Definição de testes automáticos para a detecção de problemas de “tela preta” na validação de head units

Abstract

This study presents an innovative approach to automated testing aimed at validating automotive infotainment systems, focusing on detecting the critical failure known as the “black screen” in multimedia Head Units. The proposed solution replaces manual processes, traditionally costly and error-prone, with automated methods that ensure greater robustness, repeatability, and scalability throughout the validation cycle. Three complementary scenarios were developed: (i) automatic verification of the rear camera image using computer vision techniques with Python and OpenCV integrated into the CANalyzer environment via CAPL; (ii) monitoring Head Unit startup through simulated ignition cycles, employing Arduino, relays, and light sensors for accurate detection of intermittent failures; and (iii) advanced validation with automated shutdown, incorporating the Dobot Magician robotic arm for physical interaction with the system interface. The methodology includes building a modular test bench that integrates hardware and software, capable of executing thousands of continuous cycles without human intervention. Results demonstrated high efficiency in detecting visual failures, significant reduction in validation time, and improved process reliability, highlighting the potential of automation as a strategic tool to raise quality standards in automotive embedded systems.

Keywords: automotive validation; Head Unit; black screen; infotainment system; test automation; test bench; Arduino IDE; OpenCV; CAPL; Dobot Magician.