30 credits – Safe Configurable Maps for Off-Road Sites

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 control-tower operated work sites will soon become reality. 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. High definition maps help autonomous trucks to localize themselves and navigate in the surrounding environment. As opposed to the majority of public roads, off-road work sites tend to reshape frequently, which brings about the need for configurable maps. The site map needs to support a range of different updates for efficient operation, while also ensuring safety.

Target
Analysis of prerequisites and consequences for dynamically updating maps that guide autonomous vehicles in off-road sites

Assignment
To propose a method that supports map updates that are common in off-road site scenarios and analyze the prerequisites and consequences of the required updates to ensure safety. Preferably, a prototype solution should also be implemented and evaluated.

Education
Master (civilingenjör) in computer science, electrical engineering, mechatronics, or similar.
Number of students: 1-2 students
Start date: January 2019
Estimated time needed: 20 weeks

Contact persons and supervisors
Kathrin Rosvall, Development Engineer Autonomous Perception, 08 – 553 500 23,