Dennis Luxen

Real-time routing with OpenStreetMap data

Routing services on the web and on hand-held devices have become ubiquitous in the past couple of years. Websites like Bing or Google Maps allow users to find routes between arbitrary locations comfortably in no time. Likewise onboard navigation units belong to the off-the-shelf equipment of virtually any new car. The amount of volunteered spatial data of the OpenStreetMap project has increased rapidly in the past five years. In many areas, the data quality already matches that of commercial map data, if not outright surpass it. We demonstrate both a server and a hand-held device based implementation working with OpenStreetMap data. Both applications provide real-time and exact shortest path computation on continental sized networks with millions of street segments. We also demonstrate sophisticated real-time features like draggable routes and round-trip planning.

Fast Detour Computation for Ride Sharing

Ride sharing becomes more and more popular not least because internet services help matching offers and request. However, current systems use a rather simple-minded functionality allowing to search for the origin and destination city, sometimes enriched with radial search around the cities. We show that theses services can be substantially improved using innovative route planning algorithms. More concretely, we generalize previous static algorithms for many-to-many routing to a dynamic setting and develop an additional pruning strategy. With these measures it becomes possible to match each request to

Transit Node Routing Reconsidered

n

Distributed time-dependent contraction hierarchies

offers using

Candidate Sets for Alternative Routes in Road Networks

2n+1

Candidate sets for alternative routes in road networks

exact travel time computations in a large road network in a fraction of a microsecond per offer. For requests spread over Germany according to population density, we are able to reduce the number of failing entries substantially. We are able to find a reasonable match for more than 60% of the failing entries left by contemporary matching strategies. Additionally, we halve the average waste of resources in the matches found compared to radial search.

Improved fast similarity search in dictionaries

Transit Node Routing (TNR) is a fast and exact distance oracle for road networks. We show several new results for TNR. First, we give a surprisingly simple implementation fully based on contraction hierarchies that speeds up preprocessing by an order of magnitude approaching the time for just finding a contraction hierarchy (which alone has two orders of magnitude larger query time). We also develop a very effective purely graph theoretical locality filter without any compromise in query times. Finally, we show that a specialization to the online many-to-one (or one-to-many) shortest path problem.

Firm growth and the spatial impact of geolocated external factors: Empirical evidence for German manufacturing firms

Server based route planning in road networks is now powerful enough to find quickest paths in a matter of milliseconds, even if detailed information on time-dependent travel times is taken into account. However this requires huge amounts of memory on each query server and hours of preprocessing even for a medium sized country like Germany. This is a problem since global internet companies would like to work with transcontinental networks, detailed models of intersections, and regular re-preprocessing that takes the current traffic situation into account. By giving a distributed memory parallelization of the arguably best current technique – time-dependent contraction hierarchies, we remove these bottlenecks. For example, on a medium size network 64 processes accelerate preprocessing by a factor of 28 to 160 seconds, reduce per process memory consumption by a factor of 10.5 and increase query throughput by a factor of 25.

Hierarchy decomposition for faster user equilibria on road networks

We study the computation of good alternatives to the shortest path in road networks. Our approach is based on single via-node routing on top of contraction hierarchies and achieves superior quality and efficiency compared to previous methods. We present a fast preprocessing method for computing multiple good alternatives and apply this result in an online setting. This setting makes our result applicable in legacy systems with negligible memory overhead. An extensive experimental analysis on a continental-sized real- world road network proves the performance of our algorithm and supports the general systematic algorithm engineering approach. We also show how to combine our results with the competing concept of alternative graphs that encode many alternative paths at once.

Efficient route compression for hybrid route planning

We present a fast algorithm with preprocessing for computing multiple good alternative routes in road networks. Our approach is based on single via node routing on top of Contraction Hierarchies and achieves superior quality and efficiency compared to previous methods. The algorithm has neglectable memory overhead.