Eva‐Maria Griesbauer

Expert Navigators Deploy Rational Complexity-Based Decision Precaching for Large-Scale Real-World Planning

This study examines how expert London taxi drivers plan routes by precaching decisions at key junctions, using complexity metrics to prioritize mental sampling during route planning.

London taxi drivers exploit neighbourhood boundaries for hierarchical route planning

This study shows that London taxi drivers use hierarchical planning by organizing city regions into clusters, leading to faster route recall compared to distance-based planning.

London taxi drivers leverage regional boundaries to optimise route choices and improve their navigation skill across three decades

This study shows that London taxi drivers improve their navigation skills over decades by using regional boundaries to optimize route choices.

Learning The Knowledge: How London Taxi Drivers Build Their Cognitive Map of London

This paper examines how London taxi drivers acquire their cognitive map of London through systematic study and route-based learning, providing insights for AI spatial learning.