D6.4 - Workshop

As part of the dissemination activities around SimpleFleet, project partners have organized workshops to which they invite interested developers to test the SimpleFleet framework. These events will be organized at the local level, i.e., specifically targeting developers in Berlin, Athens or Vienna

Crowdsourcing turning restrictions for OpenStreetMap

The abundance of GPS tracking data due to the emergence and popularity of smartphones has fuelled significant research around GPS trajectories and map-matching algorithms. Unfortunately, none of this previous research addresses the issue of identifying turning restrictions in the underlying road network graph. Our latest research endeavour remedies this, by proposing a novel, straightforward and effective way to infer turning restrictions for OpenStreetMap data, by utilizing historic map-matching results from an existing fleet management service. Our experimental evaluation based on the results acquired for three European cities within an one-year period, proves the robustness and credibility of our method

Exploiting Road Network Properties in Efficient Shortest‐Path Computation

The essential elements of any navigation system are a shortest‐path algorithm and a map dataset. When seen in the light of the basic requirement of such a system, to provide high quality navigation solutions fast, algorithms have to be efficient and road networks have to be up‐to‐date. The contribution of this work is two‐fold. First, the HBA * algorithm, an efficient shortest‐path algorithm, is presented that mimics human driving behavior by exploiting road network hierarchies. HBA * is a fast algorithm that produces high quality routes. Second, in a thorough performance study dynamic, travel times are introduced to replace the unreliable static speed types currently used in connection with road network datasets. Dynamic travel times are derived from large quantities of historic vehicle tracking data. The integrated result, fast algorithms using accurate data, is empirically evaluated using actual road network datasets and related dynamic travel time data