WIT Press

A macroscopic analysis of transport networks: the influence of network design on urban transportation performance

Price

Free (open access)

Paper DOI

10.2495/TDI-V3-N4-331-343

Volume

Volume 3 (2019), Issue 4

Pages

12

Page Range

331 - 343

Author(s)

Ali Enes Dingil, Federico Rupi & Zaneta Stasiskiene

Abstract

This research aims at investigating the direct and indirect influence of network structures on urban transportation performance with a macroscopic perspective. Transport systems are complex – the functional properties of a transportation network can affect mobility patterns which in turn changes the network performance. Understanding the topology of transportation networks is important in order to upgrade transport network design and to improve transportation performance. This paper attempts to determine important network indicators such connectivity, centrality and clustering measures for different network types (road, rail and bike) from 86 urban areas and 32 countries, based on compa- rable, directly observable open-source data such as OpenStreetMap (OSM) and the TomTom congestion database. Relations between indicators are identified through correlation measures. In addition, regression models are calibrated which quantify the relations between infrastructure accessibility (IA) and network indicators and average traffic delay times. The indicator average road connectivity over average road circuity (RCRC), which is proposed in this study, has not been cited before in literature. The main results suggest that the determination of distance-based connectivity of networks is an important proxy to understand road transportation performance. Consequently, two main results were obtained: (1) an increase in average short-distance connectivity of road networks (average closeness centrality and RCRC) eases road congestion, presumably because the network distributes road traffic more homogenously while decreasing low-permeability choke points, (2) an increase of the average short-distance connectivity of networks of alternative modes such as rail or bike (average weighted rail clustering coefficient and average cycle closeness centrality) does alleviate road congestion. In particular, for cities with over 0.4 km per km2  cycleway density, an increase in cycleway closeness centrality decreases road congestion and it does so almost as efficiently as an increase in road infrastructure accessibility. Presumably, well-connected, alternative networks with short and direct routes convince car users to shift to the alternative mode, which decreases road traffic volumes.

Keywords

network design, topology, infrastructure accessibility, congestion, open-source data, OSM, TomTom; transportation performance, transport planning.