Autonomous driving requires an accurate representation of the environment around the ego vehicle. The environment includes static elements such as road layout and lane structures, and also dynamic elements such as other cars, pedestrians, and other types of road users. The static elements can be captured by an HD map containing lane level information.

There are two types of mapping methods, offline and online. For offline mapping and the application of deep learning in offline mapping, please refer to my previous post. In places where there is no map support or the autonomous vehicle has never been to, online mapping would be useful. For online mapping, one conventional method is SLAM (simultaneous localization and mapping) which relies on the detection and matching of geometric features on a sequence of images, or with a twist of the added notion of object.

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