Abstract

When the pandemic hit the world, Västtrafik wanted a precise way to inform travelers about what trips were likely to be crowded so they could plan their trips safely. Since Västtrafik works in a large geographical area with a heterogeneous population landscape, creating warnings based only on the time of day wasn't considered good enough. We will present a use case of machine learning in production based on data from the automatic passenger counting system. The focus will be on all those details that make ML solutions useful in real life. How do you communicate the results? How do you maintain it? What engine does the model use? We will also present results on how travelers received it and how it is continuously evaluated and evolving today.

Erik Andersson

Product Manager BI and Analytics @ Västtrafik

Erik Andersson is a product owner at Västtrafik and is responsible for the BI and Analytics team. Erik has been at Västtrafik for six years, and during that time, he mainly worked with vehicle and passenger data. Before that, he was an ITS consultant working with road and vehicle systems. Erik has studied Civil Engineering at Chalmers Univerity in Gothenburg, focusing on traffic-related IT systems.