How do we get local governments to use data to inform policy and decisions? Here is an example of how we can use data to mitigate pedestrian crashes.
Let’s define pedestrian crashes upfront - a pedestrian crash is when one or more cars crash into one or more pedestrians. New York State’s Department of Transportation aggregates crash data from law enforcement agencies across the state, and the data is available via a Freedom of Information request. Pedestrian crash data explains where crashes happen, the fatality and injury outcomes, the date and time of the accident and the circumstances of the crash.
We can use the data to anecdotally examine crashes within WAMC’s listening area:
- Between 2020 and 2025 pedestrian crashes resulted in 148 fatalities and 654 serious injuries
- 146 pedestrian crashes & 6 fatalities occurred on Central Avenue between Schenectady and Albany,
- The most dangerous intersections in Troy are on Hoosick Street, at 13th and 15th Streets
- Albany County crashes have increased more than 80% in the last five years; crashes in Saratoga County had been constant from 2020 through 2023 before spiking at the end of 2024
- Main Street in Poughkeepsie has twice the number of pedestrian crashes as any other street within the City
Those are a few examples of pedestrian crash statistics. Why do we want to use pedestrian crash data to inform policy? We want our attention on pedestrian safety to be meaningful and not performative. In 2025 the Cities of Albany and Saratoga Springs gave visibility to pedestrian safety by reducing their city speed limits to 25 mph. Will that yield benefit over time? Is data being examined to determine the benefits?
What does it mean in practical terms for our local governments to use crash data? There are 5 points to being data-driven:
First, cities and counties can use data to understand the current state. This means policy-makers examine the characteristics of crashes on major vs. minor roads, nighttime vs daytime, locations with or without sidewalks, and many other ways of examining the data.
Secondly, data is used to set our goals. Once we use data to understand the current state, by extension we can use that same data for goal-setting. We want our governments to set pedestrian safety goals and work toward them. As an illustrative example, we want a city to set a goal of reducing pedestrian crashes by half in a three-year period.
Thirdly, data can identify pedestrian safety collaborations across government boundaries. Central Avenue between Schenectady and Albany is an example. Safety issues don’t stop at city or county borders - Central Avenue’s pedestrian safety must be examined in its totality, as a system.
Fourth, data should suggest and validate remediation activities. There are many well-intentioned but meaningless ways that we can spend money on pedestrian safety. We want data to inform where we do and don’t spend money to prevent pedestrian crashes.
Lastly, we want to measure the success and benefits of our improvements over time. Celebrate our successes where we have decreased pedestrian crashes, and change our course if we have made investments where we don’t see benefits.
As a part of this commentary, we are making a pedestrian crash dataset with analysis available for all of New York State. You can download the dataset and examine your community’s pedestrian crash data - the where, when and how. Please see the show notes for a link to the data. https://wiki.tycheinsights.com/index.php/New_York_Pedestrian_Crash_Data
There is significant potential to have data inform how we understand and mitigate pedestrian crashes. It is a topic that has not received enough research and academic examination. It is a public health issue that has a biased impact on lower socioeconomic communities. If we use data to understand the magnitude of the problem, and if data informs where we implement productive countermeasures, then the WAMC listening area has an opportunity to be world class in our efforts to reduce pedestrian crashes.
The views expressed by commentators are solely those of the authors. They do not necessarily reflect the views of this station or its management.
