Enhancing environmental engagement with natural language interfaces for in-vehicle navigation systems

Antrobus, Vicki; Large, David; Burnett, Gary; Hare, Chrisminder

Abstract

Four on-road studies were conducted in the Clifton area of Nottingham, UK, aiming to explore the relationships between driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. In a between-subjects design, a total of 61 experienced drivers completed two experimental drives comprising the same three routes (with overlapping sections), staged one week apart. Drivers were provided with the navigational support of a commercially-available navigation device (‘satnav’), an informed passenger (a stranger with expert route knowledge), a collaborative passenger (an individual with whom they had a close, personal relationship) or a novel interface employing conversational natural language NAV-NLI). The NAV-NLI was created by curating linguistic intercourse extracted from the earlier conditions, and delivering this using a Wizard-of-Oz technique. The different navigational methods were notable for their varying interactivity and the preponderance of environmental landmark information within route directions. Participants experienced the same guidance on each of the two drives to explore changes in reported and observed behaviour. Results show that participants who were more active in the navigation task (collaborative passenger or NAV-NLI) demonstrated enhanced environmental engagement (landmark recognition, route-learning and survey knowledge) allowing them to reconstruct the route more accurately post-drive, compared to drivers using more passive forms of navigational support (SatNav or informed passenger). Workload measures (TDT, NASA-TLX) indicated no differences between conditions, although satnav users and collaborative passenger drivers reported lower workload during their second drive. The research demonstrates clear benefits and potential for a navigation system employing two-way conversational language to deliver instructions. This could help support a long-term perspective in the development of spatial knowledge, enabling drivers to become less reliant on the technology and begin to re-establish associations between viewing an environmental feature and the related navigational manoeuvre.

Citation

Antrobus, V., Large, D., Burnett, G., & Hare, C. (2019). Enhancing environmental engagement with natural language interfaces for in-vehicle navigation systems. Journal of Navigation, 72(3), 513-527. https://doi.org/10.1017/S037346331800108X

• Journal Article Type: Article
• Acceptance Date: Dec 12, 2018
• Online Publication Date: Feb 15, 2019
• Publication Date: 2019-05
• Deposit Date: Jan 24, 2019
• Publicly Available Date: Aug 16, 2019
• Journal: Journal of Navigation
• Print ISSN: 0373-4633
• Electronic ISSN: 1469-7785
• Publisher: Cambridge University Press
• Peer Reviewed: Peer Reviewed
• Volume: 72
• Issue: 3
• Pages: 513-527
• DOI: https://doi.org/10.1017/S037346331800108X
• Public URL: https://nottingham-repository.worktribe.com/output/1495208
• Publisher URL: https://www.cambridge.org/core/journals/journal-of-navigation/article/enhancing-environmental-engagement-with-natural-language-interfaces-for-invehicle-navigation-systems/DCFE075AEEACFEE1C2CEE89EF45EF446
• Contract Date: Jan 24, 2019