Safe from Crime at Location-Specific Transit Facilities

Transit agencies identify two types of exposure to crime: the safety of riders and security. Transit operators have long monitored crime and are cognizant of high incident locations. However, they lack data-driven tools to readily match crime events spatially with the locations of individual transit...

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Main Authors: Moudon, Anne Vernez, Bassok, Alon, Kang, Mingyu
Format: Report
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/1773/43587
id ftunivwashington:oai:digital.lib.washington.edu:1773/43587
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spelling ftunivwashington:oai:digital.lib.washington.edu:1773/43587 2023-05-15T17:54:02+02:00 Safe from Crime at Location-Specific Transit Facilities Moudon, Anne Vernez Bassok, Alon Kang, Mingyu 2018 http://hdl.handle.net/1773/43587 en_US eng http://hdl.handle.net/1773/43587 Transit Transit Stop Amenities Transportation Safety Transit Neighborhood Disaggregate Crime Data Transit Transaction Data Technical Report 2018 ftunivwashington 2023-03-12T18:59:10Z Transit agencies identify two types of exposure to crime: the safety of riders and security. Transit operators have long monitored crime and are cognizant of high incident locations. However, they lack data-driven tools to readily match crime events spatially with the locations of individual transit facilities, and temporally with transit service periods. This pilot project explored the use of data-driven tools to (1) identify concentrations of criminal activity near transit facilities, and (2) assist decision-making regarding the selection of countermeasures and the allocation of future safety investments, using the results of models estimating environmental and socioeconomic predictors of crime near transit facilities. The project used two novel data sets: location-specific, police-reported crime incidents by type; and individual ORCA card (electronic transit fare payment system) transaction records, yielding transit ridership data. Two sets of models were developed to examine exposure to crime while waiting for transit (within 100 m of transit stops) and while walking to transit (within 400 m of transit stops). The hypotheses were that within 100 m of a stop, amenities provided at each stop could act as a deterrent of crime; and within 400 m different characteristics of the built, social, and transportation environment would be associated with crime. Analyses were restricted to the City of Seattle, and models were run using all stops as well as only stops located in the City’s urban villages (hosting 90 percent of the City’s ridership and where 74 percent of the stops fell in the highest tertile of crime). We found that amenities at stops had mixed associations with crime, suggesting that amenities serve to provide riders with added comfort but not necessarily more safety. Higher ridership provides safety while waiting for transit (100-m models), but it exposes riders to more crime as they walk to and from transit (400-m models). Higher employment densities in neighborhoods around transit stops are protective ... Report Orca University of Washington, Seattle: ResearchWorks
institution Open Polar
collection University of Washington, Seattle: ResearchWorks
op_collection_id ftunivwashington
language English
topic Transit
Transit Stop Amenities
Transportation Safety
Transit Neighborhood
Disaggregate Crime Data
Transit Transaction Data
spellingShingle Transit
Transit Stop Amenities
Transportation Safety
Transit Neighborhood
Disaggregate Crime Data
Transit Transaction Data
Moudon, Anne Vernez
Bassok, Alon
Kang, Mingyu
Safe from Crime at Location-Specific Transit Facilities
topic_facet Transit
Transit Stop Amenities
Transportation Safety
Transit Neighborhood
Disaggregate Crime Data
Transit Transaction Data
description Transit agencies identify two types of exposure to crime: the safety of riders and security. Transit operators have long monitored crime and are cognizant of high incident locations. However, they lack data-driven tools to readily match crime events spatially with the locations of individual transit facilities, and temporally with transit service periods. This pilot project explored the use of data-driven tools to (1) identify concentrations of criminal activity near transit facilities, and (2) assist decision-making regarding the selection of countermeasures and the allocation of future safety investments, using the results of models estimating environmental and socioeconomic predictors of crime near transit facilities. The project used two novel data sets: location-specific, police-reported crime incidents by type; and individual ORCA card (electronic transit fare payment system) transaction records, yielding transit ridership data. Two sets of models were developed to examine exposure to crime while waiting for transit (within 100 m of transit stops) and while walking to transit (within 400 m of transit stops). The hypotheses were that within 100 m of a stop, amenities provided at each stop could act as a deterrent of crime; and within 400 m different characteristics of the built, social, and transportation environment would be associated with crime. Analyses were restricted to the City of Seattle, and models were run using all stops as well as only stops located in the City’s urban villages (hosting 90 percent of the City’s ridership and where 74 percent of the stops fell in the highest tertile of crime). We found that amenities at stops had mixed associations with crime, suggesting that amenities serve to provide riders with added comfort but not necessarily more safety. Higher ridership provides safety while waiting for transit (100-m models), but it exposes riders to more crime as they walk to and from transit (400-m models). Higher employment densities in neighborhoods around transit stops are protective ...
format Report
author Moudon, Anne Vernez
Bassok, Alon
Kang, Mingyu
author_facet Moudon, Anne Vernez
Bassok, Alon
Kang, Mingyu
author_sort Moudon, Anne Vernez
title Safe from Crime at Location-Specific Transit Facilities
title_short Safe from Crime at Location-Specific Transit Facilities
title_full Safe from Crime at Location-Specific Transit Facilities
title_fullStr Safe from Crime at Location-Specific Transit Facilities
title_full_unstemmed Safe from Crime at Location-Specific Transit Facilities
title_sort safe from crime at location-specific transit facilities
publishDate 2018
url http://hdl.handle.net/1773/43587
genre Orca
genre_facet Orca
op_relation http://hdl.handle.net/1773/43587
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