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Title: Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

Here, this study finds the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Furthermore, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The findings will help to make smart investment decisions in context of building sustainable transportation systems accounting for active transportation.
Authors:
ORCiD logo [1] ;  [2] ;  [1] ;  [1] ;  [1] ;  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Urban Dynamics Inst.
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Urban Dynamics Inst.; Univ. of Tennessee, Knoxville, TN (United States). Dept. of Geography
Publication Date:
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
Transportation
Additional Journal Information:
Journal Name: Transportation; Journal ID: ISSN 0049-4488
Publisher:
Springer
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC); USDOE Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; 42 ENGINEERING; Random parameter model; Active transportation; Travel behavior; mixed logit; walking; bicycling; New York City
OSTI Identifier:
1352741

Aziz, H. M. Abdul, Nagle, Nicholas N., Morton, April M., Hilliard, Michael R., White, Devin A., and Stewart, Robert N.. Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data. United States: N. p., Web. doi:10.1007/s11116-017-9760-8.
Aziz, H. M. Abdul, Nagle, Nicholas N., Morton, April M., Hilliard, Michael R., White, Devin A., & Stewart, Robert N.. Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data. United States. doi:10.1007/s11116-017-9760-8.
Aziz, H. M. Abdul, Nagle, Nicholas N., Morton, April M., Hilliard, Michael R., White, Devin A., and Stewart, Robert N.. 2017. "Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data". United States. doi:10.1007/s11116-017-9760-8. https://www.osti.gov/servlets/purl/1352741.
@article{osti_1352741,
title = {Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data},
author = {Aziz, H. M. Abdul and Nagle, Nicholas N. and Morton, April M. and Hilliard, Michael R. and White, Devin A. and Stewart, Robert N.},
abstractNote = {Here, this study finds the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Furthermore, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The findings will help to make smart investment decisions in context of building sustainable transportation systems accounting for active transportation.},
doi = {10.1007/s11116-017-9760-8},
journal = {Transportation},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {2}
}