Race Data AI 模擬賽車遙測系統 by Cansu Cetin is a highly esteemed winner of the very prestigious 2025 A' Design Award 鐵獎 in 介面、互動及用戶體驗設計 Competition Category.

鐵介面· 2025

Race Data AI 模擬賽車遙測系統

by Cansu Cetin

Client: Driven AVS

A' Design Award 鐵獎 Winner in 介面 Category

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The Design

About Race Data AI 模擬賽車遙測系統

此項目透過創建一個用戶友好的遙測工具，連接虛擬與現實世界賽車，重新定義模擬賽車分析。系統透過互動賽道地圖、可自訂儀表板及圈速比較，簡化複雜數據。設計經模擬賽車手的反覆意見回饋而開發，提供易於理解而又詳盡的見解以優化表現。結合創新與易用性，賦予賽車手持續改進及更深入理解其賽車數據的能力。

The Recognition

About the A' Design Award 鐵獎

Race Data AI 模擬賽車遙測系統是 A' Design Award 鐵獎得主，這是授予滿足人們對設計精良的創作所期待的專業與工業要求的優良設計的聲望認可。鐵獎得主展現出其創作者的高超技藝、高度專業化、專家級的理解力和創造能力。預計Race Data AI 模擬賽車遙測系統將成為一件備受推崇、令人欽佩且被珍愛的創作，既實用又創新。這件贏得 A' Design Award 鐵獎的設計整合了行業最佳實踐，並擁有與專業知識和才華相結合的稱職技術特性。Race Data AI 模擬賽車遙測系統因其嚴謹而受到尊重，旨在提供有助於讓世界變得更美好的生活品質改善。

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.