How big data can help improve road safety

Big data has been increasingly deployed by municipalities that are looking to better understand the way traffic flows throughout the city, but it is also being deployed more often by police forces in order to make roads safer.

This is certainly the case in Tennessee, where they’ve been using predictive crash software to better understand the safety hot spots on their roads.  The program, which was launched in 2013, uses data from every crash reported in the state, together with the weather conditions at the time, and externalities such as special events.

This then generates a map showing the likelihood of incidents in any area during a given four-hour window each day.  This map can be monitored from the patrol car so that officers can provide targeted attention in real-time, together with more considered responses in advance.

This visible deterrent has thus far proven to be very effective, with traffic fatalities dropping by 3%, and the response time to incidents dropping by nearly 33%.

“It’s not the silver bullet that is going to solve every problem on traffic safety,” officials say. “But it’s another tool, an effective one, to give our people an idea of where they need to be and what they need to be working on to help prevent some of these crashes or at least be there quicker.”

Scaling up

Whilst these early results are promising, there has thus far been limited take up of predictive crash analytics, with the law enforcement agencies suggesting that the setup costs are prohibitive in departments that are stretched thinly already.  Such a lack of slack also often prevents people from thinking strategically enough to try different approaches.

So, despite an apparent appetite for working smarter, there has thus far been rather modest adoption from other US states.

One that has taken the plunge however is Indiana.  Interestingly, whereas Tennessee kept their data private, Indiana have decided to make it available to the public.

They’ve created a daily crash prediction map that was launched late last year, with data pulled in from crash reports and combined with traffic volume, weather data and major public events.

As before, the map is designed to pinpoint where accidents are likely, whilst also providing details of previous accidents, including their cause.

“We’re using this to better inform the public about potential hazards,” they say. “Maybe someone will click on it and decide they want to take a different route to work or allow more time.”

It is still early days so they have no data yet as to its effectiveness in reducing incidents on the roads, and as with so many innovations, it can be hard to change mindsets when behaviors and cultures are firmly entrenched.

We’ve seen predictive analytics used in a growing range of law enforcement activities, so it’s no surprise that officials are testing the water in terms of traffic safety too.

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