Abstract:
The user experience reveals valuable information about the surrounding environment and how individuals feel about the moment emotionally. Researchers have shown the impact of emotions on decision-making, including driving-related decisions in a positive mood tended to maintain a safer driving performance. With the development of intelligent human-machine systems, emotion recognition has become emerging topics for transport-related research works. The methodlogy recognizes the facial expressions of vehicle drivers to map drivers’ experiences with Google Maps data. Findings show how intersections and traffic conditions affect the driver’s emotional changes during the driving situation. This new information layer can be use to identify driver feedback during different traffic and as a valuable dataset to technological enhancements to play a major role in better driving performance and fewer accidents.
