30 credits – Artificial Intelligence for Collision Avoidance of Autonomous Vehicles

30 credits – Artificial Intelligence for Collision Avoidance of Autonomous Vehicles

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

Ingress:
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.

Background:
The concept of autonomous driving has rapidly transitioned from being a futuristic vision of robotics and artificial intelligence to being a present-day reality. The recent innovations in sensing, mapping, planning, control, and machine learning have enabled intelligent transport systems that can operate in a variety of scenarios, from desolated mines to busy urban intersections.

A crucial factor that will determine the use of this new technology in our society is the inherent risk to the human driver. Human drivers use their experience to judge risks and hazards, which in turn affect their awareness level and their driving patterns. Autonomous vehicles also need to continuously assess the risks of accidents and plan the next movement accordingly.

Target:
The target of this thesis is to investigate and implement a predictive machine learning approach for risk assessment for autonomous vehicles. More specifically, we want to estimate the risk of collision of the autonomous vehicle with the surrounding objects. This risk evaluation will allow the system to have a better situational awareness and to react proportionally to the threat.

Assignment:
The assignment is divided into sub-tasks: 1) Investigate the state of the art; 2) Perform a correct scene analysis, which consists in identifying the objects located around the autonomous vehicle; 3) Based on the current and past states of the scene, understand the current driving situation and predict the most probable evolution of the scene; 4) Design and implement a method to measure the collision risk of the vehicle with the objects in the scene; 5) Test the approach in simulations and/or in Scania research prototype vehicles.

Education:
Master (civilingenjör) in computer science, robotics, 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 2019
Estimated time needed: 20 weeks

Contact persons and supervisors:
Laura Dal Col, Development Engineer in Autonomous Motion, laura.dal.col@scania.com, 08 - 553 851 20

Christoffer Norén, Senior Engineer in Autonomous Motion, christoffer.noren@scania.com, 08 - 553 811 48

Application:
Enclose CV, cover letter and transcript of records
Mer info
Område Södertälje
Yrkesroll Teknik & Ingenjör, Ingenjör, Civilingenjör
Typ av anställning Heltid, Projekt- / Visstidsanställd, Examensarbete
Hemsida http://www.scania.com
Sista ansökningsdag 23 nov (7 dagar kvar)

Om arbetsgivaren

Scania är en världsledande leverantör av transportlösningar. Tillsammans med våra partners och kunder leder vi övergången till ett hållbart transportsystem. Under 2017 levererade vi 82 500 lastbilar, 8 300 bussar samt 8 500 industri- och marinmotorer till våra kunder. Vi omsatte närmare 120 miljarder kronor, varav 20 procent utgjordes av servicerelaterade tjänster. Scania grundades 1891 och finns idag representerat i mer än 100 länder, och har drygt 49 000 medarbetare. Forskning och utveckling är koncentrerad till Sverige, med filialer i Brasilien och Indien. Produktion sker i Europa, Latinamerika och Asien, med regionala produktcentra i Afrika, Asien och Eurasien. Scania ingår i Traton Group. För ytterligare information, besök www.scania.com.