Enhancing Accessibility of Rural Populations through Vehicle-based Services
Clemens Pizzinini, Nils Justen, David Ziegler, Markus Lienkamp

TL;DR
This paper presents an integrated GIS-based methodology to optimize mobile service stops, improving access to healthcare and education for rural populations in Sub-Saharan Africa, demonstrated through a case study in Ethiopia.
Contribution
It introduces a novel approach combining GIS data, demand modeling, and clustering algorithms to optimize mobile facility deployment in rural areas.
Findings
Mobile facilities can meet up to 62% of unmet demand.
The approach reduces average travel distances to 5 km.
It provides actionable insights for policymakers and fleet operators.
Abstract
Improving access to essential public services like healthcare and education is crucial for human development, particularly in rural Sub-Saharan Africa. However, limited reliable transportation and sparse public facilities present significant challenges. Mobile facilities like mobile clinics offer a cost-effective solution to enhance spatial accessibility for the rural population.Public authorities require detailed demand distribution data to allocate resources efficiently and maximize the impact of mobile facilities. This includes determining optimal vehicle service stop locations and estimating operational costs. Our integrated approach utilizes GIS data and an accessibility scaling factor to assess spatial accessibility for rural populations. We tailor demand structures to account for remote and underserved populations. To reduce average travel distances to 5 km, we apply a clustering…
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Taxonomy
TopicsTransportation and Mobility Innovations
