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Cornering Assistance Application

This project contains the source-code of the prototype that was implemented for the master's thesis "Using Mobile Edge Computing Technologies for Real-Time Cornering Assistance" at the TU Wien. If you use the source code, pls. make the following citations:

  • Hong-Linh Truong, Matthias Karan, "Analytics of Performance and Data Quality for Mobile Edge Cloud Applications", Preprint PDF, Mar 2018.
  • Matthias Karan, "Using Mobile Edge Computing Technologies for Real-Time Cornering Assistance", Master Thesis, TU Wien, Feb 2018.


To contribute to safer driving in any type of car, in the thesis "Using Mobile Edge Computing Technologies for Real-Time Cornering Assistance" we introduce a novel system that assists drivers in real-time while cornering. The system is designed in a way that it can be deployed to both the cloud and/or the emerging edge-computing infrastructure.


  • warn drivers ahead of curves in real-time
  • recommend safe speeds to enter a curve
  • use novel edge- and cloud-computing architectures and algorithms

See the poster for more information about the thesis.

Demo Videos

The following videos demonstrate the prototype application:



Run the Demo

See Demo - README to run the demo yourself.

Prototype Structure

The software components of the thesis' prototype are split up into the following directories:

android: A native android prototype that shows upcoming curves and recommends a safe speed live on the road.

commons: A Java library that contains common code used in the services (recommendation and detection).

detection: Source code for the detection application written in Apache Apex

docker: Docker configurations for deploying the prototype, run experiments and a simple demo (described below).

recommendation: Source code for the recommendation service.

simulator: Java applications that simulate client/car functionalities.