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Creative Commons Attribution-Share Alike 4.0 License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.

Abstract

The recent proliferation of online/desktop/mobile open source geographic information systems (GIS)routing tools such as qgis road graph plugin (QRG), open street routing machine (OSRM), google maps engine (GME), graphhopper (GH), and Osm And has led to the need to provide a method for comparatively evaluating the strength and weakness of these routing tools. This is crucial in view of its implication on the prospect and otherwise of routing related projects such as supply chain logistics, supply/delivery operations, and emergency services, among others. In this paper, comparative evaluation of these tools has been carried out using drive test survey and desktop routing estimation with respect to routine vaccine delivery in Kano, Nigeria. Kano state being one of the states in Nigeria with huge burden of health challenges with records of 3062 maternal death between 2005 – 2010(Ibrahim, 2014) . Thus vaccine delivery is one of such healthcare delivery programmes used to addressing some of these health challenges. The primary objective of this paper is to demonstrate comparative advantage of using open sourceGIS routing tools to optimize vaccine delivery process such that there would be significant reduction in logistics, manpower and cost associated with routine vaccine delivery. The capacity of the selected open source GIS routing tools was evaluated against this backdrop. Hence drive test survey was used to define the benchmark for determine the best rank among these desktop routing tools. The drive test survey was carried on selected number of delivery routes and the results were compared with values derived from desktop routing estimation using these tools. Two rounds of drive test survey were carried out for the delivery routes and an average was considered in order to minimum possible error associated with possible inconsistent in driving behavior. Significant discrepancies were observed in the outputs derived between desktop (QRG), online (OSRM, GME, GH) and mobile (Osm And) routing platforms. OSM vector base map was used across all the routing tools except GME.The overall outcome indicated QRG had the highest cumulative error margin of 67.52km while the lowest was reported for GraphHoper (46.17km) using same OSM base map. This is an indication that the routing algorithm used is not the same. When compared with GME that uses different base map, the cumulative error margin is very close (QRG – 67.52, GME – 55.99), an indication that similar routing algorithm has been used. Drive test outcome may not be sufficient to determine best or otherwise routing tool, it may be appropriate to consider other valuable criteria for the purpose of ranking these tools. Hence, those criteria were not limited to drive test/routing output error margin, others include capacity for multiple routing, base map completeness/content, support for traffic input, routing platform, and alternative routing option. With these considerations, QRG was ranked 1st. while OsmAnd (5) was least ranked. GME and GH had same ranking (2). QRG was ranked above other OSM based routing tools because it uses desktop platform and a capacity to integrate traffic input. It was ranked above GME majorly because of its robust OSM base map compared to google base map.

DOI

https://doi.org/10.7275/R50P0X7R

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