NYMTC Regional Pedestrian Safety Study - New York Metropolitan ...

located by reference marker (the small green and white signs located every one tenth mile on
divided highways and every two tenths mile on two lane roads. For local roads, the locations are
indicated using a link-node system. The location data in SIMS is not in GIS format, but it could
be.
NYSDOT personnel can access the SIMS data by a password. Municipalities and other
agencies need to make a formal request for the data, which generally takes a few weeks.
The interviews identified several problems with the data. The most commonly cited problem
was the timeliness of the data. In the recent past, the SIMS data has not been available for up to
three to four years after the crashes occurred. This has been a severe problem for agencies trying
to judge the safety impact of a recent improvement or trying to address problematic locations in a
timely manner. It should be noted that NYSDOT and NYS DMV have made improving this a
priority, and in December 2006 reported that the database is up to date, within the limits of the
reporting procedures.
A second problem is its incompleteness, particularly for crashes on local roads. The crash reports
do not have enough detail. Often the local transportation department has investigated the site,
but this data is not included with the electronic file. Also, people who are severely injured or
unconscious are typically taken to the hospital before the police collect information from them.
Once the injured person is in the hospital system, information on them is confidential, unless the
person dies. Since a pedestrian is more likely to seriously injured than a vehicle occupant, this
affects pedestrian crash data more; one result of this is the probable underreporting of pedestrian
crash participants who are impaired by alcohol or drugs.
A third problem is that there is no readily available data on exposure for pedestrian crashes.
Vehicular crash rates are calculated based on crashes per vehicle miles traveled or sometimes on
crashes per licensed drivers. For a particular roadway link or intersection, daily or peak hour
traffic volumes could be used as a measure of exposure. For pedestrian crashes, pedestrian
volumes are rarely available. The common measure of exposure is residential population, but it
is a poor substitute for the number of pedestrians in an area and even worse for trying to compare
accidents in different locations within a local pedestrian network. A better measure, although not
as easy to find, would be daytime population. Other suggestions include the percent of
population that walks to work or the sum of the percent who walk or use transit or a measure of
land use or retail activity.
Another way to address pedestrian exposure is through a new modeling approach that estimates
pedestrian flows for a large area of a city. The goals were to develop a pedestrian demand model
that uses readily available data and to provide tools for enhancing the data to account for actual
pedestrian and street network conditions. The model was applied for demonstration purposes in
Baltimore and Langley Park, Maryland. In each case about 10 square miles of the city were
modeled. The model is based on a traditional four-step process (trip generation, distribution,
mode choice, assignment) and integrated with GIS mapping as well. The network assignment
method replicates the multi-path patterns that pedestrians actually follow, and accumulates flow
totals on sidewalks, crosswalks, corner areas, and jaywalk locations. It accounts for the barrier
effects of streets and crosswalks, sidewalk quality and continuity, and other walkway factors that
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