Student mechanical engineering, automotive engineering or similar (f/m/x) - Virtual Analysis of Risk Assessment Methods Used in Autonomous Vehicles

Location

Stuttgart | Germany

Job description

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Course paper / final thesis

Virtual Analysis of Risk Assessment Methods Used in Autonomous Vehicles

Virtual Analysis of Risk Assessment Methods Used in Autonomous Vehicles

Starting date

1 February 2024

Duration of contract

6 months

Type of employment

Full-time (part-time possible)

Addressing the challenge of ensuring the safe performance of Autonomous Vehicles (AV) stands as a pivotal obstacle to the widespread adoption of this transformative technology. This research initiative encompasses a multifaceted approach aimed at understanding and enhancing the safety landscape of autonomous vehicles. Risk Assessment Methods (RAM) are techniques used by the AV to assess the risk within a given scene in a scenario and decide the best course of action. Currently, there are various RAMs that evaluate distinct risks, considering diverse sources in different scenarios. This project seeks to leverage simulation tools and software, utilising the driving simulator, CarMaker, to investigate and assess different RAMs.

The first objective of the work is to develop an overview of the state-of-the-art RAMs with a particular focus on a subset of methods that are applicable to similar scenarios or that assess the same risk. Subsequently, a select number of the investigated RAMs will be implemented into the driving simulator CarMaker. The aim of this step is to provide empirical evidence regarding the effectiveness and limitations of RAMs. Furthermore, the evaluation of the safety performance of each RAM will be conducted, scrutinising their ability to anticipate and respond to potential hazards in diverse driving scenarios. Through these systematic investigations, the project aims to contribute valuable insights to the refinement and selection of optimal RAMs, thereby advancing the safety and reliability of autonomous driving systems.

Content of the work:

• literature research on the safety of autonomous vehicles
• literature research on different risk assessment methods for autonomous vehicles
• implementation of RAM into a driving simulator (CarMaker)
• verification and validation of implemented method.
• analysis and comparison of the performance of different RAMs
• evaluation of the safety performance of each RAM
• identification of possible future development
• documentation of methodology and findings

• Bachelor’s degree in Mechanical, Automotive Engineering or similar
• proficiency in English
• good written and verbal communication skills
• ability to work as part of a team
• previous experience with a driving simulator (e.g. CarMaker) is advantageous
• previous coding experience (preferably C++/Python) is advantageous

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalleled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (f/m/x). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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