Modeling schedule recovery processes in transit operations for bus arrival time prediction

Many existing algorithms for bus arrival time prediction assume that buses travel at free-flow speed in the absence of congestion. As a result, delay incurred at one stop would propagate to the downstream stops in the same magnitude. In reality, good bus operators often constantly adjust their speeds to keep the bus on schedule. This paper formulates a Markov chain model for bus arrival time prediction that explicitly captures the behavior of bus operators in pursuing schedule recovery. The model exhibits some desirable properties in capturing the schedule recovery process and guarantees provision of the schedule information if realtime information suddenly becomes unavailable. The proposed model can be embedded into a transit arrival time estimation model for transit information systems.