SYSTÈME D'AMÉLIORATION DE DÉCISION BASÉ SUR LA RÉTROACTION DE PLANIFICATION POUR UN VÉHICULE DE CONDUITE AUTONOME

摘要

In one embodiment, systems and methods are disclosed for a planning-driven framework for an autonomous driving vehicle (ADV) driving decision system. Driving decisions are classified into at least seven categories, including: conservative decision, aggressive decision, conservative parameters, aggressive parameters, early decision, late decision, and non-decision problem. Using the outputs of an ADV decision planning module, an ADV driving decision problem is identified, categorized, and diagnosed. A local driving decision improvement can be determined and executed in a short time frame on the ADV. For a long term solution, if needed, the driving decision problem can be uploaded to an analytics server. The driving decision problems from a large plurality of ADVs can be aggregated and analyzed for improving the ADV decisions system for all ADVs.