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Master Thesis - Error Modeling for Vehicle Model Validation

Background of thesis project
The future of vehicle automation heavily relies on vehicle simulations for the upbringing of different autonomous applications, whether it is related to path planning, motion planning or control. The backbone of vehicle simulations is a vehicle model upon which the application is tested. Since the development happens at different stages, there is a need of different vehicle model fidelities.
High fidelity models are generally used for off-line simulations and in fast computing rigs where the high fidelity model tries to mimic as much as possible the dynamics and physics of a real truck. High fidelity models are verified against measured data and used as a reference for simpler, low fidelity model verification.

Project Aim
The aim of this thesis proposal is to develop a process to validate high-fidelity models based on real test data collected in Volvo automation projects. The focus will be on a statistical data driven approach for model validation where we can answer questions related to the quantity and quality of the data collected in relation to the validity of the high-fidelity model developed at V.A.S now. Those efforts are crucial for the development of both the validation techniques as well as the vehicle models used at V.A.S.

The complete picture can be depicted as:
Given a vehicle model, and for specific maneuver, provide a procedure for:
1. Set quality requirements for test data. Break down maneuver and perform required tests.
2. Construct error model for vehicle model.
3. Validate vehicle model + error model.

Thesis Scope
The proposed validation process is intended for high fidelity vehicle models that are used for simulation purposes, such as safety assessments, control verification, software integration. This thesis will focus on the second step of the project aim on the topic of constructing error models for the purpose of vehicle model validation.

Suitable background
Talented master students in Automotive, Mechatronics, Mathematics, Computer Science or Data Science, with some knowledge of Python or similar programming skills.
Please provide CV & transcript.

Thesis Level: Master

Language: English

Starting date: January 10, 2022 (flexible)

Number of students: 1 or 2

Tutor
Academic supervisor: Hans-Martin Heyn, +46 313222111
Industrial supervisors: Mohamed Takkoush, +46 313237590 and Rikard Wadman, +46 313229250
Examiner: TBA

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Volvo Autonomous Solutions constitute a new business area as of January 1, 2020, entering new and exciting territories for Volvo Group. We accelerate the development, commercialization and sales of autonomous transport solutions, focusing on defined segments for the on- and off-road space. The combination of strong tech expertise and skilled customer solutions creates innovative transport offers never seen before. We are constantly pushing our own skills and ability to drive change in a traditional industry to meet a growing customer demand. We are now looking for innovative, committed individuals to join us in our endeavor to create customer solutions that enhance safety, flexibility and productivity.

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