A naturalistic data-driven study was conducted in Chennai, Tamil Nadu, to study drivers’ physiological stress behavior under Indian traffic conditions. Six male participants with professional driving experience were recruited and asked to complete daily trips in urban roadways of Chennai. The participants completed their trips in a sedan-type four-wheeler vehicle mounted with two cameras (near the rearview mirror) to record the traffic data and driver’s in-vehicle behavior. An android phone mounted on the dashboard collected GPS and accelerometer data. The drivers wore an Empatica E4 device to record their physiological data, such as electrodermal activity, a key indicator of physiological stress. A holistic database assembled by linking different kinds of information was used to identify traffic events and road characteristics that can potentially impact the driver’s physiological stress levels. This data was analyzed using a mixed-effects model. It was observed that U-turns and Protected Right turns in an intersection significantly increased the driver’s stress. Additionally, slow-moving traffic in such scenarios further increased the effect. Merge Points serve as undesignated spaces for vehicle and pedestrian crossing and were identified as a contributor to the driver’s stress. Alternatively, the presence of a median and a greater number of lanes significantly decreased the driver’s stress. This paper reports a first-of-its-kind study conducted in India to assess the factors impacting driver’s stress. Adopting measures and initiatives to modify the identified factors can help create a stress-free traffic environment for Indian drivers.


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    Titel :

    A Naturalistic Data-Driven Study of Indian Traffic Conditions and Driver’s Physiological Stress


    Weitere Titelangaben:

    Transp. in Dev. Econ.


    Beteiligte:


    Erscheinungsdatum :

    01.10.2022




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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