Efficient traffic enforcement is an essential, yet complex, component in preventing road accidents. In this paper, we present a novel model and an optimizing algorithm for mitigating some of the computational challenges of real-world traffic enforcement allocation in large road networks. Our approach allows for scalable, coupled and non-Markovian optimization of multiple police units and guarantees optimality. In an extensive empirical evaluation we show that our approach favorably compares to several baseline solutions achieving a significant speed-up, using both synthetic and real-world road networks.