Direction disturbance model

What is direction disturbance model and why we need it?

In real orienteering, it’s not easy to keep accurate azimuth. You must look at a ground, at a map, you are fatigued, you need to avoid obstacles. So many factors are considerably influencing your running direction accuracy.

Some factors are replicated in Virtual-O simulation, like avoiding obstacles or looking into map. But looking on the ground, fatigue or uneven ground is different beast.

And here comes direction disturbance model to “rescue” (to be fair it’s trying to destroy your race)

It’s not an easy task to alter your direction ideally without you notice it. To simulate organic changes to direction, I’m using perlin noise based algorithm to change player direction

based on terrain steepness and actual map symbol. Similar to running speed modifiers, you can modify this behaviour separetely for every symbol. You can specify x (speed of trend change) and y (magnitude of angle change) scale for symbol.

A video is worth a 1000 words. On the road no disturbance at all is applied. (as it’s easy to keep bearing on road) In elderberries after I have set bearing to rocks, I haven’t changed direction by myself. Everything was result of direction disturbance model.

In blackberries, you can see influence of terrain steepness: