arXiv:2611.13214v1 Announce Type: new Abstract: Automotive radars operating in dense traffic environments may experience significant mutual interference, potentially degrading sensing reliability for advanced driver assistance systems (ADAS). This issue motivates the development of techniques to mitigate interference among multiple radar-equipped vehicles sharing the same spectrum. This paper investigates interference mitigation strategies for uncoordinated radar networks through system-level simulation. Two approaches are considered: frame-by-frame collision avoidance (FbF-CA), which exploits idle intervals to measure the perceived interference and possibly adapt the operating frequency, and frame-by-frame collision detection (FbF-CD), which estimates interference during transmission based on observed chirp collisions. An event-driven radar network simulator is used to model realistic highway traffic and radar interactions. Results show that collision avoidance provides higher robustness when a larger bandwidth is available, while collision detection is more effective under bandwidth-limited conditions. The analysis highlights the trade-off between collision avoidance and collision detection mitigation strategies and provides design insights for scalable automotive radar deployments.