Industrial PhD Position in “Perception” for Autonomous Vehicles

At Autonomous Transport Solutions (ATS) Pre-Development & Research, Scania R&D, we pursue top-quality research and development of future cutting edge ATS concepts. We operate in agile, diverse and self-steered teams that work in close cooperation with the Volkswagen group, leading technology suppliers, and academic institutions. Our culture is built upon delivering added customer value through research and practical experiments that iteratively lead to concepts for industrialization.

Background

Vehicle autonomy has been heavily promoted as a means of improving transportation safety on the roadway. This goal, however, requires the vehicle to possess a high level of scene perception and situational awareness — that is, the ability to correctly perceive and understand the surrounding environment, the other road users and how the scene evolves over time.

One of the reasons why human drivers can safely navigate in complex environments is that they augment their sensing capabilities and anticipate the need to react to potential hazards. As an example, a driver slows down because she foresees the risk of collisions that arise due to the presence of vulnerable road users, occlusions in the traffic scene, or unfavourable weather conditions. Despite rapid research and innovation in scene perception for autonomous driving, dealing with complex traffic scenes and scalability for the production of fully autonomous vehicles are still challenging – specifically, when dealing with occluded traffic participants.

PhD Thesis Description

This PhD position lies within a bigger research project with the overall target to detect, classify, and track all road participants, specifically the occluded ones (i.e. road participants partly observable by onboard sensors), that share the road network with the autonomous vehicle. Within this PhD position, you will be focusing on the development of novel theoretical concepts and evaluate these in practice on an experimental testbed. The thesis goal to develop algorithms for enabling the prediction of future states of scene objects particularly the occluded ones. These reasoning algorithms will be based upon the prior information for object positions and classes derived from scene context information both perceived (e.g. from objects detected in multi-sensor data) and from scene metadata (e.g. HD maps). The algorithms will have to perform in real-time conditions while being validated through simulation and real data. To achieve these objectives, the industrial PhD student will pursue research in the theoretical areas of sensor fusion, behavioural learning, prediction and probabilistic modelling.

This research project will be conducted a research team responsible for concept evaluation of environment perception algorithms for autonomous driving. The results of this research project will be implemented in Scania’s development environment for autonomous driving and will be experimentally evaluated in operating prototype vehicles (trucks and buses) equipped with sensors and a platform setup for autonomous driving.

Your profile

To apply you should have a master of science/engineering degree (or equivalent) in applied mathematics, computer science, robotics, engineering physics, electrical engineering or in a related technical science or engineering subject.

The candidate is expected to have a solid mathematical background and programming skills. We look for a candidate who is self-motivated, engaged, and can communicate clearly to the team and the rest of the organisation.

Extra meritorious are:


• Knowledge and experience within software languages such as C++ and/or MATLAB/Simulink and/or Python.
• If you are fluent in English both in writing and in speech.

This research will be conducted in collaboration with Vinnova, FFI and the Robotics, Perception and Learning department at KTH Royal Institute of Technology, in Stockholm. Start date: not later than Feb 2021.

Number of PhDs: 1

Further Information

Does this sound like an exciting challenge? We are looking forward to receiving your application! Please do not hesitate to contact:

Nazre Batool (Senior Engineer) +46 (0) 855 372 381 (or)

Naveenraj Vijayan (Manager) +46 (0) 855 353 208 to know more.

Application

Your application should include a CV, cover letter and copies of any certificates & transcripts. Apply via our website www.scania.com/jobs by 2021-01-03 at the latest. Job Id 20202596. Applications will be reviewed and interviews held continuously during the recruitment process.