Spatial Intelligence of a Self-driving Car and Rule-Based Decision Making
This work addresses the challenge of spatial intelligence for autonomous vehicles, but it appears incremental as it builds on existing motion planning techniques.
The paper tackles the problem of achieving human-like behavior in self-driving cars in complex traffic by combining rule-based decision making with traditional motion planning, though it does not provide concrete numerical results.
In this paper we show how rule-based decision making can be combined with traditional motion planning techniques to achieve human-like behavior of a self-driving vehicle in complex traffic situations. We give and discuss examples of decision rules in autonomous driving. We draw on these examples to illustrate that developing techniques for spatial awareness of robots is an exciting activity which deserves more attention from spatial reasoning community that it had received so far.