Analyzing traffic speeds from 100 billion drive records
🎥 Watch the Webinar recording associated with this blog post here.
Over the last few decades, it has become increasingly evident that passenger vehicles are by far the most dangerous way to travel. As a result, it has become more and more important to find an efficient and effective method to predict traffic risk. However, predicting traffic accidents and where they are likely to occur is a very complex problem, with large amounts of data being needed for most meaningful predictions.
At Pacific Spatial Solutions, we are currently trying to tackle this problem by training a machine learning model to predict road and intersection risk in Japan nationwide. As we are trying to predict traffic risk on a national level it is only natural that the data we use cover the same area.