State of Alertness During Simulated Driving Tasks
Literature has shown the importance of studying alertness and attention in drivers by means of electroencephalographic (EEG) indexes. Moreover, many kinematic parameters can be used to give information about the safety of the road depending on the traffic flow.
To our knowledge, no study, has focused the attention on the relationship between alertness indexes and kinematic parameters. The aim of this study was to analyse the influence of traffic conditions on alertness by assessing an EEG index (EI) and the relationship between EI and kinematic parameters.
Nine volunteers participated in the study. The experiment was carried on by using the STISIM driving simulator. Three scenarios were simulated. Each scenario was characterized by a different traffic flow. From STISIM two kinematic parameters were considered: mean velocity and distance from the central line during driving.
EEG data were recorded during driving simulations and the EI was derived from the power spectral bands of EEG.
The results showed significant different values for EI among the three conditions, with the highest level of alertness in urban scenario. Significant differences for the kinematic parameters were also found. The mean velocity decreased when the traffic conditions were more demanding, and the capacity to maintain the vehicle in the centre of the road decreased when the traffic conditions were less demanding.
The analysis suggests that when the mean velocity increases, the alertness decreases with a consequent increased risk of collision; conversely when the mean velocity decreases, also EI decreases so demonstrating a greater level of alertness accomplished by driving on the centre of the road, so reducing the probably of collision. These results suggest that the alertness of the drivers is influenced by the traffic flow.
KeywordsAlertness Driving Engagement index EEG Kinematic parameters
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