E-Scooter safety: The riding risk analysis based on mobile sensing data. (March 2021)

• Record Type: Journal Article
• Authors: Ma, Qingyu; Yang, Hong; Mayhue, Alan; Sun, Yunlong; Huang, Zhitong; Ma, Yifang
• Is Part Of: Accident analysis and prevention. Volume 151(2021)
• Publication Date: 2021-03
• Subjects: Electric scooters -- E-Scooter safety -- Micro-mobility -- Naturalistic riding -- Mobile sensing -- Riding risk; Accidents -- Prevention -- Periodicals; Accident Prevention -- Periodicals; Accidents -- Prévention -- Périodiques; 363.106
• DOI: 10.1016/j.aap.2020.105954
• Languages: English
• ISSNs: 0001-4575

Abstract

Highlights: Developed a mobile sensing system for collecting detailed data on E-Scooter riding. A first study quantitatively investigating E-Scooter riding risk on different facilities. Proposed surrogate safety metrics to depict safety challenges during E-Scooter riding. Assessed obstacles and vibration impact experienced when riding E-Scooters. Sensed data can be analyzed for assessing the quality of riding facilities. Abstract: The emergence of shared electric scooter (E-Scooter) systems offers a new micro-mobility mode in many urban areas worldwide. These systems have rapidly attracted numerous trips on various types of facilities such as sidewalks and bike lanes. After their burst of popularity, there are also growing safety concerns about E-Scooter riding. Consequently, a few cities have banned or temporarily suspended E-Scooters as severe crashes occurred. As an emerging micro-mobility mode, its safety performance is significantly understudied as compared to other travel modes such as cars and bicycles. The lack of crash records further prevents it from understanding the underlying mechanisms that drive the occurrences of E-Scooter crashes. The overarching goal of this paper is to probe the safety risk when riding E-Scooters. Specifically, it aims to study the interactions between e-scooter riding and the environment settings through naturalistic riding experiments. Rather than focusing on the analysis of individual riders' heterogeneous behavior (e.g., swinging, hard braking, etc.) and rider characteristics (e.g., age, gender, etc.), the naturalistic riding study examines the riding process in different riding circumstances. A mobile sensing system has been developed to collect data for quantifying the surrogate safety metrics in terms of experienced vibrations, speed changes, and proximity to surrounding objects. The results from naturalistic riding experiments show that E-Scooters can experience notable impacts from different riding facilities. Specifically, compared to bicycle riding, more severe vibration events were associated with E-Scooter riding, regardless of the pavement types. Riding on concrete pavements was found to experience a multiple times higher frequency of vibration events when compared to riding on asphalt pavements of the same length. Riding on both sidewalks and vehicle lanes can both encounter high-frequency close contacts in terms of proximity with other objects. These experimental results suggest that E-Scooters are subject to increased safety challenges due to the increased vibrations, speed variations, and constrained riding environments.