A Framework to Assess Pedestrian Exposure Using Personal Device Data. (September 2022)

• Record Type: Journal Article
• Authors: Douglas, Grace; Boyle, Linda Ng; Kim, Haena; Moudon, Anne; Mooney, Steve; Saelens, Brian; Ebel, Beth
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 66:Part 1(2022)
• Page Start: 320
• Page End: 324
• Publication Date: 2022-09
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1071181322661319
• Languages: English
• ISSNs: 1541-9312

Abstract

Capturing pedestrian exposure is important to assess the likelihood of a pedestrian-vehicle crash. In this study, we show how data collected on pedestrians using personal electronic devices can provide insights on exposure. This paper presents a framework for capturing exposure using spatial pedestrian movements based on GPS coordinates collected from accelerometers, defined as walking bouts. The process includes extracting and cleaning the walking bouts and then merging other environmental factors. A zero-inflated negative binomial model is used to show how the data can be used to predict the likelihood of walking bouts at the intersection level. This information can be used by engineers, designers and planners in roadway designs to enhance pedestrian safety.