Resumen
Journey planning is a key process in public transport, where travelers get informed how to make the best use of a given public transport system for their individual travel needs. A common trait of most available journey planners is that they assume deterministic travel times, but vehicles in public transport often deviate from their schedule. The present paper investigates the problem of finding journey plans in a stochastic environment. To fully exploit the flexibility inherent in multi-service public transport systems, we propose to use the concept of a routing policy instead of a linear journey plan. A policy is a state-dependent routing advice which specifies a set of services at each location from which the traveler is recommended to take the one that arrives first. We consider current time dependent policies, that is, when the routing advice at a given location is based solely on the current time. We propose two heuristic solutions that find routing policies that perform better than deterministic journey plans. A numerical comparison shows the achievable gains when applying the different heuristic policies based on extensive simulations on the public transport network of Budapest. The results show that the probability of arriving on time to a given destination can be significantly improved by following a policy instead of a linear travel plan.