Improve Customer Experience in Automotive Industry Through Advanced Driver Assistant Systems

This manuscript explores the impact of emerging technologies in the automotive industry, specifically focusing on enhancing the customer experience and driving safety. The study investigates the advantages of incorporating emotion-tracking technologies like facial coding and affective computing algorithms into Advanced Driver Assistant Systems (ADAS). A simulated experiment involving 20 participants uses facial coding systems to track emotional responses and statistical analysis to establish a connection between emotional states and driving behaviour. The research reveals a strong correlation between negative emotions and unsafe driving behaviour. The study proposes an ADAS system that utilizes emotional tracking to provide real-time feedback to drivers and adjust the driving environment accordingly. Although the study highlights the potential benefits of emotional tracking technology, it emphasizes the need for further research to refine and validate the proposed ADAS system and address privacy concerns. Overall, this research offers an innovative approach to improving driving experience and safety, contributing to integrating new technologies in the automotive sector

A Study on Recent Developments and Issues with Obstacle Detection Systems for Automated Vehicles

This paper reviews current developments and discusses some critical issues with obstacle detection systems for automated vehicles. The concept of autonomous driving is the driver towards future mobility. Obstacle detection systems play a crucial role in implementing and deploying autonomous driving on our roads and city streets. The current review looks at technology and existing systems for obstacle detection. Specifically, we look at the performance of LIDAR, RADAR, vision cameras, ultrasonic sensors, and IR and review their capabilities and behaviour in a number of different situations: during daytime, at night, in extreme weather conditions, in urban areas, in the presence of smooths surfaces, in situations where emergency service vehicles need to be detected and recognised, and in situations where potholes need to be observed and measured. It is suggested that combining different technologies for obstacle detection gives a more accurate representation of the driving environment. In particular, when looking at technological solutions for obstacle detection in extreme weather conditions (rain, snow, fog), and in some specific situations in urban areas (shadows, reflections, potholes, insufficient illumination), although already quite advanced, the current developments appear to be not sophisticated enough to guarantee 100% precision and accuracy, hence further valiant effort is needed