Distance Oracles for Time-Dependent Networks

Abstract

We present the first approximate distance oracle for sparse directed networks with time-dependent arc-travel-times determined by continuous, piecewise linear, positive functions possessing the FIFO property. Our approach precomputes $$(1+\varepsilon )$$(1+?)-approximate distance summaries from selected landmark vertices to all other vertices in the network. Our oracle uses subquadratic space and time preprocessing, and provides two sublinear-time query algorithms that deliver constant and $$(1+\sigma )$$(1+?)-approximate shortest-travel-times, respectively, for arbitrary origin---destination pairs in the network, for any constant $$\sigma > \varepsilon $$?>?. Our oracle is based only on the sparsity of the network, along with two quite natural assumptions about travel-time functions which allow the smooth transition towards asymmetric and time-dependent distance metrics.