Detecting lost cargo on highways poses a critical and stringent challenge for Level 3 Autonomous Driving Systems (ADS), especially considering UN 157 (ALKS) requirements. This presentation will examine how functional safety and SOTIF considerations further complicate this task. We'll explore how to derive realistic acceptance criteria based on real-world accident data and translate them into concrete perception validation targets. The analysis will then map various collision avoidance maneuvers to their corresponding perception needs. Finally, we will evaluate the suitability of different sensor technologies to effectively meet these identified perception requirements for robust lost cargo detection.