Inaccurate prediction of user intent and departure schedules leads to inefficient route planning. Reducing this uncertainty allows for proactive vehicle system preparation and optimized multimodal coordination.

Sensor observation errors and environmental noise lead to unreliable lane recognition. Reducing these inaccuracies ensures the safety and stability of automated driving functions.

Human drivers struggle to replicate precise steering and positioning during repetitive complex maneuvers like parking. Automating the recording and playback of trajectories eliminates human error and variability in confined spaces.

Discrepancies between stored map information and real-world road geometry lead to failures in automated driving systems. Ensuring map data matches the actual traveled road section prevents hazardous navigation errors.

Ambiguity in right-of-way and emergency vehicle clearance protocols leads to collision risks and traffic flow disruptions. Resolving this uncertainty ensures safe and predictable vehicle movement at complex junctions.