Dodging Stress: Non-Intrusive Stressor Mapping While Driving

Driving under stress negatively affects driving behaviour, increasing the risk of dangerous traffic situations and accidents. To effectively reduce driving stress, it is crucial to gain insights into stress triggers using ubiquitous stress detection methods that facilitate the collection of real-world driving data. We developed a system that localises stressors along a route using heart rate data collected from a smartwatch. Stress sources are identified by detecting and classifying heart rate anomalies, which are then correlated with GPS locations. Our system differentiates between common and individual stressors using a scoring system and maps detected stress indicators on a stressmap, allowing comparison across multiple rides. Crowdsourced deployment enhances the precision of stressor localization and enables their association with specific road characteristics. Our findings indicate that heart rate anomalies reliably predict the locations of stressors, which are consistently observed across multiple rides and different drivers. These stressors are linked to traffic facilities and road features, such as intersections and traffic lights. By employing ubiquitous stress detection methods, we enable the collection of crowdsourced data, providing new insights into real-world driving stress. Our stress detection and visualization system aims to improve route guidance, particularly benefiting stress-prone, stress-sensitive, and frequent drivers.