The article examines the problem of training unmanned aerial vehicle operators to support urban public-safety tasks carried out by police units, where effectiveness depends not only on piloting skills but also on anticipation, situational awareness, the ability to filter informational noise, and decision-making under time pressure and deliberate counteractions by offenders (communication interference, GPS spoofing, concealment). The limitations of traditional linear programs are shown: they often produce fragmented professional thinking and cognitive overload with a tunnel-vision effect. An adaptive scenario-modeling method is proposed and tested, in which an intelligent simulator dynamically changes the complexity of inputs (communication interference, weather factors, dense urban environment, regulatory flight constraints, navigation failures) depending on the trainee’s current performance, keeping training within an optimal difficulty zone; reflexive debriefing based on video review and eye-tracking analysis is also used. Compared with traditional training (equal-size samples), applied indicators improve markedly: the time to detect an object of interest decreases from 18,42 to 12,15 s, reaction to navigation failure decreases from 5,87 to 3,22 s, critical errors drop from 3,12 to 1,45 per 10 flights, and overall task success increases from 0.642 to 0.815; resilience to informational noise rises (from 5.34 to 7.89 points) and performance variability decreases, indicating higher skill stability. Psychophysiological monitoring (heart rate variability, tremor, pulse) shows a lower “cost” of activity in the stress phase, while delayed testing after three months records higher retention of integrative competencies (85–94% versus 59,8–78,3%). Training intensification is demonstrated: the required flight time to reach the qualification level decreases from 48.5 to 31.2 hours, successful flights per 10 hours of practice increase from 6,4 to 11,8, and early accident rate decreases from 28,4% to 12,7%, which is interpreted as the formation of situational plasticity and a shift toward parallel processing of operationally relevant information.