Optimal Cruiser-Drone Traffic Enforcement Under Energy Limitation

Optimal Cruiser-Drone Traffic Enforcement Under Energy Limitation

Ariel Rosenfeld, Oleg Maksimov, Sarit Kraus

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Main track. Pages 3848-3855. https://doi.org/10.24963/ijcai.2018/535

Drones can assist in mitigating traffic accidents by deterring reckless drivers, leveraging their flexible mobility. In the real world, drones are fundamentally limited by their battery/fuel capacity and have to be replenished during long operations. In this paper, we propose a novel approach where police cruisers act as mobile replenishment providers in addition to their traffic enforcement duties. We propose a binary integer linear program for determining the optimal rendezvous cruiser-drone enforcement policy which guarantees that all drones are replenished on time and minimizes the likelihood of accidents. In an extensive empirical evaluation, we first show that human drivers are expected to react to traffic enforcement drones in a similar fashion to how they react to police cruisers using a first-of-its-kind human study in realistic simulated driving. Then, we show that our proposed approach significantly outperforms the common practice of constructing stationary replenishment installations using both synthetic and real world road networks.
Keywords:
Multidisciplinary Topics and Applications: Security and Privacy
Multidisciplinary Topics and Applications: Multidisciplinary Topics and Applications