30 credits – Sensor fusion architecture with respect to safety

Scania is now undergoing a transformation from being a supplier of trucks, buses and engines to a supplier of complete and sustainable transport solutions.

Ingress:

The Autonomous Vehicle Perception group at Scania develops key components sensor fusion, localization and mapping for autonomous trucks. A thesis project at the group and Scania is a great opportunity to work on the forefront of autonomous vehicle development and an excellent way of making contacts for your future working life.

Background:

Autonomous vehicle development is advancing at a very high pace and self-driving trucks on public roads will soon see the light of day. In the Autonomous Vehicle Perception group we develop cutting edge sensor fusion algorithms and high precision localization and mapping systems. Our systems are essential in enabling high level autonomy for the transportation systems of the future. It is critical that the perception is robust to failures off an individual sensor, the architecture and algorithms should never fail due to common errors.

Target:

To explore and investigate different approaches for algorithms, or architectures for safety critical sensor fusion.

Assignment:

To propose either an algorithm or architecture that could be suitable for the next generation of autonomous trucks with respect to safety and redundancy. The concept could be tested in a simulation environment or in real experiments.

Education:

Master (civilingenjör) in electrical engineering, physics, mechatronics, or similar, preferably with specialization in control, robotics, machine learning.

Number of students: 1-2 students

Start date: January 2019

Estimated time needed: 20 weeks

Contact persons and supervisors:

Hjalmar Lundin, Development Engineer Autonomous Perception,

08 – 553 512 73, Hjalmar.lundin@scania.com

Application:

Enclose CV, cover letter and transcript of records.

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