Travel in city road networks follows similar transport trade-off principles to neural and plant arbors

Suen, J. Y., Navlakha, S. (May 2019) Travel in city road networks follows similar transport trade-off principles to neural and plant arbors. J R Soc Interface, 16 (154). p. 20190041. ISSN 1742-5662 (Public Dataset)

DOI: 10.1098/rsif.2019.0041


Both engineered and biological transportation networks face trade-offs in their design. Network users desire to quickly get from one location in the network to another, whereas network planners need to minimize costs in building infrastructure. Here, we use the theory of Pareto optimality to study this design trade-off in the road networks of 101 cities, with wide-ranging population sizes, land areas and geographies. Using a simple one parameter trade-off function, we find that most cities lie near the Pareto front and are significantly closer to the front than expected by alternate design structures. To account for other optimization dimensions or constraints that may be important (e.g. traffic congestion, geography), we performed a higher-order Pareto optimality analysis and found that most cities analysed lie within a region of design space bounded by only four archetypal cities. The trade-offs studied here are also faced and well-optimized by two biological transport networks-neural arbors in the brain and branching architectures of plant shoots-suggesting similar design principles across some biological and engineered transport systems.

Item Type: Paper
Subjects: bioinformatics
organism description > plant behavior
bioinformatics > computational biology > algorithms
bioinformatics > computational biology
CSHL Authors:
Communities: CSHL labs > Navlakha lab
Depositing User: Matthew Dunn
Date: 31 May 2019
Date Deposited: 06 Nov 2019 16:21
Last Modified: 02 Feb 2024 21:01
PMCID: PMC6544892
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