Improving transportation networks: Effects of population structure and decision making policies

Abstract

Transportation networks are one of the fundamental tools for human society to work, more so in our globalized world. The importance of a correct, efficient design of a transportation network for a given region or country cannot be overstated. We here study how network design is affected by the geography of the towns or nuclei to be connected, and also by the decision process necessary to choose which connections should be improved (in a generic sense) first. We begin by establishing that Delaunay networks provide an efficient starting point for the network design and at the same time allow us to introduce a computationally amenable model. Subsequent improvements lead to decentralized designs in geographies where towns are more or less homogeneously distributed, whereas radial designs arise when there is a core-periphery distribution of nodes. We also show that optimization of Delaunay networks outperforms that of complete networks at a lower cost, by allowing for a proper selection of the links to improve. In closing, we draw conclusions relevant to policy making applied to designing transportation networks and point our how our study can be useful to identify mechanisms relevant to the historical development of a region.

Complex networks to understand the past: the case of roads in Bourbon Spain

“…Temporary advantages can lead to cities developing permanent advantages such as population size, the establishment of fairs, or simply the development of travel habits that keep traffic on the same routes despite the existence of new alternatives. This means that it may be appropriate from an economic policy point of view to alter the optimum sequence in the construction of the network by prioritizing less efficient sections if a territorial rebalancing is to be achieved (Pablo-Martí and Sánchez 2017 ).…”

“…Once we chose to work using computer simulations, the next step is to establish reasonable criteria for the development of the road network and to observe whether the results arising from our approach under each of the criteria differ significantly from those observed in reality. For this purpose, we rely on an optimal transport network generation model developed by Pablo-Martí and Sánchez ( 2017 ), which allows the selection of the sections to be improved from a preexisting network to achieve maximum benefit from a global perspective based on the individual preferences of each of the agents, the optimization criteria, and the voting system.…”

Local network connectivity optimization: an evaluation of heuristics applied to complex spatial networks, a transportation case study, and a spatial social network

“…S.1E and S.1F ). Planarity is particularly important in many fields and networks generated from Voronoi diagrams and Delaunay triangles have been used in spatial health epidemiology ( Johnson, 2007 ), transportation flow problems ( Steffen & Seyfried, 2010 ; Pablo-Martì & Sánchez, 2017 ), terrain surface modeling ( Floriani, Falcidieno & Pienovi, 1985 ), telecommunications ( Meguerdichian et al, 2001 ), computer networks design ( Liebeherr & Nahas, 2001 ), and hazard avoidance systems in autonomous vehicles ( Anderson, Karumanchi & Iagnemma, 2012 ). Delaunay triangulation maximizes the minimum angles between three nodes to generate planar graphs with consistent network characteristics while Voronoi diagrams, the dual of a Delaunay triangulation, are composed of points and cells such that each cell is closer to its point than any other point ( Delaunay, 1934 ).…”

Comparing spatial networks: A one-size-fits-all efficiency-driven approach

“…Random distribution of nodes in a square show very little fluctuations as indicated by the shadow of the curve. On the contrary, a real network's layout can be far from this distribution, and this sure affects the output of a spatial network model [39]. 6.…”