Speed Traps and Ticket Dodging: Multiagent Decision-Making on Transportation Networks

We model a transportation network where agents of different types operate with conflicting objectives: drivers want to drive at high speeds to reach their destination faster, while police agents want to prevent unlawful speeding. Police units have to efficiently allocate their limited resources to monitor roads and catch speeders, who try to avoid being caught. Assuming that police and drivers make strategic choices, the problem can be modeled as a game-theoretic problem. We describe the models and algorithms we developed and validate them on different maps.