GTFS (General Transit Feed Specification) is a standard of Google for public transportation schedules. The specification describes stops, routes, dates, trips, etc. one or more company city country. Examining feed it can be considered as graph. In addition in the last decades new database management systems was born order to support big data era and/or help write program codes. Their collective...

We study an important practical aspect of the route planning problem in real-world road networks – maneuvers. Informally, maneuvers represent various irregularities of the road network graph such as turnprohibitions, traffic light delays, round-abouts, forbidden passages and so on. We propose a generalized model which can handle arbitrarily complex (and even negative) maneuvers, and outline how...

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while ...

It is often assumed that three-dimensional topographic maps provide more effective route planning, navigation, orientation, and way-finding results then traditional two-dimensional representations. The research reported here investigates whether three-dimensional spatial mappings provide better support for route planning than two-dimensional representations. In a set of experiments performed as...

Computing optimal routes in road networks is one of the showpieces of realworld applications of algorithmics. In principle, we could use Dijkstra’s algorithm—the ‘classic’ solution from graph theory. But for large road networks this would be far too slow. Therefore, there is considerable interest in speedup techniques, which typically invest some time into a preprocessing step in order to gener...

One of the most ubiquitous AI applications is vehicle route planning. While state-of-the-art systems take into account current traffic conditions or historic traffic data, current planning approaches ignore the impact of their own plans on the future traffic conditions. We present a novel algorithm for self-aware route planning that uses the routes it plans for current vehicle traffic to more a...

Algorithms for route planning in transportation networks have recently undergone a rapid development, leading to methods that are up to one million times faster than Dijkstra’s algorithm. We outline ideas, algorithms, implementations, and experimental methods behind this development. We also explain why the story is not over yet because dynamically changing networks, flexible objective function...