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1. A Survey of Electric-Scooter Riders’ Route Choice, Safety Perception, and Helmet Use

   https://doi.org/10.3390/su15086609  

   Sievert, Kelsey; Roen, Madeleine; Craig, Curtis M.; Morris, Nichole L. (April 2023, Sustainability)

   This study investigated electric-scooter (e-scooter) rider behaviors and preferences to inform ways to increase safety for e-scooter riders. Data was collected from 329 e-scooter riders via two online and one in-person survey. Survey questions considered rider roadway infrastructure preferences, safety perceptions, and helmet-wearing behavior. Protected bike lanes were more commonly indicated as the safest infrastructure (62.4%) but were less likely to be the most preferred infrastructure (49.7%). Sidewalks were better matched between riders, indicating them as their preferred riding infrastructure (22.7%) and the perceived safest riding infrastructure (24.5%). Riders had low feelings of safety and preference for riding on major/neighborhood streets or on unprotected bike lanes. Riders reported significant concern about being hit by a moving vehicle, running into a pothole/rough roadway, and running into a moving vehicle. In line with the Theory of Planned Behavior, a significant relationship was found between the frequency of riding and helmet-wearing behavior, with more frequent riders being more likely to wear helmets. Findings suggest that existing roadway infrastructure may pose safety challenges and encourage rider-selected workarounds. Public policy may consider emphasizing protected bicycle lane development, rather than helmet mandates, to support e-scooter riding safety for all vulnerable road users. 

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2. Dissecting shared e-scooters usage patterns and its impact on other transportation modes: A case study of Portland city

   https://doi.org/10.1016/j.tbs.2024.100812  

   Tuli, Farzana Mehzabin; Mitra, Suman (July 2024, Travel Behaviour and Society)

   The study analyzed the survey data from the 2018 Portland E-scooter Pilot Program and aims to determine (i) who uses shared e-scooters and why they use them, and (ii) whether there is any association between e-scooter usage and the usage of other modes of transportation. To accomplish the first objective, the study identifies the users of shared e-scooters based on their travel behavior using an unsupervised machine learning approach, latent class analysis (LCA). The LCA model grouped e-scooter users into three distinct classes: Class 1 (Recreational Enthusiasts) −occasional and frequent users for recreation, Class 2 (Commute Riders) −frequent users for work, and Class 3 (Intermittent Joyriders) −occasional and one-time users for recreation. Furthermore, a set of ordered logit models is employed to determine the second objective based on the identified classes of e-scooter users, their socio-demographic characteristics, and the built environment variables. The results of ordered logit models revealed that compared to Commute Riders, both Recreational Enthusiasts and Intermittent Joyriders exhibit less interest in increasing the usage of available transportation modes after adopting e-scooters. Notably, low-income e-scooter users show a higher probability of increasing their usage across various transportation modes, including public transportation, driving, shared mobility services, personal bikes, shared bikes, and walking. The study offers valuable insights to guide city planners and policymakers in developing effective strategies for the deployment of e-scooters, targeting each group of users. 

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3. Autonomous Scooter Navigation for People with Mobility Challenges

   https://doi.org/10.1109/ICCC.2018.00020  

   Mulky, Rajath Swaroop; Koganti, Supradeep; Shahi, Sneha; Liu, Kaikai (July 2018, 2018 IEEE International Conference on Cognitive Computing (ICCC))

   Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping the blind and elderly navigate to their destinations in a hassle-free manner. Riders often face challenges in driving scooters in some indoor and crowded places, especially on sidewalks with numerous obstacles and other pedestrians. People with certain disabilities, such as the blind, are often unable to drive their scooters well enough. In this paper, we propose to improve the safety and autonomy of the navigation by designing a cutting-edge autonomous scooter, which allows people with mobility challenges to navigate independently and safely in possibly unfamiliar surroundings. We focus on the localization and navigation challenges for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. Solving these challenges will enable the scooter to both travel within buildings and perform tight maneuvers in densely crowds automatically. 

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4. Gender split and safety behavior of cyclists and e-scooter users in Asbury Park, NJ

   https://doi.org/10.1016/j.cstp.2023.101073  

   Younes, Hannah; Noland, Robert B; Andrews, Clinton J (December 2023, Case Studies on Transport Policy)

   Micromobility usage has increased significantly in the last several years as exemplified by shared escooters and privately owned bicycles. In this study, we use traffic camera footage to observe the behavior of over 700 shared e-scooters and privately owned bicycles in Asbury Park, New Jersey. We address the following questions: (1) What are the behavioral differences between bicycle and e-scooter usage in terms of helmet use, bike lane / sidewalk use, gender split, group riding, and by time of day? (2) Are more protective conditions associated with helmet use and bike lane / sidewalk use? And (3) what is the gender split between e-scooter users and cyclists? We find notable differences in safety precautions: around one third of cyclists but no shared e-scooter users were observed wearing a helmet. Among cyclists, helmet use was more prominent among men than women. However, men were more likely to ride on the road than women. We also found that the gender split was narrower among e-scooter users, with a nearly even gender split – as opposed to cyclists, where only 21% of cyclists were observed to be women. Our findings suggest that e-scooter users take fewer safety precautions, in that they are less likely to use a bike lane and to wear a helmet. We conclude with policy implications with regards to safety and gender differences between these two modes. 

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5. Understanding the Relationships Among E-scooter Ridership, Transit Desert Index, and Health-Related Factors

   https://doi.org/10.1177/03611981221097094  

   Jiao, Junfeng; Degen, Nathaniel; Azimian, Amin (June 2022, Transportation Research Record: Journal of the Transportation Research Board)

   This study aims to analyze electric scooter (e-scooter) markets in transit deserts and oases in the U.S. The four cities of Austin, Chicago, Portland, and Minneapolis were selected as case studies to determine the prevalence of e-scooter rides as related to locations with limited public transportation options. A t-test was performed to analyze the difference in the number of e-scooter rides between the transit deserts and transit oases. Overall, the arithmetic means of the e-scooter rides between the transit deserts and transit oases were not significantly different in Austin, Chicago, and Portland. The results confirm that the transit index score was among the top three predictors of trips in Austin, Minneapolis, and Portland. In Chicago, health-related characteristics such as crude prevalence of arthritis, diabetes, and obesity were found to be the most important predictors of trips in Chicago. 

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