Tradeoffs between safety and time: A routing view

Daniel R. Carmody; Richard B. Sowers

doi:10.1016/j.trc.2019.09.020

Tradeoffs between safety and time: A routing view

Research output: Contribution to journal › Article › peer-review

Abstract

This article proposes a data-driven combination of travel times, distance, and collision counts in urban mobility datasets, with the goal of quantifying how intertwined traffic accidents are in the road network of a city. We devise a bi-attribute routing problem to capture the tradeoff between travel time and accidents. We apply this to a dataset from New York City. By visualizing the results of this computation in a normalized way, we provide a comparative tool for studies of urban traffic.

Original language	English (US)
Pages (from-to)	357-377
Number of pages	21
Journal	Transportation Research Part C: Emerging Technologies
Volume	108
DOIs	https://doi.org/10.1016/j.trc.2019.09.020
State	Published - Nov 2019

Keywords

Accidents
Intelligent urban navigation
Optimization
Routing
Safety
Smart city

ASJC Scopus subject areas

Civil and Structural Engineering
Automotive Engineering
Transportation
Management Science and Operations Research

Online availability

10.1016/j.trc.2019.09.020

Library availability

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title = "Tradeoffs between safety and time: A routing view",

abstract = "This article proposes a data-driven combination of travel times, distance, and collision counts in urban mobility datasets, with the goal of quantifying how intertwined traffic accidents are in the road network of a city. We devise a bi-attribute routing problem to capture the tradeoff between travel time and accidents. We apply this to a dataset from New York City. By visualizing the results of this computation in a normalized way, we provide a comparative tool for studies of urban traffic.",

keywords = "Accidents, Intelligent urban navigation, Optimization, Routing, Safety, Smart city",

author = "Carmody, {Daniel R.} and Sowers, {Richard B.}",

note = "The authors would like to thank Arnab Chakraborty for some helpful insights on risk. The authors would also like to thank A. Madhusudan and H. Athi, both Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign, Urbana, Illinois, for their work on prior versions of this project. This material is based upon work supported by the National Science Foundation under Grant Nos. CMMI 1727785 and DMS 1345032. The authors would like to thank the High Performance Computing Center of the MSFE program at the University of Illinois for computational support. The code for this work is at https://github.com/dcarmod2/VisionZeroTheory_Submission.",

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doi = "10.1016/j.trc.2019.09.020",

language = "English (US)",

volume = "108",

pages = "357--377",

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T2 - A routing view

AU - Carmody, Daniel R.

AU - Sowers, Richard B.

N1 - The authors would like to thank Arnab Chakraborty for some helpful insights on risk. The authors would also like to thank A. Madhusudan and H. Athi, both Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign, Urbana, Illinois, for their work on prior versions of this project. This material is based upon work supported by the National Science Foundation under Grant Nos. CMMI 1727785 and DMS 1345032. The authors would like to thank the High Performance Computing Center of the MSFE program at the University of Illinois for computational support. The code for this work is at https://github.com/dcarmod2/VisionZeroTheory_Submission.

PY - 2019/11

Y1 - 2019/11

N2 - This article proposes a data-driven combination of travel times, distance, and collision counts in urban mobility datasets, with the goal of quantifying how intertwined traffic accidents are in the road network of a city. We devise a bi-attribute routing problem to capture the tradeoff between travel time and accidents. We apply this to a dataset from New York City. By visualizing the results of this computation in a normalized way, we provide a comparative tool for studies of urban traffic.

AB - This article proposes a data-driven combination of travel times, distance, and collision counts in urban mobility datasets, with the goal of quantifying how intertwined traffic accidents are in the road network of a city. We devise a bi-attribute routing problem to capture the tradeoff between travel time and accidents. We apply this to a dataset from New York City. By visualizing the results of this computation in a normalized way, we provide a comparative tool for studies of urban traffic.

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KW - Optimization

KW - Routing

KW - Safety

KW - Smart city

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ER -

Tradeoffs between safety and time: A routing view

Abstract

Keywords

ASJC Scopus subject areas

Online availability

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