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 nonMarkovian 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 realworld road networks.