Master Thesis - Using Generative AI to Analyse Logged Vehicle Data
Volvo Business Services AB / Elektronikjobb / Göteborg
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hela Sverige Thesis Background
Electrification of road transport is a key element in delivering the Green Deal, for a carbon neutral Europe and ultimately a carbon neutral world. Using hydrogen as a carrier of green electricity to power electric trucks in long-haul operations is one important part of the puzzle, and a complement to battery electric vehicles and other renewable fuels.
At Volvo's Powertrain Strategic Development, we shape technology strategies and inform business decisions for new powertrain solutions. We probe emerging powertrain tech, legal shifts, and future societal needs to prepare a powertrain roadmap. In addition, we also develop technology solutions, to support the transition from concept to production. In this context, the analysis of logged vehicle data, both during the development phase and from in-production vehicles, stands as a cornerstone of our data-driven approach, offering insights into vehicle performance, user behavior, and potential areas for innovation.
A potential shift in data analytics from traditional coding to employing Generative AI, where one simply poses a prompt to articulate desired outcomes, would be a monumental leap forward. Embracing Generative AI not only streamlines processes but also democratizes data analysis, making it more accessible to non-technical users. This paradigm shift underscores the transformative power of Generative AI, fostering a more intuitive, efficient, and dynamic approach to extracting insights from vast datasets.
Problem motivating the project
The evolution of modern commercial vehicles presents both opportunities and challenges. The sheer volume of data generated by the ECUs offers profound insights into vehicle performance and potential areas for enhancement. However, the intricacy of data analysis, as per current industry standards, has become a considerable bottleneck. This limitation restricts the broader team from fully leveraging these insights.
With this project, our ambition goes beyond merely simplifying data analytics. We're looking to pioneer a new era in data interpretation by utilizing the capabilities of Generative AI. Through an intuitive interaction with a Generative AI prompt, we envision a future where every team member, be it engineers or managers, can seamlessly access and understand the wealth of data our vehicles generate. By making data analytics universally accessible, we aim to cultivate a collaborative decision-making environment, thereby accelerating innovation and ensuring our commercial vehicles remain at the forefront of the industry.
Objective and Deliverables
Finetuning existing Large Language Models (LLMs) enable analysis and visualisation of logged vehicle data from both development phase
The tool should assist in extracting insights, through an intuitive Graphical User Interface (GUI)
Publication of a Master Thesis report, with presentations of findings at both the university and Volvo
Requirement on student background:
Master students in Engineering Physics, Data Science, Mathematics or relevant fields
Good Python programming skills
Any current experience of working with Generative Ai would be an added plus
Ability to drive the work forward by being proactive, curious, and persistent
Supervision and examination:
Powertrain Strategic Development, GTT, Volvo Group
Chalmers University of Technology
Thesis Level: Master
Language: English
Starting date: Spring 2024
Number of students: 2
Physical location: Mostly at Volvo Lundby (CampX).
Tutor:
Volvo contact person: Masoom Kumar (+46 76 553 40 75) & Parthav Desai (+46 73 902 59 02)
Academic supervisor: Morteza Haghir Chehreghani, Associate Professor, Dept. of Computer Science and Engineering (+46 31 772 64 15)
Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.
Så ansöker du Sista dag att ansöka är 2023-10-31
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Arbetsgivare Volvo Business Services AB (org.nr 556029-5197)
405 08 GÖTEBORG
Arbetsplats Volvo Group
Jobbnummer 8104030
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