Markus Straub

Semantically Enriched Multi-Modal Routing

We present an innovative extension to routing: intention-oriented routing which is a direct result of combining classical routing-services with Semantic Web technologies. Thereby, the intention of a user can be easily incorporated into route planning. We highlight two use cases where this hybridization is of great significance: neighborhood routing, where a neighborhood can be explored (e.g. searching for events around your place) and via routing, where errands should be run along a route (e.g. buying the ingredients for dinner on your way home). We outline the combination of different methods to achieve these services, and demonstrate the emerging framework on two case studies, with a prototype extending in-use routing services.

On the way to a multi-modal energy-efficient route

Within this paper, we present a flexible and expandable routing framework capable of finding multi-modal and inter-modal energy-efficient routes incorporating, among others, transportation modes such as public transport, electric vehicles, car-sharing, bike-sharing and walking. In contrast to conventional trip planning services, the proposed framework can evaluate routes not only with respect to travel distance or travel time but also with respect to energy used. In addition, range limitation by electric vehicles is incorporated into the routing request such that range-safety can be provided.

Is OSM Good Enough for Vehicle Routing? A Study Comparing Street Networks in Vienna

As a result of OpenStreetMap’s (OSM) openness and wide availability, there is increasing interest in using OSM street network data in routing applications. But due to the heterogeneous nature of Volunteered Geographic Information (VGI) in general and OSM in particular, there is no universally valid answer to questions about the quality of these data sources. In this paper we address the lack of systematic analyses of the quality of the OSM street network for vehicle routing and the effects of using OSM rather than proprietary street networks in vehicle routing applications. We propose a method to evaluate the quality of street networks for vehicle routing purposes which compares relevant street network features as well as computed route lengths and geometries using the Hausdorff distance. The results of our case study comparing OSM and the official Austrian reference graph in the city of Vienna show close agreement of one-way street and turn restriction information. Comparisons of 99,000 route pairs with an average length of 6,812 m show promising results for vehicle routing applications with OSM, especially for route length computation where we found median absolute length differences of 1.0 %.

Estimating travel times from static map attributes

Estimating accurate travel times on road networks is a prerequisite for many mobility related applications such as transportation planning, dynamic intermodal routing or logistics. Two widely used methods are (1) the trivial but inaccurate calculation of travel times using static speeds taken from road maps and (2) the use of historic time series calculated from rich data sets. For the second method extensive measurement campaigns are required. In this paper we present a novel approach to estimate realistic travel times exclusively from static map coefficients without the need for further data collection. Our method uses a linear regression model to estimate the diurnal variation of travel times for cars in urban and interurban areas. We discuss the model which has been developed and calibrated for the city of Vienna, Austria, and demonstrate the transferability of the model to a different city.