空间认知驱动的自适应路径引导

为了生成符合人们认知习惯、反映用户空间知识并易于利用自然语言表达的路径引导, 提出了一个将路径抽象为一系列结构统一、具有时序性和多粒度性且可以被加工为指导用户沿路径前进的短语或句子的指示单元的表达框架,并说明了利用环境结构、路径特征、先验知识等上下文因素生成多粒度的指示单元, 从中选择最合适的指示单元, 进而实现自适应路径引导的方法。通过与传统的采用“Distance-to-Turn”模式的路径引导进行对比可以发现, 基于空间认知的自适应路径引导更加符合人们描述路径的方式, 能够降低用户的认知压力并提高导航的效率。

Spatial cognition driven context-adaptive route directions

A route representation framework and its main implementation procedures are proposed for generating contextadaptive route directions, which could meet human cognitive habits, refl ect user's spatial knowledge, and is apt to be expressed in natural language. In the framework, a route is represented as a sequence of uniform temporal and various granular instruction units, which can be processed into route instruction phrases or sentences. For the implementation of context-adaptive route directions, landmark extraction, various granular instruction unit generation and most appropriate instruction unit sequence selection are introduced, while some contextual factors such as environmental structures, route characteristics and prior knowledge are also considered in these procedures. After compared with traditional route directions predominantly using distance-to-turn information, it can be found that the context-adaptive route directions based on spatial cognition is more conformable to the way people describe routes, and thus could decrease user's cognitive workload and promote the effi ciency of navigation systems.