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Detecting Transport Hubs using TensorFlow

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Thesis project at Scania is an excellent way of making contacts for your future working life. Many of our current employees started their career with a thesis project.

Background

Scania is one of the world’s leading manufacturer of trucks and buses for heavy transports, as well as industrial and marine engines. Transport servi- ces and logistics services make up an increasing part of our business, which guarantees Scania’s customers costefficient 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 platform, as part of Sca- nia’s increasing focus on communication, servi- ces and smart transport solutions. Advanced data analysis capabilities are a cornerstone enabler in this development.

Description

Scania has 300 thousand connected vehicles continuously sending in position information. From this data we can learn a lot about the trucks and the transport system. One important piece of the information puzzle is the transport hubs.

A transport hub is a location with a specific set of characteristics. Examples of transport hubs are fuel stations, cargo terminals and saw mills. By identify- ing transport hubs and the relation between them we get a map of the transport system. Using this map we can discover logistic patterns, optimize transport flows and gain a deeper understanding of how the trucks are used. Ultimately this enables the future development of services to better conform with Scania’s customers’ needs in their daily ope- rations.

Master thesis work - 30 credits

Detecting Transport Hubs using TensorFlow

Contacts

Gustav Rånby, Development Engineer, gustav.x.ranby@scania.com, +46855372188

Anders Hasselkvist, Head of Driver & Vehicle Evaluation, anders.hasselkvist@scania.com, +46855352104

See more on scania.com

Not only will you have access to data sets with billions of observations and big data computation platforms, but you will have access to the know- ledgeable researchers and developers working at Connected Services.

Goal

Explore the applicability of TensorFlow and deep learning for detection and classification of trans- port hubs. This will at least include:

• Design and extract features from a set of vehicle stops or positions

• Setup TensorFlow

• Design, train, test and evaluate neural networks

Applicants

We are looking for 1-2 students who are studying a master’s program in Machine Learning, Data Sci- ence, Computer Science or similar. We consider it meritorious if you have experience with TensorFlow.

Applicants are expected to have a good understan- ding of relevant machine learning and data mining methods. As part of your application, please descri- be methods you may use or a suggested approach you might take to solve this problem.

Time plan

The project is planned for 20 weeks and can be started any time during the fall of 2017 or spring 2018.

Applicants will be assessed on a continuous basis until the position is filled.

Job Id: 20174956

Apply here

References

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