Compression of Digital Road Networks

Abstract

In the consumer market, there has been an increasing interest in portable navigation systems in the last few years. These systems usually work on digital map databases stored on SD cards. As the price for these SD cards heavily depends on their capacity and as digital map databases are rather space-consuming, relatively high hardware costs go along with digital map databases covering large areas like Europe or the USA. In this paper, we propose new techniques for the compact storage of the most important part of these databases, i.e., the road network data. Our solution applies appropriate techniques from combinatorial optimization, e.g., adapted solutions for the minimum bandwidth problem, and from data mining, e.g., clustering based on suitable distance measures. In a detailed experimental evaluation based on real-world data, we demonstrate the characteristics and benefits of our new approaches.

This work was supported in part by KOSEF grant No. R01-2006-000-10536-0(2007) and in part by the Brain Korea 21 Project in 2007.