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 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 from transit stops) and while walking to transit (within 400 m from transit stops). The hypotheses were that within 100 m of a stop, amenities at stops act as deterrents of crime; and within 400 m different characteristics of the built, social, and transportation environment are associated with crime. Analyses were restricted to the City of Seattle, and models were run using all stops and only stops located in the City’s urban villages (hosting 90 percent of the City’s ridership and the stops with the most crime). The authors found that amenities at stops have 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 exposes riders to more crime as they walk to and from transit (400-m models). In urban villages, sidewalks are associated with a lower likelihood of crime. However, a more connected street network, which characterizes the oldest, most urban areas of Seattle, is associated with more crime. The project illustrated how novel sets of disaggregated data on both crime and transit ridership can serve to develop models assessing the safety of transit riders at specific locations. Future research should continue to examine how transit riders can be protected from crime while they wait for transit as well as while they walk to and from it.

• Record URL:
  http://hdl.handle.net/1773/43587
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/36440
• Corporate Authors:

  Washington State Transportation Center

  University of Washington, 1107 NE 45th Street, Suite 535
  Seattle, WA  United States  98105

  Washington State Department of Transportation

  Research Office, Transportation Building, MS 47372
  Olympia, WA  United States  98504-7372

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Moudon, Anne Vernez
  • Bassok, Alon
  • Kang, Mingyu
• Publication Date: 2018-6

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Research Report
• Features: Figures; Maps; References; Tables;
• Pagination: 46p

Subject/Index Terms

• TRT Terms: Crimes; Data files; Decision support systems; Disaggregate analysis; Facilities; Public transit; Ridership; Security; Transit riders; Transit safety
• Geographic Terms: Seattle (Washington)
• Subject Areas: Data and Information Technology; Public Transportation; Safety and Human Factors; Security and Emergencies; Terminals and Facilities;

Filing Info

• Accession Number: 01678975
• Record Type: Publication
• Report/Paper Numbers: WA-RD 882.1
• Files: NTL, TRIS, ATRI, USDOT, STATEDOT
• Created Date: Aug 27 2018 2:05PM