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Scania Södertälje Heltid

30 hp – Geospatial trip data generation using deep neural networks

Detta jobb är inaktivt och går inte att söka längre.

About the job

Scania is one of the world’s leading manufacturer of trucks and buses for heavy transports, as well as industrial and marine engines. Transport services and logistics services make up an increasing part of our business, which guarantees Scania’s customers cost-efficient transport solutions and high availability. Over a million Scania vehicles are in active use, in over 100 countries.

In the Connectivity section within Scania R&D, we develop new solutions for connected vehicles in our Internet of Things (IoT) platform, as part of Scania’s increasing focus on communication, services and smart transport solutions. Advanced data analysis capabilities are a cornerstone enabler in this development.


The goal of this project is to use deep learning methods to generate sequential geospatial traces that are similar to real trips driven by our vehicles. Generating synthetic data has in recent years become a very popular way to increase data repository, but also a way to use non-private data for model development or testing functionalities due to GDPR. In particular in the field of GANs (generative adversarial networks) generating realistic face photos of non-existing persons. Now, geospatial data together with time and date are sensitive since it could be back-tracked to an individual and thus is very personal. Thus being able to generate realistic geospatial data together with some vehicle data would be invaluable for Scania. A big challenge with geospatial data is that the position has a physical context, meaning that generating a geoposition in the middle of an ocean is not desirable unless there is a ferry route.

Training data is available in the form of several years of geospatial traces from Scania’s global connected fleet of more than 450 000 heavy trucks and buses. The student will have access to Scania’s Hadoop cluster as computational resources to train and run their models.

Description of the assignment

  1. Evaluate suitable metrics to compare generated data against real data.
  2. Identify and evaluate suitable methods for generating fake geospatial traces with other vehicle data.
  3. Visually compare generated data with real data on a map.

If time permits,

  • Extend to generate more different types of vehicle data, such as fault codes.


Assign education, line or direction: masters programmes in Machine Learning, Data Science, Computer Science, Engineering Physics, Engineering Mathematics, Media Technology, or similar.

Number of students: 1-2

Start date for the Thesis project: Anytime during fall 2021 or spring 2022

Estimated timescale: 20 weeks

Contact person and supervisor

Kuo-Yun Liang, data scientist, 08-553 508 33,

Katarina Prytz, group manager, 08-553 723 08,


Your application should contain the following:

  • CV,
  • personal letter,
  • and copies of grades.

As part of your application, please:

  • describe methods you may use or a suggested approach you might take to solve this problem,
  • as well as delimitations that you may want to make to fit within the time scope.

Date of publication, as from – through

Until 2021-06-27. Applicants will be assessed on a continuous basis until the position is filled.

Om företaget

Scania is a world-leading provider of transport solutions, including trucks and buses for heavy transport applications combined with an extensive product-related service offering. Scania offers vehicle financing, insurance and rental services to enable our customers to focus on their core business. Scania is also a leading provider of industrial and marine engines. In 2019, we delivered 91,700 trucks, 7,800 buses as well as 10,200 industrial and marine engines to our customers. Net sales totalled to over SEK 152 billion, of which about 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 51,000 people. Research and development are concentrated in Sweden, with branches in Brazil and India. Production takes place in Europe, Latin America and Asia, with regional production centers in Africa, Asia and Eurasia. Scania is part of TRATON SE.

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