Ad hoc matching of vectorial road networks

Abstract

In integration of road maps modeled as road vector data, the main task is matching pairs of objects that represent, in different maps, the same segment of a real-world road. In an ad hoc integration, the matching is done for a specific need and, thus, is performed in real time, where only a limited preprocessing is possible. Usually, ad hoc integration is performed as part of some interaction with a user and, hence, the matching algorithm is required to complete its task in time that is short enough for human users to provide feedback to the application, that is, in no more than a few seconds. Such interaction is typical of services on the World Wide Web and to applications in car-navigation systems or in handheld devices.

Several algorithms were proposed in the past for matching road vector data; however, these algorithms are not efficient enough for ad hoc integration. This article presents algorithms for ad hoc integration of maps in which roads are represented as polylines. The main novelty of these algorithms is in using only the locations of the endpoints of the polylines rather than trying to match whole lines. The efficiency of the algorithms is shown both analytically and experimentally. In particular, these algorithms do not require the existence of a spatial index, and they are more efficient than an alternative approach based on using a grid index. Extensive experiments using various maps of three different cities show that our approach to matching road networks is efficient and accurate (i.e., it provides high recall and precision).

General Terms:Algorithms, Experimentation

Keywords:

• road map
• spatial network
• integration
• matching polylines
• location-based join
• corresponding objects
• conflation

Acknowledgements

The work of Yaron Kanza and Yehoshua Sagiv was partially supported by The Israeli Ministry of Science and Technology (Grant 3-6472).

Notes

1. DCPNY (LION): http://www.ci.nyc.ny.us/html/dcp/home.html

2. CUGIR: http://cugir.mannlib.cornell.edu

3. SOI: http://www.mapi.gov.il/

4. MAPA: http://www.mapa.co.il/

5.