30 credits – Heuristics for vehicle motion planning with search trees

Scania genomgår nu en transformation från att vara en leverantör av lastbilar, bussar och motorer till en leverantör av kompletta och hållbara transportlösningar.

The Autonomous Vehicle Motion Planning and Control group at Scania develops the key components for local motion planning and control for our autonomous vehicles. A thesis project at the group and Scania is a great opportunity to work at the forefront of autonomous vehicle development, and an excellent way of making contacts for your future working life.


Motion planning is an essential part of the autonomous system, and aim to calculate trajectories for the vehicle to follow. These trajectories must meet the dynamical constraints of the vehicle, as well as the constraints from the surroundings. One approach to planning the path between a start point and a goal point is to use a Rapidly exploring random tree (RRT). These are extensively used, but one of their weaknesses is that they does not consider the cost of the complete path from start to goal. This often leads to paths that are longer than necessary and suffer from excessive steering. One possibility to improve the search is to use heuristics that biases the RRT growth.


To develop a heuristic function for an RRT that improves its performance in terms of reduced search time and shorter, straighter paths.


To study and develop a heuristic function that improves the RRT performance, by biasing the growth towards fast solutions with low costs. At the same time, the complete computational time must be considered. The function shall be implemented and evaluated in simulation, and preferably also in a real vehicle.


Master (civilingenjör) in electrical engineering, physics, mechatronics, computer science or similar. Preferably with specialization in control theory, robotics or computer science.

Number of students: 1

Start date: January 2020

Estimated time needed: 20 weeks

Contact persons and supervisors:

Robin Andersson, Autonomous Vehicle Motion Planning and Control,

08 - 553 702 65

Enclose CV, cover letter and transcript of records.

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