Race Data AI 심 레이서를 위한 텔레메트리 by Cansu Cetin

Race Data AI 심 레이서를 위한 텔레메트리 by Cansu Cetin is a highly esteemed winner of the very prestigious 2025 A' Design Award 철상 in 인터페이스, 인터랙션 및 사용자 경험 디자인 Competition Category.

철인터페이스· 2025

Race Data AI 심 레이서를 위한 텔레메트리

by Cansu Cetin

Client: Driven AVS

A' Design Award 철상 Winner in 인터페이스 Category

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The Design

About Race Data AI 심 레이서를 위한 텔레메트리

이 프로젝트는 가상과 현실 레이싱을 연결하는 사용자 친화적인 텔레메트리 도구를 개발하여 심 레이싱 분석을 재정의합니다. 인터랙티브 트랙 맵, 커스터마이즈 가능한 대시보드, 랩 비교 기능을 통해 복잡한 데이터를 간소화합니다. 심 레이서들의 반복적인 피드백을 바탕으로 개발된 이 디자인은 성능 최적화를 위한 접근성 높은 상세한 인사이트를 제공합니다. 혁신과 사용성을 결합하여 레이서들이 지속적으로 발전하고 레이싱 데이터를 깊이 있게 이해할 수 있도록 합니다.

The Recognition

About the A' Design Award 철상

Race Data AI 심 레이서를 위한 텔레메트리, 이 작품은 A' Design Award 철상 수상작으로, 잘 디자인된 창작물에 기대되는 전문적·산업적 요건을 충족하는 좋은 디자인에 수여되는 권위 있는 인정입니다. 철상 수상작은 창작자의 뛰어난 기술, 높은 전문성, 전문가다운 이해, 창의적 역량을 보여 줍니다. Race Data AI 심 레이서를 위한 텔레메트리, 이 작품은 높이 평가받고 감탄과 사랑을 받는 창작물로서 실용적이고 혁신적일 것으로 기대됩니다. 이 철상 수상 디자인은 업계 모범 사례를 통합하며 노하우와 재능으로 연결된 유능한 기술적 특성을 갖추고 있습니다. Race Data AI 심 레이서를 위한 텔레메트리, 이 작품은 철저함으로 존중받으며 삶의 질을 개선하여 세상을 더 나은 곳으로 만들도록 디자인되었습니다.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: This design transforms sim racing analysis with intuitive data visualization and advanced telemetry tools, providing racers with actionable insights. Its user-focused approach ensures accessibility while maintaining technical depth, featuring interactive track maps, customizable dashboards, and seamless lap comparisons. Personalized analysis tools and community-driven feedback make it a standout solution for improving performance and bridging the gap between virtual and real racing.
Dimensions & Packaging: The design was developed with a focus on responsiveness, ensuring compatibility across various screen sizes. The layout adapts seamlessly from 1024x768px to 1792x1024px for larger displays. Interactive elements were optimized for touch and mouse input, with clickable areas sized for ease of use across devices. Data visualization tools were engineered for high performance, processing telemetry data in real-time with minimal latency, ensuring smooth user experience even with large datasets.
Tags: Telemetry analysis, real-time data processing, racing insights, sim racer tools, user experience design, user-centric design,
Production Technology: The design was developed using an iterative UX/UI process, emphasizing user feedback from sim racers. Wireframes and prototypes were created to test and refine key functionalities, such as telemetry data visualization and lap comparisons. Agile methodology was employed to allow for continuous improvement based on user testing. A modular design approach ensured flexibility, while data-driven insights guided the creation of interactive features that prioritize performance optimization and ease of use.
Design Challenge: The hardest part of this design was simplifying complex telemetry data without losing essential details. The challenge lay in balancing technical depth with user accessibility, as racers needed both detailed insights and easy navigation. Historical perspectives of traditional racing tools influenced the design, but new technology offered opportunities to innovate. External factors, such as varying levels of user expertise and limited research on specific racing behaviors, also presented obstacles, requiring extensive user feedback to refine the product.
Research: The research combined qualitative and user-centered studies to understand sim racers' needs and behaviors. The goal was to simplify telemetry data presentation to enhance performance. Insights were gathered through interviews, surveys, and online community observations, involving both casual and competitive sim racers. Results revealed a preference for simplified, interactive interfaces, informing a design that improves performance and user experience in virtual and real-world racing.
Inspiration: The project was inspired by the challenges sim racers face in translating virtual performance to real-world racing. Recognizing the complexity of existing telemetry tools, the goal was to simplify data analysis while enhancing usability. Drawing from user interviews, market research, and technical studies, the design combines intuitive features with a user-centered approach to help racers optimize performance and make the most of limited practice time.
Project Duration: The project started in May 2024 in Turkey and finished in December 2024 in Canada.
Operation Flow: This design helps sim racers improve their performance by providing easy-to-understand data about their racing. Users can view their racing line, speed, and other key information to see where they can improve. By comparing laps, racers can find areas to optimize, such as braking and acceleration points. The design allows for simple interactions like clicking on turns to get more detailed feedback, making it easier to focus on key areas for improvement and achieve better results over time.