Virtual Reality Web Application for Automotive Data Visualization

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Oliveira, T (Author) Other; da Silva, JML (Author) Other; Jorge Alves Silva (Author) FEUP

Conference proceedings International

Title: 2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Pages: 37-42

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00V-1W3

DOI: 10.1109/icarsc52212.2021.9429800

Abstract (EN): Road safety is crucial in the design of autonomous vehicles, so safety and performance tests must be carried out regularly. Visualization applications of data acquired in these tests are critical to helping the continuous progress of autonomous driving. Currently, there is an application that helps in visualizing these data through a web platform, called Kratos Visualization. This application was developed using the WebGL library, to help companies that carry out experiments with autonomous vehicles to visualize and validate the data that they collect. These data represent different sequences of autonomous driving experiences and can contain a lot of information about the vehicle and objects in the environment around it. The work that led to this paper aims to explore the visualization of these data with the help of virtual reality. To strengthen the visualization of autonomous driving data, an application was created named Kratos VR. Designed with the A-Frame framework to work in any browser, this application contains the same functionalities of Kratos Visualization and new virtual reality features. Performance tests were carried out to evaluate the application. These tests allowed us to conclude that virtual reality can be successfully used to effectively visualize Advanced Driving Assist Systems (ADAS) and Autonomous Driving (AD) data and that the developed application provides a solid basis for future virtual reality applications in this field.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6