Dependency on Complex Algorithms for Decision Making in Vehicle Technology

In recent years, the automotive industry has witnessed a surge in the development of advanced vehicle technologies that heavily rely on complex algorithms for decision making. These technologies include advanced driver assistance systems (ADAS), autonomous driving systems, and connected vehicle systems, among others. While these technologies have the potential to improve safety, reduce accidents, and enhance the overall driving experience, they also pose significant challenges related to their reliance on complex algorithms. The increasing dependency on complex algorithms for decision making in vehicle technology raises several concerns related to the reliability, transparency, and accountability of these systems. One of the primary concerns is the potential for errors or malfunctions in the algorithms that could lead to accidents, injuries, or fatalities. Another concern is the lack of transparency in how these algorithms make decisions, which can make it difficult for users to understand and trust the technology. To address these concerns, there is a need for greater collaboration between industry stakeholders, regulators, and researchers to develop robust testing and validation processes for complex algorithms used in vehicle technology. Additionally, there is a need for greater transparency and accountability in how these algorithms make decisions, such as the use of explainable AI techniques that can provide insights into the decisionmaking process. Overall, the growing dependence on complex algorithms for decision making in vehicle technology presents both opportunities and challenges for the automotive industry. This paper aims to details by addressing the concerns related to these algorithms, stakeholders can work towards realizing the full potential of these technologies while ensuring safety and reliability for users.