Personalized Driver State Profiles: A Naturalistic Data-Driven Study

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1212)


Previous studies suggest that variation in driver’s states, such as being under stress, can degrade drivers’ performance. Moreover, different drivers may have varying behaviors and reactions in different road conditions and environments (contexts). Thus, personalized driver models given different contextual settings can assist in better predicting the drivers’ states (behavioral and psychological); this can then allow vehicles to adjust the driving experience around the driver and passengers’ preferences and comfort levels. This paper aims at developing personalized hierarchical driver’s state models by considering driver’s heart rate variability (HRV) in relation to the changes in various contextual settings of road, weather, and presence of a passenger. Results from 12 participants over 150 h of driving data suggest that drivers are on average less stressed in highways compared to cities, when being with a passenger compared to alone, and when driving in non-rainy conditions compared to rainy weather.


Naturalistic driving studies Driver’s heart rate Environmental factors 


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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Engineering Systems and EnvironmentCharlottesvilleUSA

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