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

Abstract

Active transportation modes--walk and bicycle--are central for low carbon transport, healthy living, and complete streets initiative. Building a community with amenable walk and bicycle facilities asks for smart planning and investments. It is critical to investigate the impact of infrastructure building or expansion on the overall walk and bicycle mode usage prior to making investment choices utilizing public tax money. This research developed an agent-based model to support investment decisions that allows to assess the impact of changes in walk-bike infrastructures at a high spatial resolution (e.g., block group level). The agent-based model (ABM) utilizes data from a synthetic population simulator generating agents with corresponding socio-demographic characteristics, and integrates facility attributes regarding walking and bicycling (e.g., sidewalk width, bike lane length) into the mode choice decision making process. Moreover, the ABM accounts for the effect of social interactions among agents who live and work at the same geographic locations. Finally, GIS-based maps are developed at block group resolution that allows exploring the effect of walk-bike infrastructure related investments. The results from New York City case study indicate that infrastructure investments such as widening sidewalk and increasing bike lane network can positively influence the active transportation mode choices. In addition, themore » level of impact varies with geographic locations--different boroughs of New York City will have different impacts. Lastly, social promotions resulting in higher social interaction among agents can reinforce the impacts of infrastructure changes.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1414721
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Transportation Research Part C: Emerging Technologies
Additional Journal Information:
Journal Volume: 86; Journal Issue: C; Journal ID: ISSN 0968-090X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Agent-based simulation; Walking; Bicycling; New York City; High-performance Computing; Repast HPC

Citation Formats

Aziz, H. M. Abdul, Park, Byung H., Morton, April M., Stewart, Robert N., Hilliard, Michael R., and Maness, Michael. A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City. United States: N. p., 2017. Web. doi:10.1016/j.trc.2017.11.008.
Aziz, H. M. Abdul, Park, Byung H., Morton, April M., Stewart, Robert N., Hilliard, Michael R., & Maness, Michael. A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City. United States. doi:10.1016/j.trc.2017.11.008.
Aziz, H. M. Abdul, Park, Byung H., Morton, April M., Stewart, Robert N., Hilliard, Michael R., and Maness, Michael. Fri . "A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City". United States. doi:10.1016/j.trc.2017.11.008.
@article{osti_1414721,
title = {A high resolution agent-based model to support walk-bicycle infrastructure investment decisions: A case study with New York City},
author = {Aziz, H. M. Abdul and Park, Byung H. and Morton, April M. and Stewart, Robert N. and Hilliard, Michael R. and Maness, Michael},
abstractNote = {Active transportation modes--walk and bicycle--are central for low carbon transport, healthy living, and complete streets initiative. Building a community with amenable walk and bicycle facilities asks for smart planning and investments. It is critical to investigate the impact of infrastructure building or expansion on the overall walk and bicycle mode usage prior to making investment choices utilizing public tax money. This research developed an agent-based model to support investment decisions that allows to assess the impact of changes in walk-bike infrastructures at a high spatial resolution (e.g., block group level). The agent-based model (ABM) utilizes data from a synthetic population simulator generating agents with corresponding socio-demographic characteristics, and integrates facility attributes regarding walking and bicycling (e.g., sidewalk width, bike lane length) into the mode choice decision making process. Moreover, the ABM accounts for the effect of social interactions among agents who live and work at the same geographic locations. Finally, GIS-based maps are developed at block group resolution that allows exploring the effect of walk-bike infrastructure related investments. The results from New York City case study indicate that infrastructure investments such as widening sidewalk and increasing bike lane network can positively influence the active transportation mode choices. In addition, the level of impact varies with geographic locations--different boroughs of New York City will have different impacts. Lastly, social promotions resulting in higher social interaction among agents can reinforce the impacts of infrastructure changes.},
doi = {10.1016/j.trc.2017.11.008},
journal = {Transportation Research Part C: Emerging Technologies},
number = C,
volume = 86,
place = {United States},
year = {Fri Nov 24 00:00:00 EST 2017},
month = {Fri Nov 24 00:00:00 EST 2017}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on November 24, 2018
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