30 credits - Collision Risk Prediction for Autonomous Driving Systems

Sodertalje, Stockholm
den 4 oktober 2019
den 24 november 2019
Övriga jobb
A 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.

Autonomous driving is a widely studied topic that has gained a lot of interest both in the scientific and industrial community: there are more and more advanced driver assistance functions on the market, and we will see fully autonomous vehicles on the road in the near future.

Safe navigation in urban areas is a challenging problem for self-driving vehicles.

One of the reasons why human drivers can safely navigate and interact with other traffic participants is that they augment their sensing capabilities and anticipate the need to slow down due to the potential risk of collision. Therefore, one of the key capabilities to enable autonomous driving is to estimate the risk of collision with other vehicles.

Situational awareness is crucial for autonomous driving in urban environments. In order to ensure the safety of its occupants and other traffic coparticipants, an autonomous vehicle has to perform the sense-plan-act methodology in which sensing relates to understanding the surrounding environment, planning is the decision making and acting is actually moving the vehicle according to the planning. The problem of estimating the probability of a traffic collision occurring in real-time has been intensively targeted by many researchers and engineers. The objective of this project is to build a framework to estimate the probability of a collision risk with surrounding objects in Scania's platform for autonomous driving.

The assignment is divided into the following sub-tasks: 1. Evaluate current state of the art; 2. Model the occupancy and dynamics of the environment; 3. Propose and implement a method to describe the occupancy evolution of the environment (e.g., a risk grid) that is updated according to the observations; 4. Propose and implement a method to estimate the collision risk of the autonomous vehicle, evaluated by quantitative measures such as time to collision; 5. Test the work in simulation and/or in real experiments using research vehicles;

Master (civilingenjör) in computer science, engineering physics, electrical engineering, or applied mathematics, preferably with specialization in artificial intelligence algorithms, control theory, optimal control or optimization. Knowledge of programming, predictive modeling, and reinforcement learning are a plus.
Number of students: 1-2
Start date: January 2020
Estimated time needed: 20 weeks

Contact persons and supervisors:
Laura Dal Col, Development Engineer in Autonomous Motion, , 08 - 553 851 20

Christoffer Norén, Senior Engineer in Autonomous Motion, , 08 - 553 811 48

Enclose CV, cover letter and transcript of records.

Scania is a world-leading provider of transport solutions. Together with our partners and customers we are driving the shift towards a sustainable transport system. In 2018, we delivered 88,000 trucks, 8,500 buses as well as 12,800 industrial and marine engines to our customers. Net sales totalled to over SEK 137 billion, of which about 20 percent were services-related. Founded in 1891, Scania now operates in more than 100 countries and employs some 52,000 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 centres in Africa, Asia and Eurasia. Scania is part of TRATON SE. For more information visit:

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