Cybersecurity in Automotive: Current Trends, Regulations, and Future Paths
This article shares the findings and conclusions of the rinf.tech Automotive Cybersecurity study.
This article shares the findings and conclusions of the rinf.tech Automotive Cybersecurity study.
GoodFirms Features rinf.tech Among Top 30 Automotive Software Companies 2022 We’re excited to announce that one of the leading B2B research and review platforms, GoodFirms
This article provides an overview of the Experience Per Mile (EPM) Index as a new measurement of mobility experiences and how it can affect automotive software development.
This article addresses how HIL Testing works and helps bridge the gap between the automotive software component models and an actual object like a car.
This article explores how AGL platform facilitates and streamlines the development of infotainment and instrument cluster solutions.
This article addresses the closed-loop approach to virtual AR-HUD development and examines the key benefits that automotive software engineers can get from it.
This article looks at certain use cases to better understand how machine learning (ML) and deep learning (DL) technologies are used to build advanced systems for different levels of vehicle automation.
Check out what it takes to build a highly effective digital cockpit solution and how it can benefit both car makers and Tier1 providers.
Hardware-in-the-Loop (HIL) Automation Testing Client: global manufacturer of agricultural equipment Technology SW tools: MATLAB Simulink, Vector CANoe, TwinCAT Programming scripting automation languages: Python, CAPL HIL