Abstract

In the future, vehicles will gather more and more spatial information about their environment, using on-board sensors such as cameras and laser scanners. Using this data, e.g. for localization, requires highly accurate maps with a higher level of detail than provided by today's maps. Producing those maps can only be realized economically if the information is obtained fully automatically. It is our goal to investigate the creation of intermediate level maps containing geo-referenced landmarks, which are suitable for the specific purpose of localization. To evaluate this approach, we acquired a dense laser scan of a 22 km scene, using a mobile mapping system. From this scan, we automatically extracted pole-like structures, such as street and traffic lights, which form our pole database. To assess the accuracy, ground truth was obtained for a selected inner-city junction by a terrestrial survey. In order to evaluate the usefulness of this database for localization purposes, we obtained a second scan, using a robotic vehicle equipped with an automotive-grade laser scanner. We extracted poles from this scan as well and employed a local pole matching algorithm to improve the vehicle's position. Document type: Part of book or chapter of book

Abstract

The 'backhaul problem' is characterized by an imbalance in transport flows between locations. This problem is usually studied in a perfectly competitive framework, which essentially predicts that when the imbalance is sufficiently large, the freight price of transport from low demand regions to high demand regions, the so-called backhaul price, drops to zero. This result is inconsistent with empirical observations. In this paper, we develop a matching model to address this inconsistency. We argue that market friction, through search imperfections due to lack of information by carriers on the (future) demand for transport by customers, may play an important role in the determination of backhaul prices. We demonstrate that carriers are at least compensated for the time they search for customers, so the backhaul price is in general positive. The matching model is numerically applied to the inland navigation shipping market in the Rhine river area in Western-Europe. We also analyse the effects of increases in transport costs on transport flows and backhaul prices, e.g. due to climate changes.

Abstract

In Germany, the data of the Open Street Map project has become available as an alternative to proprietary road networks in commercial business geomatics software, and their customers are wondering whether the quality may be sufficient. This paper describes an implemented methodology to compare OSM street data with those of Navteq for all populated roads in Germany. As a unique feature, the presented methodology is based on a matching between the street objects of OSM and Navteq, and all steps are fully automated so that they can be applied to updated versions of both data sets. While there are considerable qualitative differences between regions, towns, and street categories, at a national level the relative completeness of objects, their relative precision and the relative completeness of names are high enough for maps. However, other attributes, which are needed for the computation of catchment areas, are still relatively incomplete.