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A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City

  • Published:2018-01 Issue: Volume:86 Page:280-299
  • ISSN:0968-090X
  • Container-title:Transportation Research Part C: Emerging Technologies
  • language:en
  • Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Aziz H.M. Abdul,Park Byung H.,Morton April,Stewart Robert N.,Hilliard M.,Maness M.

Funder

U.S. Department of Energy

Office of Science

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference87 articles.

1. Mass effects and mobility decisions;Abou-Zeid;Transport. Lett.,2013

2. ACS, 2012. The 2008-2012 ACS 5-Year Summary File Technical Documentation.

3. Extent and correlates of walking in the USA;Agrawal;Transport. Res. Part D: Transp. Environ.,2007

4. Nonlinear modeling of complex large-scale plants using neural networks and stochastic approximation;Alessandri;IEEE Trans. Syst. Man Cybernet. – Part A: Syst. Hum.,1997

5. A multi-agent approach using perceptron-based learning for robust operation of distributed chemical reactor networks;Artel;Eng. Appl. Artif. Intell.,2011

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