In some urban transit systems, passengers are legally required to purchase tickets before entering but are not physically forced to do so. Instead, patrol units move about through the transit system, inspecting tickets of passengers, who face fines for fare evasion. This setting yields the problem of computing optimal patrol strategies satisfying certain temporal and spacial constraints, to deter fare evasion and hence maximize revenue. In this paper we propose an initial model of this problem as a leader-follower Stackelberg game. We then formulate an LP relaxation of this problem and present initial experimental results using real-world ridership data from the Los Angeles Metro Rail system.
['Albert Xin Jiang', 'Zhengyu Yin', 'Matthew P. Johnson', 'Milind Tambe', 'Christopher Kiekintveld', 'Kevin Leyton-Brown', 'Tuomas Sandholm']
Towards optimal patrol strategies for fare inspection in transit systems