Routes represent an integral part of triggering emotions in drivers. Navigation systems allow users to choose a navigation strategy, such as the fastest or shortest route. However, they do not consider the driver's emotional well-being. We present HappyRouting, a novel navigation-based empathic car interface guiding drivers through real-world traffic while evoking positive emotions. We propose design considerations, derive a technical architecture, and implement a routing optimization framework. Our contribution is a machine learning-based generated emotion map layer, predicting emotions along routes based on static and dynamic contextual data. We evaluated HappyRouting in a real-world driving study (N=13), finding that happy routes increase subjectively perceived valence by 11% (p=.007). Although happy routes take 1.25 times longer on average, participants perceived the happy route as shorter, presenting an emotion-enhanced alternative to today's fastest routing mechanisms. We discuss how emotion-based routing can be integrated into navigation apps, promoting emotional well-being for mobility use.

翻译：路径是触发驾驶员情绪的重要组成部分。导航系统允许用户选择导航策略，例如最快或最短路径，但未考虑驾驶员的情绪健康。我们提出HappyRouting，这是一种基于导航的新型共情车载界面，可在引导驾驶员应对真实交通情境的同时唤起积极情绪。我们提出了设计考虑因素，推导了技术架构，并实现了路径优化框架。我们的核心贡献是基于机器学习的生成式情感地图层，该层根据静态和动态情境数据预测沿路情绪。通过真实驾驶研究（N=13）评估HappyRouting，发现快乐路径使主观感知效价提升11%（p=.007）。尽管快乐路径平均耗时增加1.25倍，但参与者主观感知其更短，为当今最快路径机制提供了情感增强型替代方案。我们探讨了如何将基于情感的路由集成到导航应用中，以促进移动出行中的情绪健康。