Concept
An AI implemented drift mode that assisted drivers while drifting both on track and on the road.
Problem
Performance driving demands split-second decisions, yet most in-car interfaces today are built for everyday commuting, not high-intensity scenarios like drifting. Critical information is often scattered across multiple displays or even omitted, forcing drivers to divide their attention at the exact moments focus matters most. Drift Mode addresses this gap by delivering a focused, intelligent HUD that adapts to the driving context—supporting performance without compromising safety.
Pain Points
Design Challenge
Use Cases
Solution
By consolidating critical vehicle data into a single, glanceable interface, the system reduces cognitive load and keeps the driver’s attention on the road. Context-aware visuals and progressive safety cues communicate traction limits and vehicle stability in real time, enabling confident performance driving without sacrificing control or safety.
Design
Road
Track
Features
Configuration Panel
A performance-tuning interface that lets drivers define how much drift freedom the system allows in real time. By adjusting thresholds for slip angle, traction intervention, and safety boundaries, the Configuration Panel gives drivers precise control over how aggressively Drift Mode responds—maintaining a configurable safety margin while supporting intentional, controlled drifting.
Moving Forward
Future iterations of Drift Mode could expand beyond real-time assistance to include deeper performance analysis, adaptive learning, and expanded environmental awareness. By integrating post-drive insights, skill-based presets, and enhanced sensor data, the system could evolve into a fully personalized performance and safety platform—supporting drivers as they progress while maintaining responsible boundaries for high-intensity driving.
Drift Mode Assistance HUD
The Next Generation of Performance
Timeline
Sep - Dec 2025
Role
Designer & Developer
Platforms
Figma, Unreal Engine, After Effects