A PostGIS-based pedestrian way finding module using OpenStreetMap data

Jianghua Zheng, Zhangang Zhang, Blazej Ciepluch, Adam C. Winstanley, Peter Mooney, Ricky Jacob
2013 2013 21st International Conference on Geoinformatics  
Open source GIS (OSG) is a fast developing field. When OSG is combined with Web2.0 and Service Orientated Architectures (SOA) technologies and more applications of Public Participation GIS, it has many advantages over commercial GIS software. Despite this, OSG still needs more improvement in terms of stability and functional integrity. In order to build more robust, more practical, and more functional LBS applications, this research investigates pedestrian-orientated wayfinding, with special
more » ... uirements as its study topic. We describe some Web 2.0 routing APIs which can be easily used to provide general shortest path planning. However, these APIs cannot provide guidance services for specific user groups with special requirements, such as tourists in small towns. We take Maynooth as case-study. Maynooth is the only University town in Ireland with a population of approximately 20,000. This research uses OpenStreetMap (OSM) as spatial data source. OSM contains very spatially rich dataset. It is stored and managed in PostGIS/PostgreSQL. Through previous work on LBS applications using the CloudMade Routing API and OSM data, we present a Java-based wayfinding module implementing a restricted area version of Dijkstra algorithm. A set of native PostGIS spatial functions are used to improve performance of the routing algorithm. Results from our wayfinding algorithm are presented and compared with those obtained by using the CloudMade Routing API. Our results are promising and show that this special version of Dijkstra algorithm can take advantage of the spatial data stored in OSM. This work provides a base to build more effective pedestrian wayfinding algorithms which can be implemented in open source software and open APIs. This approach provides a feasible and economical LBS solution for small towns, villages and tourism regions outside larger cities.
doi:10.1109/geoinformatics.2013.6626049 dblp:conf/geoinformatics/ZhengZCWMJ13 fatcat:bjtgdcetpvbbjdwhlopq7s3j34