Insight Lane - The D4D Crash Model

Using data science to help cities build safer roads

Insight Lane is a global effort to understand the causes of road crashes. By combining the power of machine learning with open data, it helps cities to:

  1. identify high risk locations in their road network
  2. examine the features that contribute to risk
  3. understand the impact of intervention and how roads might be improved

Any city in the world is invited to participate. Risk is currently assessed using road features, historical crash data and citizen-reported safety concerns, but this is only the beginning - traffic volumes, average speeds, construction events, weather and more can all help improve understanding of what creates risk.

We're interested in speaking with any city that shares our vision for improving road safety. As more cities become involved and the depth of data increases we're looking to unlock the potential of shared insights, in a way that allows for true collaboration on a global problem, rather than siloed, single-city efforts

Join this Project

We depend on the skill sets, ideas and passionate commitment of our volunteers to help make each project a success. If this project is something you'd like to be a part of, we'd love to have you on board.