Friday, March 03, 2023

Decision Factors for Offloading Automated Driving Functions to Cloud via 6G

Background and Goal of the Thesis

Cloud- and edge-based computing in the context of automated driving promises to support, enhance, as well as completely replace intelligent driving functions of automated vehicles. Next-generation communication technologies like 5G and beyond enable completely new use cases such as offloading functions from the vehicle to connected (edge-)cloud servers.

Offloading intelligent driving functions to a connected (edge-)cloud server promises to reduce vehicle power consumption, gives access to more compute, and potentially increases the vehicle hardware upgrade cycle.
The goal of this thesis is to design and possibly implement a decision process determining under which circumstances which functions are qualified to be offloaded to a connected (edge-)cloud server. To this end, suitable functions should be identified and decision criteria based on relevant properties of the current vehicle state should be derived. The decision process should also include an assessment of when to return offloaded functions back to the vehicle.

You will have access to ika’s extensive hardware and software infrastructure, including research vehicles, high-performance computers, simulation environments, and deep learning-frameworks. Additionally, you can expect close supervision and collaboration with other highly motivated researchers.

Working Points

  • Literature research on function offloading in the domain of automated driving and robotics in general
  • Identification of intelligent driving functions suitable for offloading, based on literature research and experience with ika’s existing driving functions
  • Derivation of decision criteria, based on literature research and experience with ika’s existing driving functions
  • Design of a decision process determining under which circumstances which functions are qualified to be offloaded
  • (optional) Implementation and evaluation of the designed decision process using ika’s research vehicle and high-performance cloud servers

Requirements

  • Reliability, commitment, and enjoyment of working independently
  • Enthusiasm for cutting-edge automated driving research
  • Logical and structured thinking and problem-solving
  • Nice-to-have experience
    • C++
    • ROS

Note: Please attach brief resume and grade summary.

Contact

Lennart Reiher M.Sc.
+49 241 80 25614
Email

Type of work

Bachelorarbeit, Masterarbeit

Start

at the earliest possible date

Prior knowledge

C++, ROS

Language

Deutsch, Englisch

Research area

Fahrzeugintelligenz & Automatisiertes Fahren

Address

Institute for Automotive Engineering
RWTH Aachen University
Steinbachstraße 7
52074 Aachen · Germany

office@ika.rwth-aachen.de
+49 241 80 25600

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