Abstract

Route scheduling on time-dependent road network is slow due to its problem complexity of Ω(T(|V|log |V|+|E|)), where T is the size of the result's time-dependent function, |V| is the number of vertices and |E| is the number of edges. To make things worse, T grows larger as the route becomes longer or the query time interval becomes bigger, especially for a fastest path profile query whose time interval is 24 hours. In this paper, we aim to answer the fastest path profile query on time-dependent road network faster by extending the 2-hop labeling approach, which is fast in answering shortest distance query on the static graph. However, building an index on a time-dependent graph is both time and space consuming, so currently only online-search approach exist. Apparently, its query answering power is limited by the online searching. To solve this problem, we first propose the time-dependent hop on large road network by partitioning it into smaller sub-graphs. The index is built within and between the partitions, and is retrieved from disk during query answering with the help of sampling. Moreover, we propose an online approximation technique AT-Dijkstra and a bottom-up compression method to further reduce the label size, save construction time and speedup query answering. Experiments on real world road network show that our approach outperforms the state-of-art fastest path index approaches and can speed up the query answering by hundreds of times.

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