A Quantitative Analysis of Superblocks Based on Node Removal

Lingxuan Zhang, Monica Menendez, Bin Shuai

Research output: Contribution to journalArticle

Abstract

Superblocks are city blocks whose size is significantly larger than average. Despite their widespread use across countries such as China, few studies have investigated how these superblocks affect network traffic performance. This paper aims to narrow that gap in knowledge. To that end, we use a grid network emulating a dense city environment. Then, multiple scenarios corresponding to size, location, shape, and number of superblocks are designed by removing nodes and related links. We evaluate network traffic performance by considering the factors of travel distance, travel time, volume-to-capacity ratios on nodes and links, as well as the level of traffic heterogeneity. The results indicate that superblocks with relatively small size (i.e. less than 1/4 of the network size) do not affect traffic significantly. The importance and connectivity of nodes and links related to superblocks are crucial factors affecting the overall traffic performance. In general, the more central the superblock, the larger its influence on the network traffic, except for extremely large superblocks that can significantly affect traffic when located in the periphery, as they lead to high traffic heterogeneities. Rectangular superblocks are more detrimental than square ones. Furthermore, traffic performance can be significantly improved by dividing the superblock into several relatively smaller blocks. Our results should be of direct interest to city-planning decision-makers in dense urban centers.

Original languageEnglish (US)
Article number9086433
Pages (from-to)84996-85006
Number of pages11
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Keywords

  • Urban traffic
  • block size
  • node removal
  • superblocks
  • traffic performance

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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