Enhancing safety of transport by road by on-line monitoring of driver emotions

Abstract

Driving while fatigued is dangerous and may result in car accidents. Moreover, adding technology to assist driving can distract the driver. In this work, we present a noninvasive and non-distracting method for monitoring driver emotions and fatigue. To the best of our knowledge, no scientifically agreed definition of emotions exists, as a physical state to be monitored. Emotion recognition is defined as measuring observations of motor system behavior that correspond with high probability to an underlying emotion or combination of emotions. This definition is based on the fact that measuring cognitive influences is currently impossible. In this work we have investigated driving sessions for identifying possible risks at drive in a certain itinerary, analyzing HRV trend. In general, HRV signals can be used as indicators of the responses of the autonomic nervous system (ANS) because the ANS is influenced by the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). The first one (SNS) response to an alarm situation: struggle, stress, drowsiness (and other factors) while PNS, when is activated, produces a slowing down of heart rate and breathing therefore PNS is the normal response to a situation of calmness and absence of danger and stress. For the test, we have collected ECG signals (Electrocardiography) and driver position in 15 trips on 2 daily sessions, by 2 different drivers on the same path. Results show an interesting geospatial relationship of emotions on the travelled path

A Review of Emotion Recognition Using Physiological Signals

“…Emotion recognition has been applied in many areas such as safe driving [ 1 ], health care especially mental health monitoring [ 2 ], social security [ 3 ], and so on. In general, emotion recognition methods could be classified into two major categories.…”

Multimodal Features for Detection of Driver Stress and Fatigue: Review

“…Driver stress can be caused by many stressors such as: mood changes, biorhythm, fatigue, boredom, disease, drugs, traffic (e.g. busy city [26]), weather, night driving, problems in job/family, workload [21], [27], [9]. In spite of the possibility to introduce a list of the most frequent stressors in drivers or according to the classical theories [28], a high inter-individual variability is typical for the start of the stress reaction [29], [13].…”

Analysis of the Relationship between Road Accidents and Psychophysical State of Drivers through Wearable Devices

“…From the methodological point of view, the approach adopted in this study can be summarized by the diagram reported in Figure 1. It should be underlined that investigation of the driver's psychophysical state was performed in several previous studies [22][23][24][25][26][27][28][29][30][31]. The added value of this paper is an investigation into how this aspect influences driving activity, in particular, the probability that high levels of stress or relaxation could impact on-road safety issues, supporting a preventive approach for road safety analysis.…”