Exploration of mental envelope determinants when pedestrians interact with various mobilities on mixed streets. (February 2022)

• Record Type: Journal Article
• Authors: Zou, Lubing; Yai, Tetsuo
• Is Part Of: Transportation research. Volume 85(2022)
• Page Start: 24
• Page End: 37
• Publication Date: 2022-02
• Subjects: Mental envelope -- Human–machine interaction -- Pedestrian -- Mixed street; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2022.01.002
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: A new envelope theorem divided into physical and mental envelopes (PE and ME) is proposed for dealing with mixed traffic. The ME composed of the subject and object mental envelope (SME and OME) expands the previous interpersonal distance. Determinants and relationships of MEs are analyzed by structural equation modeling with data from a questionnaire survey. The unexpected result of OME positively affecting SME illustrates that OME plays an important role in describing pedestrian perception in the model construction. Abstract: Mixed traffic of multiple road users may increase when machines and future mobilities are gradually introduced in human society to satisfy the travel and service needs of people. For providing a safe and comfortable walking environment for pedestrians in the mixed streets with various mobilities, this study proposes the envelope theorem based on the contributions and limitations of the previous explorations in human–machine coexistence. The envelope is divided into physical and mental envelopes. The main focus of this study is the mental envelope (ME) which is a psychological boundary used to distinguish the range of comfort and unpleasantness in people's minds. ME as the expansion of previous interpersonal distance can explain the pedestrian perceptions from different perspectives. This paper discusses the definition, expressions, and applications of ME, and then explores its determinants and relationships by conducting structural equation modeling (SEM) based on the questionnaire survey. The findings may assist to create better road allocation in the future.