TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems Using Game Theory

Yin, Zhengyu (University of Southern California) | Jiang, Albert Xin (University of Southern California) | Tambe, Milind (University of Southern California) | Kiekintveld, Christopher (University of Texas at El Paso) | Leyton-Brown, Kevin (University of British Columbia) | Sandholm, Tuomas (Carnegie Mellon University) | Sullivan, John P. (Los Angeles County Sheriff's Department)

AI Magazine 

In proof-of-payment transit systems, passengers are legally required to purchase tickets before entering but are not physically forced to do so. Instead, patrol units move about the transit system, inspecting the tickets of passengers, who face fines if caught fare evading. TRUSTS models the problem of computing patrol strategies as a leader-follower Stackelberg game where the objective is to deter fare evasion and hence maximize revenue. We present an efficient algorithm for computing such patrol strategies and present experimental results using real-world ridership data from the Los Angeles Metro Rail system.