This is not your typical boring academic paper filled with jargon and equations that make you want to pull out your hair (or maybe it will). Instead, let’s have some fun while learning!

To set the stage: what are recurrent events? In the context of autonomous vehicle testing, these are situations where a certain event or scenario repeats itself multiple times during a test run. For example, if we’re testing how well our car can handle roundabouts, we might encounter several different ones throughout the course of the test.

Now that we have a basic understanding of what recurrent events are, why they matter in autonomous vehicle testing. Well, for starters, it helps us identify any patterns or trends that may be present in these situations. By analyzing how our car performs on multiple roundabouts, we can see if there are certain factors (such as the size of the roundabout) that affect its ability to navigate safely and efficiently.

But wait, you might say isn’t it enough to just test each scenario once? After all, if a car can handle one roundabout, surely it can handle any other roundabout, right? Well, not exactly. Each roundabout is unique in terms of its size, shape, and layout, which means that our car may perform differently on each one. By testing multiple times, we can see how consistent (or inconsistent) the results are across different scenarios.

So, now that we understand why recurrent events matter, how to model them in autonomous vehicle testing. One approach is to use a statistical method called Markov chains. Essentially, this involves breaking down each scenario into smaller “states” and then tracking the probability of transitioning from one state to another. For example, if we have three states (approaching roundabout, navigating through roundabout, exiting roundabout), we can calculate the probability of moving from one state to another based on historical data.

But wait, you might say isn’t that a lot of work? After all, we would need to collect and analyze a ton of data just to create these models! Well, yes, it is a bit more involved than simply testing each scenario once. However, the benefits are well worth the effort. By modeling recurrent events in this way, we can identify any areas where our car may be struggling or performing inconsistently. This allows us to make improvements and optimize its performance over time.