RIS devotes considerable time and resources to finding out which areas of the City have the worst speeding problems. The office has a minimum threshold for a street to become a candidate for traffic-calming treatments: when 15% of vehicles are traveling at 5 or more mph above the speed limit. It sounds simple, but gathering that data and ensuring it’s reliable is not.
“We needed a more comprehensive dataset to better determine where we should direct our resources,” says Rob Viola, Director of Safety Policy & Research at RIS. “We get thousands of comments and complaints about road safety every year from community members. Faced with limited budgets, we were looking for a quick and accurate way to assess the validity of these claims and make evidence-based investments.”
Establishing which streets should receive traffic-calming treatments – ranging from lowered speed limits to speed humps and speed cushions (humps modified to accommodate trucks and buses) – is a complex calculation involving multiple factors. There were several key areas where RIS needed more consistent, high-quality data:
- Verifying whether roads meet the qualifying criteria for traffic-calming interventions
- Before/after evaluations of the effectiveness of traffic-calming interventions
- Vetting of community requests and complaints
The “Priority Geographies” identified by Vision Zero – those with a high incidence of pedestrian fatalities and injuries – go to the top of the list, followed by school zones. “There are thousands of schools in the City, so we’re always trying to find new and better ways to allocate our resources,” says Viola.
Beyond these top two areas, there are still many spots in the City that require the office’s attention. While roads must meet detailed criteria (traffic volume, types of vehicles, road geometry and more) to qualify for traffic-calming interventions, the primary determinants are speeding history and crash history.
“Our office receives a live feed of all the City’s injury crashes, which goes into a database,” says Viola. “For historical speeds, though, we were using the time-consuming, manual approach of sending people out with radar guns to gather information.” Other methods such as pulling speed data from mobile devices can be problematic due to difficulties distinguishing between slow moving vehicles, bus riders and bicyclists. “The bottom line is we needed easier access to better data.”