A Review on Measuring Affect with Practical Sensors to Monitor Driver Behavior

Abstract

Using sensors to monitor signals produced by drivers is a way to help better understand how emotions contribute to unsafe driving habits. The need for intuitive machines that can interpret intentional and unintentional signals is imperative for our modern world. However, in complex human-machine work environments, many sensors will not work due to compatibility issues, noise, or practical constraints. This review focuses on practical sensors that have the potential to provide reliable monitoring and meaningful feedback to vehicle operators-such as drivers, train operators, pilots, astronauts-as well as being feasible for implementation and integration with existing work infrastructure. Such an affect-sensitive intelligent vehicle might sound an alarm if signals indicate the driver has become angry or stressed, take control of the vehicle if needed, and collaborate with other vehicles to build a stress map that improves roadway safety. Toward such vehicles, this paper provides a review of emerging sensor technologies for driver monitoring. In our research, we look at sensors used in affect detection. This insight is especially helpful for anyone challenged with accurately understanding affective information, like the autistic population. This paper also includes material on sensors and feedback for drivers from populations that may have special needs.Safety 2019, 5, 72 2 of 18 would be challenging to apply in vehicles because of noise sensitivity and data-processing requirements. Beyond engineering considerations, it would be unrealistic to expect daily drivers to apply the EEG sensor before each trip because it would be a new behavior and a time-consuming departure from the driver's routine in a world where it is already difficult to get people to wear seatbelts. Wearable sensing devices such as watches and eyeglasses that fit into a driver's established routine are more practical. Video cameras, reviewed in 2016 by Fernández et al. [1], are practical in the sense that users do not need to activate or touch them, but cameras and microphones also introduce privacy concerns and produce high bandwidth data that requires processing. New soft and textile-embedded sensor formats are promising because they can be fitted to vehicle interiors, and because they can detect safety-relevant activity using body contact data that is not as personally identifiable as video and audio streams. Figure 1 illustrates a pressure sensor for tracking a driver's grip pressure in (a) a body-worn format, and (b) a vehicle surface format. Wearable sensors such as the glove in (a) are more practical for daily use than, for example, blood sampling to measure glucose [2] or cortisol levels, or neural implants to detect brain activity in animal studies. Such invasive sampling can validate conclusions drawn from proxy signals available at the body surface, but a sensor glove is better for daily wear from the user's viewpoint. However, for this grip-tracking application, the driver would have to modify their behavior to put gloves on, would need ...

On Driver Behavior Recognition for Increased Safety: A Roadmap

“…More in detail, stationary sensors are well suited for unobtrusive monitoring, as they are typically installed in the environment (e.g., in the vehicle's cabin) and act without any physical contact with the user: a standard example of a stationary sensor is a camera installed in the cabin. On the other hand, mobile sensors, e.g., wearable, have become practical (thanks to the miniaturization of sensors) and appealing, since nowadays people buy versatile smart devices (e.g., smart watches with sensors for health parameters monitoring) that can be exploited for driver's behavior monitoring and recognition [103].…”

Personal informatics and negative emotions during commuter driving: Effects of data visualization on cardiovascular reactivity & mood

“…For example, there is a positive association between traffic congestion and elevated blood pressure due to journey impedance (Schaeffer et al, 1988;Stokols et al, 1978). The development of driving sensors (Welch, 2019) and lifelogging technology with wearable physiological sensors represents one way to raise awareness of unconscious physiological changes associated with emotion during real-world driving.…”

Transition characteristics of driver's intentions triggered by emotional evolution in two‐lane urban roads

“…Sani et al [8] determined the link between risky driving behaviour and emotion regulation, and found that emotional self‐regulation is related significantly to driving violations. Welch et al [9] provided a review of using sensor technologies to understand how emotions affect dangerous driving habits. Wang et al [10] identified driver's intentions and human‐vehicle interaction by recognizing driver's emotions dynamically.…”