Drowsy driving is one of the main causes of traffic accidents. To reduce such accidents, early detection of drowsy driving is needed. In previous studies, it was shown that driver drowsiness affected driving performance, behavioral indices, and physiological indices. The purpose of this study is to investigate the feasibility of classification of the alert states of drivers, particularly the slightly drowsy state, based on hybrid sensing of vehicle-based, behavioral, and physiological indicators with consideration for the implementation of these identifications into a detection system. First, we measured the drowsiness level, driving performance, physiological signals (from electroencephalogram and electrocardiogram results), and behavioral indices of a driver using a driving simulator and driver monitoring system. Next, driver alert and drowsy states were identified by machine learning algorithms, and a dataset was constructed from the extracted indices over a period of 10 s. Finally, ensemble algorithms were used for classification. The results showed that the ensemble algorithm can obtain 82.4% classification accuracy using hybrid methods to identify the alert and slightly drowsy states, and 95.4% accuracy classifying the alert and moderately drowsy states. Additionally, the results show that the random forest algorithm can obtain 78.7% accuracy when classifying the alert vs. slightly drowsy states if physiological indicators are excluded and can obtain 89.8% accuracy when classifying the alert vs. moderately drowsy states. These results represent the feasibility of highly accurate early detection of driver drowsiness and the feasibility of implementing a driver drowsiness detection system based on hybrid sensing using non-contact sensors.

Thermal factors not only affect the thermal comfort sensation of occupants, but also affect their arousal level, productivity, and health. Therefore, it is necessary to control thermal factors appropriately. In this study, we aim to design a thermal environment that improves both the arousal level and thermal comfort of the occupants. To this end, we investigated the relationships between the physiological indices, subjective evaluation values, and task performance under several conditions of changes in the indoor ambient temperature. In particular, we asked subjects to perform a mathematical task and subjective evaluation related to their thermal comfort sensation and drowsiness levels. Simultaneously, we measured their physiological parameters, such as skin temperature, respiration rate, electroencephalography, and electrocardiography, continuously. We investigated the relationship between the comfort sensation and drowsiness level of occupants, and the physiological indices. From the results, it was confirmed that changes in the indoor ambient temperature can improve both the thermal comfort and the arousal levels of occupants. Moreover, we proposed the evaluation indices of the thermal comfort and the drowsiness level of occupants using physiological indices.

The design of vehicle cabin seats is crucial in transportation, as it directly affects the safety and comfort of both drivers and passengers. To design seat parameters that enhance sitting comfort, a quantitative evaluation of sitting comfort involving an understanding of users’ physiological responses is necessary. This study aimed to assess users’ physiological responses to relaxation induced by changes in seat parameters using electroencephalography and electrocardiography. We examined the physiological responses and subjective evaluations of relaxation in fifteen participants, focusing on the effects of reclining, ottoman, and slab. The results demonstrated an improvement in the subjective level of relaxation with changes in all seat parameters set here. However, central nervous system responses and autonomic nervous system reactions varied based on alterations in posture angles and seat pressure distributions. This underscores the importance of physiological markers, encompassing indicators of autonomic and central nervous system responses, in evaluating relaxation in relation to changes in posture angles and seat pressure distribution.

Indoor temperature affects the arousal level and thermal comfort of drivers. In this study, we aim to prevent the drowsy state and to improve the thermal comfort of drivers in driving for a long time using changes in ambient temperature in cabin. Targeting the scene of driving for 90 minutes, the hypothesis that repeated thermal stimulation to the driver can prevent the decrease of arousal level and thermal comfort of the driver was tested. We investigated the drowsiness level, thermal comfort based on subjective evaluation, and physiological parameters of the driver in the condition of repeated thermal stimulation for 90 min with driving in a simulator. As a result, the drowsiness level with a scale from 0 (alert) to 4 (extremely drowsy) was kept below 1 (slightly drowsy), and the comfort sensation with a scale from -3 (very uncomfortable) to 0 (comfortable) was maintained above -1 (slightly uncomfortable). These results suggest that repeated thermal stimulation is valid to prevent the decrease of arousal level and thermal comfort of the driver.

This study proposes an autonomous lane-changing system for congested merging areas. Manual and autonomous vehicles are expected to coexist until all vehicles are substituted by autonomous vehicles. Therefore, interactions between humans and autonomous driving systems should be discussed. This study assumed a scenario in which an autonomous vehicle performed a lane change to a congested main lane, where all vehicles were manual. The proposed system estimated the possibility of changing lanes without collisions. A driving simulator was used to measure the lane-changing operations of human drivers in a congested merging area, and the proposed method was developed based on the experimental results. Simulations demonstrated that the proposed method could safely change lanes.

'Retraction Note to: Impact of Auditory Alert on Driving Behavior and Prefrontal Cortex Response in a Tunnel: An Actual Car Driving Study' published in 'Advances in Neuroergonomics and Cognitive Engineering'