Road traffic crashes cause over one million deaths worldwide each year. AI-operated detection of traffic anomalies could help improve emergency response times, though human verification remains necessary. This paper addresses the challenge of enhancing situational awareness in command centers through user-centered visualizations for traffic anomaly detection – not only in urban traffic but also in smart manufacturing environments, such as industrial parking areas or intralogistics operations. Prototypes were developed using Human-Centered Design (HCD) and Design Thinking, focusing on intuitive visual representations that support quick human verification and response. A quantitative user study compared the prototypes with existing approaches, showing that the new visualizations significantly improved the accuracy of anomaly detection compared to the currently used version.