  Police officer presence at an intersection discourages a potential traffic
violator from violating the law. It also alerts the motorists' consciousness to
take precaution and follow the rules. However, due to the abundant
intersections and shortage of human resources, it is not possible to assign a
police officer to every intersection. In this paper, we propose an intelligent
and optimal policing strategy for traffic violation prevention. Our model
consists of a specific number of targeted intersections and two police officers
with no prior knowledge on the number of the traffic violations in the
designated intersections. At each time interval, the proposed strategy, assigns
the two police officers to different intersections such that at the end of the
time horizon, maximum traffic violation prevention is achieved. Our proposed
methodology adapts the PROLA (Play and Random Observe Learning Algorithm)
algorithm [1] to achieve an optimal traffic violation prevention strategy.
Finally, we conduct a case study to evaluate and demonstrate the performance of
the proposed method.
