设计师 Cansu Cetin 的作品 Race Data AI 模拟赛车遥测系统荣获了极具声望的 2025 A' Design Award 铁奖，竞赛类别为界面、交互与用户体验设计。

铁界面· 2025

Race Data AI 模拟赛车遥测系统

设计师： Cansu Cetin

客户: Driven AVS

界面类别A' Design Award 铁奖获奖者

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关于 Race Data AI 模拟赛车遥测系统

该项目通过打造用户友好的遥测工具，重新定义了模拟赛车分析，在虚拟与真实赛车世界间架起桥梁。它借助交互式赛道地图、可定制仪表盘和圈速对比功能，将复杂数据化繁为简。该设计基于模拟赛车手的迭代反馈开发而成，提供既易于理解又详尽的性能优化洞察。融合创新性与易用性，助力赛车手持续进步并深入理解赛车数据。

荣誉认可

关于A' Design Award 铁奖

Race Data AI 模拟赛车遥测系统是 A' Design Award 铁奖得主，这是授予满足人们对设计精良的创作所期待的专业与工业要求的优良设计的声望认可。铁奖得主展现出其创作者的高超技艺、高度专业化、专家级的理解力和创造能力。预计Race Data AI 模拟赛车遥测系统将成为一件备受推崇、令人钦佩且被珍爱的创作，既实用又创新。这件赢得 A' Design Award 铁奖的设计整合了行业最佳实践，并拥有与专业知识和才华相结合的称职技术特性。Race Data AI 模拟赛车遥测系统因其严谨而受到尊重，旨在提供有助于让世界变得更美好的生活品质改善。

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由设计师提供的致谢、团队成员及技术详情。

独特属性: 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.
尺寸与包装: 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.
标签: Telemetry analysis, real-time data processing, racing insights, sim racer tools, user experience design, user-centric design,
生产技术: 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.
设计挑战: 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.
研究: 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.
灵感: 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.
项目周期: The project started in May 2024 in Turkey and finished in December 2024 in Canada.
操作流程: 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.