Multi-Modal Route Planning with Transfer Patterns

We examine a way to extend routing using transfer patterns – a state of the art route planning approach for fast routing in public transportation networks – to a multi-modal scenario that allows using public transport, cars, and walking. We specifically examine how to precompute transfer patterns for multi-criteria, multi-modal route planning. When done naively with a Pareto cost model, this leads to a large number of undesirable route variations that render precomputation computationally infeasible. We identify reasons why these variations appear and present ways to reduce the number of variations with appropriate graph models and by applying limits during search. Our results indicate that precomputing multi-modal transfer patterns on large datasets is feasible with such a restricted model.