Motorsport performance analysis: A spatio-temporal approach

Abstract

As data logging technologies advanced, a point was reached where amateur motorsport enthusiasts could now log their vehicle's data while competing in motorsport events. Many drivers take advantage of these new data logging technologies but lack options for analyzing the data during and after motorsport events beyond standard tables and two-dimensional graphs. This thesis investigated the use of GIS as a tool for analyzing data collected during a motorsport event through time geography approaches and three-dimensional geovisualization techniques. Data were collected from the vehicle to analyze the speed and handling of the car while heart rate data were collected from the driver to help understand the driver's emotional state while navigating the course. Analysis of the data showed that time geography visualizations in a three-dimensional environment could help drivers better understand the data that had been collected from their vehicles and themselves and use it to improve their future performances when driving in motorsport events.