Safe from Crime at Location-Specific Transit Facilities: Final Project Report

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). We 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.

Publication Date: 
Friday, June 1, 2018
Publication Number: 
WA-RD 882.1
Last modified: 
08/28/2018 - 09:28
Anne Vernez Moudon, Alon Bassok, Mingyu Kang.
Washington State Transportation Center (TRAC-UW).
Number of Pages: 
Public transit, Transit riders, Safety and security, Urban areas, Urban transit, Transit safety, Bus stops, Safety, Crimes, Data fusion, Data analysis.