How Much is too Much: Exploring the Effect of Verbal Route Description Length on Indoor Navigation

TL;DR

This study investigates the optimal length of verbal route descriptions for indoor navigation, proposing a theoretical framework and experimental validation that suggests four route segments as ideal for effective recall and navigation.

Contribution

It introduces a theoretical model linking route segments to working memory and empirically tests the impact of description length on navigation performance.

Findings

Optimal description length is around four route segments.

Longer descriptions may hinder recall and performance.

Shorter descriptions may be insufficient for navigation.

Abstract

Navigating through a new indoor environment can be stressful. Recently, many places have deployed robots to assist visitors. One of the features of such robots is escorting the visitors to their desired destination within the environment, but this is neither scalable nor necessary for every visitor. Instead, a robot assistant could be deployed at a strategic location to provide wayfinding instructions. This not only increases the user experience but can be helpful in many time-critical scenarios e.g., escorting someone to their boarding gate at an airport. However, delivering route descriptions verbally poses a challenge. If the description is too verbose, people may struggle to recall all the information, while overly brief descriptions may be simply unhelpful. This article focuses on studying the optimal length of verbal route descriptions that are effective for reaching the destination and easy for people to recall. This work proposes a theoretical framework that links route segments to chunks in working memory. Based on this framework, an experiment is designed and conducted to examine the effects of route descriptions of different lengths on navigational performance. The results revealed intriguing patterns suggesting an ideal length of four route segments. This study lays a foundation for future research exploring the relationship between route description lengths, working memory capacity, and navigational performance in indoor environments.