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Ansök senast: 2021-11-30
30hp – Modelling Safety of Autonomous Driving using Stochastic Processes
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.
In experimental projects around the world, autonomous driving has been demonstrated for different kind of vehicles and scenarios. Scania is among the companies aiming to sell fully autonomous vehicles a few years from now. However, to guarantee safety of the autonomous driving is still a huge challenge. Notably, this is also indicated by the fact that all of the reported experiments on public roads have had a human driver present ready to take over in a situation when autonomous driving fails.
Clearly, safety of autonomous driving in general and in particular for Level 3, i.e. when the person in the drivers seat does not need to watch the road, needs deeper analysis. In this project, autonomous driving is to be analysed using semi-Markov processes. Semi-Markov processes are a generalization of Markov processes and the advantage is that the former are more general since they allow transition probabilities that are dependent on time spent in a state; something that is useful when modelling vehicle and driver behaviour in the context considered. By using the models, the aim is to answer questions such as: how does reliability and response time of individual systems affect the overall safety? In a situation where driver actions are needed, how does driver alertness affect overall safety?
Example of assignments:
- Extend the current semi-Markov analysis to allow for more general semi-Markov models more applicable to real systems for autonomous driving.
- Extend a tool within MATLAB to support analysis of more general semi-Markov models, to support scenario-modelling and analysis related to autonomous driving.
Specify education or specialization: M.Sc. in Engineering or similar with an interest for mathematics.
Number of students: 1-2.
Start date: January/February 2022.
Estimated time needed: 20 weeks.
Contact person and supervisor:
Stefan Kaalen, Industrial PhD student, 0700811610 , firstname.lastname@example.org.
Enclose CV, personal letter and grades.
Please send your application to email@example.com.
2021-09-14 – 2021-11-30