Race Sight

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  Dashboard 1 - Single Driver

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  3D Maps

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  Scatterplots

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  Compare Performance

Inspiration

Inspired by the high-performance environment of racing, the challenges of interpreting large and complex datasets, and the need to turn this data into strategic insights, I wanted to create a platform that unifies multiple data streams, visualizes them interactively and immersively, and recreates play-by-play moments—serving both as a means of continuous improvement for drivers and teams and as a way to enhance strategic decision making.

What it does

Race Sight is an immersive and interactive racing analytics platform and playback system. The advanced performance analytics tool integrates telemetry data, weather and environment conditions, analysis endurance data and results data.
The system combines: 1) customizable, dynamic, interactive scatterplots on driver endurance, 2) multiple interactive, synchronized and animated dashboards and 3) 3D animated heat maps that allow users to explore how performance variables change over the course of the race. Users can also view key metrics like race results and information on each driver’s best 10 laps. Users can view data by driver, lap or even compare performance between drivers or between races.

How I built it

The demo was built with HTML, CSS and JavaScript. JavaScript frameworks, D3.js and Three.js were used to create interactive and immersive data visualizations. Python scripts were created to process the large datasets and convert them to JSON format. JSON files were then stored for easy accessibility using open-source databases, PostgreSQL (via Supabase).

Challenges I ran into

Python scripts were developed to handle the very large telemetry files (> 4 GB). In the first script, each telemetry file was split into multiple smaller files based on vehicle number, and all resulting vehicle number files were stored together in a dedicated folder. This process increased data accessibility and improved ease of manipulation of the data by vehicle number. Additionally, an optional script was created to extract selected lap numbers for the purposes of the demo.

Accomplishments that I'm proud of

That the demo is useful to drivers, coaches, engineers and analysts, and can be used to display the data in unified synchronized dashboards. The demo can currently be used for post-race analysis, in review sessions and can be adapted to display real-time data.

What I learned

A lot about the GR Cup series, interactive and immersive analytics and insights into the large volumes of sensor data generated real-time during a race.

What's next for Race Sight

Further development of the backend, real-time data processing.

Built With

• d3.js
• github
• javascript
• leaflet.js
• python
• three.js