match your personal situation. You may also expect:

• An extremely professional, innovative working environment where colleagues are leading experts in their field.
• The opportunity to attend courses, workshops and conferences, and to receive training and coaching based on your needs.
• 33 days annual leave on a full-time basis.
• An employer that values and encourages diverse talent, with initiatives like the Female Leadership Program, our Rainbow Community and round tables on inclusion topics.
• We offer a comprehensive and flexible mobility plan that also includes full compensation for public transportation for commuting and business travel.
• Great social events with your team and other TNO colleagues. That’s how you will get to know a lot of people really quickly.
• Flexible working hours, the possibility to work parttime (32 of 36 hours) and the possibility of working from home.
• Extensive relocation package for international candidates.
• A good pension scheme.

Read more about tailoring your benefits package.

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world. Read more about TNO as an employer.

At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society. Want to know more? Read what steps we are taking in the area of diversity and inclusion.

Please apply before the 24th of November, 2024. The selection process comprises two interview rounds. In a final meeting we will discuss the terms of employment and your tailored benefits package. We aim to finalize the entire process within four weeks.

The selection process may include an online assessment and a reference check.

A certificate of Conduct (VOG) is required before starting a new job at TNO.