Adopting Agile methodologies and frameworks in Automotive Industry
Suresh Sureddi · Journal of Artificial Intelligence Machine Learning and Data Science · 2022
The automotive industry is going through a significant transformation due to advancements in technologies like connected cars (V2X technologies), artificial intelligence, autonomous driving and cloud technologies.Due to increasing complexity and functionalities, industry is moving to the concept of software defined vehicle.However, many automotive OEMs are still following the traditional process for building the software for ECUs (Electronic Control Units) over a period of 2-to-3-year life cycle.Especially, in an ECU (Electronic Control Unit), for e.g., Head unit, ADAS (Advanced driver assistant system) or telematics, there is a huge software with numerous requirements and functionalities.Cost of identifying and fixing the defects close to or post SOP (Start of production) involves huge cost and causes program delays.In fact, this would have a significant impact causing delays to vehicle builds.OEMs shall adopt to agile methodology along with the Tier-1 supplier and the product should be built and tested continuously to ensure delivery of a high-quality product.This paper details the pain areas experienced by OEMs due to following the traditional practices and challenges to adopt to agile for software development and then details the benefits of using AGILE and hybrid models to overcome those pain areas and challenges.