driver through high crime areas of a city at night, or through unsafe roads in order to save a few minutes of travel time.
A road network partitioning algorithm was introduced. The algorithm uses the hierarchy of roads to segment the network into areas that are enclosed by large roads. This method yields very natural partitions, where large areas are observed at regions with low road densities, and much finer areas are observed at dense regions such as big cities. Ar- eas are a central concept to route planning, as they pro- vide the basis for hierarchical path finding, area level pre- computation, and area sensitive support of driving patterns.
We showed that significant query processing gains can be obtained, by following the principle that drivers tend to travel through the largest roads available for the trip, unless small roads along the way have a speed advantage over the large ones. We also presented a method to identify such fast roads, and efficiently incorporate them into route planning. In our experimental study we demonstrated that incorpo- rating fast small roads into the hierarchical path finding al- gorithm can significantly improve the quality of routes.
Through an empirical study, on real road networks, us- ing a realistic traffic information, we verify the large perfor- mance gains of our algorithms vs. competing methods, while showing that computed routes are close to optimal.
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