Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trips in New York City, San Francisco, Singapore, and Vienna, we compute the shareability curves for each city, and find that a natural rescaling collapses them onto a single, universal curve. We explain this scaling law theoretically with a simple model that predicts the potential for ride sharing in any city, using a few basic urban quantities and no adjustable parameters. Accurate extrapolations of this type will help planners, transportation companies, and society at large to shape a sustainable path for urban growth.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337932 | PMC |
| http://dx.doi.org/10.1038/srep42868 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Global urban greening and its implication for urban heat mitigation.
Proc Natl Acad Sci U S A
January 2025
School of Politics and Public Administration, Soochow University, Suzhou 215006, China.
Urban vegetation provides essential ecosystem services and benefits to support biodiversity and human well-being in urban areas. However, the dynamic trends, driving factors, and their implications to urban heat mitigation at the global scale remain largely unclear. Here, we used a high-resolution enhanced vegetation index (EVI) dataset to examine the vegetation dynamics in 11,235 urban areas worldwide, identify the driving factors behind its changes, and estimate the potential urban heat mitigation benefits of these changes.
View Article and Find Full Text PDFMicrobial Carbon Use Efficiency and Growth Rates in Soil: Global Patterns and Drivers.
Glob Chang Biol
January 2025
Department of Soil Science of Temperate Ecosystems, Department of Agricultural Soil Science, University of Goettingen, Göttingen, Germany.
Carbon use efficiency (CUE) of microbial communities in soil quantifies the proportion of organic carbon (C) taken up by microorganisms that is allocated to growing microbial biomass as well as used for reparation of cell components. This C amount in microbial biomass is subsequently involved in microbial turnover, partly leading to microbial necromass formation, which can be further stabilized in soil. To unravel the underlying regulatory factors and spatial patterns of CUE on a large scale and across biomes (forests, grasslands, croplands), we evaluated 670 individual CUE data obtained by three commonly used approaches: (i) tracing of a substrate C by C (or C) incorporation into microbial biomass and respired CO (hereafter C-substrate), (ii) incorporation of O from water into DNA (O-water), and (iii) stoichiometric modelling based on the activities of enzymes responsible for C and nitrogen (N) cycles.
View Article and Find Full Text PDFPredicting drug and target interaction with dilated reparameterize convolution.
Sci Rep
January 2025
Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, 110016, China.
Predicting drug-target interaction (DTI) stands as a pivotal and formidable challenge in pharmaceutical research. Many existing deep learning methods only learn the high-dimensional representation of ligands and targets on a small scale. However, it is difficult for the model to obtain the potential law of combining pockets or multiple binding sites on a large scale.
View Article and Find Full Text PDFInfluence of label and academic field on cancer stigma and subjective illness theories among medicine and psychology students: a cross-sectional online study.
Sci Rep
January 2025
Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.
The growing population of cancer survivors faces psychosocial challenges, including stigma. This study examined stigma toward "persons with cancer" and "cancer survivors" among medicine and psychology students, focusing on the impact of labeling. Additionally, the study explored these students' subjective illness theories of cancer.
View Article and Find Full Text PDFThe Dyson equalizer: adaptive noise stabilization for low-rank signal detection and recovery.
Inf inference
March 2025
Program in Applied Mathematics, Yale University, New Haven, CT 06520, US.
Detecting and recovering a low-rank signal in a noisy data matrix is a fundamental task in data analysis. Typically, this task is addressed by inspecting and manipulating the spectrum of the observed data, e.g.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!