Safer Micromobility:
Technical Background Report
March 2024

George Yannis, Professor
Virginia Petraki, Research Associate

Philippe Crist, Senior Advisor

The International Transport ForumThe International Transport Forum is an intergovernmental organisation with 66 member countries. It
acts as a think tank for transport policy and organises the Annual Summit of transport ministers. ITF is
the only global body that covers all transport modes. The ITF is politically autonomous andadministratively integrated with the OECD.
The ITF works for transport policies that improve peoples’ lives. Our mission is to foster a deeper
understanding of the role of transport in economic growth, environmental sustainability and social
inclusion and to raise the public profile of transport policy.
The ITF organises global dialogue for better transport. We act as a platform for discussion and prenegotiation of policy issues across all transport modes. We analyse trends, share knowledge and promoteexchange among transport decision-makers and civil society. The ITF’s Annual Summit is the world’s largest
gathering of transport ministers and the leading global platform for dialogue on transport policy.
The Members of the Forum are: Albania, Armenia, Argentina, Australia, Austria, Azerbaijan, Belarus,
Belgium, Bosnia and Herzegovina, Brazil, Bulgaria, Cambodia, Canada, Chile, China (People’s Republic of),
Colombia, Costa Rica, Croatia, Czechia, Denmark, Estonia, Finland, France, Georgia, Germany, Greece,
Hungary, Iceland, India, Ireland, Israel, Italy, Japan, Kazakhstan, Korea, Latvia, Liechtenstein, Lithuania,
Luxembourg, Malta, Mexico, Republic of Moldova, Mongolia, Montenegro, Morocco, the Netherlands,
New Zealand, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, Serbia, Slovak
Republic, Slovenia, Spain, Sweden, Switzerland, Tunisia, Türkiye, Ukraine, the United Arab Emirates, theUnited Kingdom, the United States and Uzbekistan.

About the Corporate Partnership Board
The Corporate Partnership Board (CPB) is the ITF’s platform for engaging with the private sector andenriching global transport policy discussion with a business perspective. The members of the ITF Corporate
Partnership Board are: Airbus, Allianz Partners, Alstom, Amazon, Aramco, AutoCrypt, Bolt, Bosch, BP, CEIIA,
Cruise, DP World, Enel, ExxonMobil, FS Italiane, Honda, Hyundai Motor Company, Iberdrola, Kakao
Mobility, Michelin, Microsoft, Mott Macdonald, NXP, PTV Group, RATP Group, Rolls Royce, Shell, Siemens,
TotalEnergies, Toyota, Trucknet, Uber, Valeo and Volvo Group.

Disclaimer
Funding for this work has been provided by the ITF Corporate Partnership Board. This report is publishedunder the responsibility of the Secretary-General of the ITF. It has not been subject to the scrutiny of ITF
or OECD member countries and does not necessarily reflect their official views or those of the membersof the Corporate Partnership Board.

ACKNOWLEDGEMENTS

Acknowledgements
The authors of this publication are Virginia Petraki and George Yannis of the National Technical Universityof Athens (NTUA) and Philippe Crist of the International Transport Forum (ITF). Katerina Deliali (NTUA)
assisted with research coordination.
The authors would like to thank the following ITF Corporate Partnership Board representatives who
participated in the project workshop: Julian Alhers (Tier), Sarah Badoux (Voi), Georgia Heathman (Tier),
Enzo Lanoue (Allianz Partners), Victoria Delicado Montoya (ENEL), Christy Pearson (Voi), RobertMorgenstern (Allianz), Welmoed Neijmeijer (Bolt) and Tatiana Samsonova (Bolt).
Thank you also for other workshop participants who provided inputs at and after the workshop: Adil Bahi
(Ministère du Transport et de la Logistique), Alasdair Cain (United States Department of Transportation),
Pierpaolo Cazzola (University of California, Institute of Transportation Studies), Julien Chamussy (Fluctuo),
Chris Cherry (University of Tennessee), Wanda Debauche (Belgian Road Research Center), Laurent Demilie(SPF Mobilité et Transports), Storm Gibbons (TIER Mobility), Bjorne Grimsrud (Institute of Transport
Economics - Norwegian Centre for Transport Research), Firas Ibrahim (United States Department ofTransportation), Jade Kawan (Cabinet Elke Van den Brandt), Laurent Kennel (Dott), Konstantin Krauss(Fraunhofer Institute for Systems and Innovation Research ISI), Soichiro Minami (Ministry of Land,
Infrastructure and Tourism), Stefano Porro (Pirelli), Alexandre Santacreu (European Metropolitan
Transport Authorities (EMTA), Sebastian Schlebusch (Dott), Lidia Signor (UITP), Alejandro Tirachini(University of Twente), Anatole Reboul (Fluctuo), Karen Vancluysen (POLIS), Marie Vignat-Cerasa (Lime),
Ceri Woolsgrove (European Cyclists' Federation), Teruki Yamada (Ministry of Land, Infrastructure andTourism).
The authors would also like to thank Aisling Dunne (Bolt), Alex Liaw (Lime), Saša Jevšnik Kafol (AVPSlovenia) who provided additional inputs to the report and the following reviewers of the report: Andrea
John (DETEC – Switzerland), Benoît Hiron (CEREMA – France), Dominique Mignot (Université Eiffel and
ITRD), Riikka Rajamäki (Traficom – Finland), Manuelle Salathé (ONISR – France), Sebastian Schlebusch(Micromobility for Europe and Dott), Kishan Vandael Schreurs (VIAS-Belgium), Ceri Woolsgrove (European
Cyclists’ Federation).

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FOREWORD

Foreword
In 2020, the ITF published Safe Micromobility, a report assessing the safety of micromobility and new
mobility services. In the four years since publication, much has changed in terms of the evidence baseregarding the safety of micromobility.
This report analyses current evidence on recent micromobility safety trends and risks. It provides safety
recommendations for authorities and micromobility operators in line with the Safe System approach. It
does not address safety issues related to fire risk from defective or damaged battery packs which istypically addressed via battery-specific standards and policies.
It is summarised in a policy document written by the same authors. That publication, entitled “Safer
Micromobility” can be found here: https://www.itf-oecd.org/safer-micromobility.

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TABLE OF CONTENTS

Table of contents
Executive Summary ........................................................................................................................ 7
What we did .................................................................................................................................... 7
What we found................................................................................................................................ 7
What we recommend ..................................................................................................................... 8
Safe Micromobility ....................................................................................................................... 11
What is micromobility? ................................................................................................................. 11
Micromobility, safety and health .................................................................................................. 12
Methodology ................................................................................................................................. 12
Structure ....................................................................................................................................... 12
Key Micromobility Safety Trends .................................................................................................. 14
Micromobility crash and injury data.............................................................................................. 14
Safe infrastructure ........................................................................................................................ 23
Safe Riders..................................................................................................................................... 24
Safe vehicles .................................................................................................................................. 27
Summary of Key Micromobility Risk Factors.................................................................................. 31
Recommendations ....................................................................................................................... 33
Safety Recommendations for Authorities ..................................................................................... 33
Safety Recommendations for Operators ....................................................................................... 35
Conclusion ................................................................................................................................... 39
References ................................................................................................................................... 41

FiguresFigure 1. Definition of micromobility ............................................................................................ 11
Figure 2. Comparative description of e-scooter and bicycle riders’ injuries (AIS≥1) as apercentage of patients presenting with injuries to hospitals in the Department of theRhone in France in 2019 ............................................................................................................... 17
Figure 3. Various e-scooter and bicycle characteristics and safety ................................................. 30

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TABLE OF CONTENTS

TablesTable 1. Synthesis of the findings on e-scooter and e-bike injury severity and type........................ 15
Table 2. Shared e-scooter risk and e-scooter safety regulations across European markets ............. 19

Table 3. Micromobility collision types. .......................................................................................... 21
Table 4. Risk factors related to infrastructure associated with micromobility safety ...................... 23
Table 5. Risk factors related to users associated with micromobility safety.................................... 25
Table 6. Key micromobility risk factors. ......................................................................................... 32

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EXECUTIVE SUMMARY

Executive Summary
What we did
The objective of this report is to comprehensively analyse and synthesize the most recent and key
micromobility safety trends and risks and to formulate safety recommendations for both authorities andmicromobility operators. Specifically, this report zooms in the safety implications of privately-owned or
shared powered micromobility devices, with a particular emphasis on e-scooters and e-bikes. The safety
analysis and recommendations are founded on the Safe System Approach, aimed at raising safety
standards and effectively mitigating risks within the micromobility ecosystem, including road users,
infrastructure, and vehicle design.
In the framework of this report an extensive review of scientific and "grey" literature to investigate key
micromobility safety trends and risks was conducted, covering areas such as crash and injury trends, issues
related to under-reporting of crashes, risk factors related to vehicles, users, and infrastructure, and theutility of surrogate safety data. A total of 145 relevant studies were identified, including peer-reviewed
papers and reports from policy organizations, government agencies, and service providers.
A questionnaire was administered to five micromobility operators thoughtfully arranged in alphabeticalorder: Bolt, Dott, Lime, TIER Mobility, and VOI. This questionnaire served a dual purpose. Firstly, it was
tailored to gather comprehensive insights into the safety aspects encompassing both the physical features
and the increasingly vital digital facets, including app-based functionalities of micromobility vehicles.
Secondly, it aimed to identify challenges and lessons-learned from the deployment of micromobility
vehicles.

What we foundThe introduction of powered micromobility vehicles, including e-scooters and e-bikes in many cities, has
ushered in significant changes in urban transportation, presenting new and pressing challenges forpolicymakers and stakeholders. This transformation coincides with a growing public concern surrounding
the upswing in micromobility-related crashes and their severity. Even though micromobility-related
crashes attract publicity, they consist of a low percentage of the overall crashes inside and outside cities.
Most micromobility-related crashes are single-vehicle crashes of low severity, whereas collisions withlarger motor vehicles lead to higher-severity injuries. Also, most reported micromobility crashes result in
only minor injuries. Severe injuries comprise a small portion of total reported injuries, and a relatively small
percentage of reported micromobility crashes lead to fatal injuries. E-scooterists presented to hospitals
with a greater share of head, face, and neck injuries than cyclists. Injury severity is correlated to crashmechanisms, vehicle types and road users.
In addition to crash frequency, casualty risk reflects the probability of crashes and their severity. Overall,as shared e-scooter travel volumes outpace the growth of injuries requiring medical attention, e-scooter
risk has diminished across various markets. However, good quality and representative data on e-scooter
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EXECUTIVE SUMMARY

exposure and crashes is often not available, mainly for privately-owned e-scooters. Shared and especiallyprivately-owned micromobility safety analysis would highly benefit from the existence of more consistentand available exposure and safety data to ensure more reliable risk estimations for injuries and crashes.
This report underscores the multifaceted nature of micromobility and, particularly, e-scooter safety. Escooter-related incidents predominantly involve single road users, resulting in falls and collisions withstationary objects. Pedestrians are injured through collisions with either moving or stationary e-scooters.
The gravest danger emerges from conflicts between micromobility vehicles and larger motor vehicles,
often leading to fatalities.
Night-time riding, drug or alcohol-impaired riding, riding in traffic lanes or on sidewalks and encountering
poorly maintained road surfaces all contribute to elevated crash and injury risk. Helmet use is low among
injured e-scooterists, and this contributes to the frequency, severity and type of reported injuries. Vehicle
design plays an important role in crash occurrence and severity with e-scooters displaying different andless stable characteristics than bicycles. Shared e-scooter designs have evolved rapidly to incorporate
safety-improving features and make these available to riders.
E-scooter crashes disproportionately lead to head and facial injuries, particularly in the lower face region,
compared to crashes involving conventional or electric bikes. Head injuries are significant in that they may
involve serious and lasting trauma and related neurological complications – in this way, they are unlike
other injury types and warrant special consideration. E-scooter crashes also often lead to fractures in theupper and lower extremities, particularly in the lower arm and wrist. Generally, injuries involving escooters are more severe than injuries involving conventional bikes and lighter than injuries involving ebikes – likely linked to the more elevated travel speed of the latter.
In the case of micromobility safety, surrogate safety-based analyses are useful as they shed light to user
behaviour and potential precursor factors and crash mechanisms (e.g. time to collision, harsh accelerationand deceleration, speeding, helmet use, double riding, etc.). Due to advances in modelling and technology,
surrogate safety methodologies and analyses are expected to further grow.

What we recommend
Understanding the causes and mechanisms behind micromobility crashes and identifying risk factors
implies that many of these incidents are preventable through coordinated efforts by the authorities andthe micromobility operators. These recommendations are summarised below.
Safety Recommendations for Authorities
Safe Infrastructure
Proactively maintain micromobility infrastructure: To minimise the risk of micromobility-related crashes
caused by potholes, debris etc., authorities should undertake regular maintenance of infrastructure,especially in high micromobility traffic areas.
Establish a dedicated and well-connected micromobility network: Authorities should develop acomprehensive urban plan that incorporates mixed and protected “light traffic lanes” for all micromobility
modes, ensuring connectivity with existing transportation networks.
Establish and enforce micromobility parking policy and designate parking areas where needed: Authorities
should formulate consistent micromobility parking guidelines that enhance its use. This includes

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EXECUTIVE SUMMARY

establishing clearly marked and well-delineated parking zones for e-scooters and bicycles at the curb or
on pedestrian or shared zones, mainly in core urban areas.
Safe Riders
Implement a 30km/h (or lower) speed limit in areas with high micromobility use: Authorities should default
to 30 km/h (or 20 km/h) speed limits for car and truck traffic in areas with high micromobility traffic.
Establish low speed limits for micromobility vehicles on pedestrian or shared zones: In areas where
micromobility users share pedestrian spaces, authorities should default to a safe speed limit (e.g. ~6-10km/h) for micromobility modes, to reduce the conflicts between micromobility riders and pedestrians.
Take enforcement action against risky micromobility riding: Authorities should impose and enforce
penalties for illegal micromobility riding including such as speeding, drug- or alcohol-impaired riding,underage riding, and double riding.
Promote the use of appropriate helmets: Authorities should encourage use of appropriate helmets forprivate and shared micromobility insofar as helmet promotion messages do not depress the use of active
micromobility.
Introduce rider education in secondary schools: Micromobility training should be integrated into thecurriculum of secondary schools.
Safe Micromobility Vehicles
Set universal technical requirements for e-scooter design: Establishing and converging technical standards
for e-scooter is essential.
Adopt riding support systems in micromobility: Authorities should foster the adoption of riding support
systems in micromobility vehicles including, for example, emergency braking assistance, audible speed
warnings, ride condition detection technology, occupancy detection sensors, inappropriate parking
notification, etc.
Safe Management
Establish and collect data on distinct micromobility categories in safety statistics: Creating distinct
categories for each micromobility mode in road traffic casualty records, including police records andmedical records, improves safety assessment.
Safety Recommendations for Operators
Safe Infrastructure
Establish collaborative partnerships with authorities for infrastructure condition reporting: Micromobility
operators, armed with valuable data collected through in-vehicle sensors on potholes, falls, and nearcrashes, should play an active role in the proactive maintenance of urban infrastructure.
Integrate parking zones in shared micromobility apps and deploy smart docking in high-traffic areas:
Shared micromobility apps should onboard designated parking areas and restrictions. Also, operators canreinforce responsible parking, e.g. by offering rewards for users who comply with parking requirements orin docks if these are available.

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Safe Riders
Provide safety feedback via telematics data: Operators can use telematics data on speeding,acceleration/deceleration or distracted riding to provide riders with post-trip feedback. Real-time safety
alerts to riders could also be considered where these do not contribute to rider distraction.
Provide economic incentives for safe riding: Shared micromobility operators may encourage helmet use
with economic incentives such as providing free helmets or discounts to encourage safety-conscious
ridership.
Implement mandatory initial rider training: To enhance rider safety, shared micromobility operators canrequire new riders to pass through in-app safe riding screens for the first few rides they make to help
ensure that riders are familiar with local rules and guidelines before embarking on their e-scooter trips.
Verify age to start riding: Operators should implement age verification procedures to ensure riders meetthe minimum age requirements defined in each city, ensuring compliance with local regulations and safety
standards.
Safe Micromobility Vehicles
Ensure systematic maintenance of micromobility fleets: Operators should maintain their fleets in good
repair and follow state-of-the-art maintenance protocols, emphasising regular checks and upkeep of
essential components, including brakes, lights and batteries.
Enable context-dependent maximum speed control – geofencing: Shared micromobility operators canemploy geofencing technology to dynamically lower maximum speeds in high-risk zones, such aspedestrian areas and junctions and during risky hours like nighttime.
Switch off e-scooter access if double riding or/and alcohol use is detected: Shared micromobility operators
should be encouraged to incorporate in-vehicle sensors to detect double riding and introduce in-app tests
to identify users under the influence of alcohol and drugs.
Implement riding support systems in shared e-scooters: Operators should be encouraged to implement
riding support systems in e-scooters
Safe Management
Enable in-vehicle or in-app crash detection technology:
Shared micromobility operators can enhance the safety and user experience of their services and address
the low micromobility crash data availability by integrating crash detection technology into their vehicles
or mobile applications.

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SAFE MICROMOBILITY

Safe Micromobility
The uptake of micromobility has been catalysed by the arrival of e-scooters and e-bikes – both privatelyowned and shared. These vehicles and their use confers benefits to people and to cities but also raises
challenges, particularly with respect to safety and their insertion in busy city spaces that are largely
dominated by cars.
In 2020, the ITF published the report titled "Safe Micromobility" assessing the safety of micromobility andnew mobility services (ITF, 2020). In the three years since publication, much has changed in terms of theevidence base (especially for safety) and changes in technology and operations.
The objective of this report is to comprehensively analyse and synthesise the most recent and key
micromobility safety trends and risks and to formulate safety recommendations for both authorities andmicromobility operators. These recommendations are led by the Safe System Approach and seek tocontribute to the improvement of safety standards and mitigate risks associated with micromobility users,
infrastructure and vehicles.

What is micromobility?
This report focuses on the safety impact of micromobility as defined by the ITF in the report “Safe
Micromobility” (Figure 1- ITF, 2020) and specifically on e-scooters and e-bicycles (or e-bikes). Both shared(i.e., operated by riders on a for-hire basis) and privately-owned e-scooters and e-bikes are considered
and, when possible and relevant, these are addressed separately.
Figure 1. Definition of micromobility
What is micromobility?
Type A

Type BThe term “micromobility” covers the use of micro-vehicles
with a mass of no more than 350 kilograms (771 pounds)
and a design speed no higher than 45 km/h (28mph). ITF
identifies four types of micromobility vehicles based on
mass and speed:
Type A: powered or unpowered vehicles weighing lessthan 35 kilograms and with a maximum powered
design speed of 25 km/h.
Type B: powered or unpowered vehicles weighing
between 35 kilograms and 350 kilograms andwith a maximum powered design speed of 25
km/h.
Type C: powered vehicles weighing less than 35 kilograms
and with a design speed between 25 km/h and 45
km/h.
Type D: powered vehicles weighing between 35 kilogramsand 350 kilograms and with a design speed
between 25 km/h and 45 km/h.

Type CType D

Micromobility vehicles come in a range established (e.g.
bicycles) and less established and rapidly evolving form
factors (e.g. standing or seated E-scooters, electricunicycles, powered skateboards, etc…).
Some of these vehicles are homologated for use on roads,
others not. Some are allowed to be used in pedestrianenvironments – sidewalks and pavements – in somecountries and cities but not in others.
Finally, some micromobility vehicles require human exertion
to move (bicycles, non-throttled e-bicycles, kick-scooters,
skateboards, etc.) and others accelerate and move only withdirect traction from a motor. The former active modes
confer important health benefits whereas the latter do not.

Micromobility plays an important role in daily mobility on its
own or in conjunction with other modes, is highly popular inmany contexts, is suited to many trips and is moreenvironmentally sustainable than heavier and larger
vehicles.

Source: ITF (2020)

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Micromobility, safety and health
Physical activity is a crucial determinant of the overall contribution of safety to overall health. If safety is aconcern for micromobility, it is because crashes and ensuing injuries negatively impact health and impose
personal and societal costs. Exposure to air pollution also imposes a health burden on micromobility riders.
Physically active forms of micromobility, however, confer significant health benefits across multiple healthendpoints. Safety impacts from micromobility use must be considered in the overall context of healthimpacts. On balance, active travel’s positive contribution to good health is orders of magnitude greaterthan the negative health impacts of crashes and air pollution (ITF, 2013; 2024).
From a health– perspective, active and passive forms of micromobility are not on the same footing. While
micromobility modes like cycling and electrically-assisted cycling are physically active, other electricallypowered micromobility modes, such as e-scooters, offer marginal benefits in terms of physical activity (ITF,
2024; Djokic et al., 2023; Haufe et al., 2022; Bourne et al., 2018; Bretones, A. and Marquet, O. 2023;
Sanders et al., 2022). Nonetheless, e-scootering and other forms of non-active micromobility are generally
associated with more active lifestyles, possibly linked to the greater use of micromobility in conjunction
with public transport and other non-car modes. A key, context-based factor to consider when looking at
micromobility-linked health outcomes is the extent to which non-active micromobility replaces walking
and cycling versus highly sedentary car travel. Policy must seek to ensure the highest overall healthoutcomes, and thus, it must balance the positive health contributions of active micromobility modes
versus the negative health outcomes of all micromobility when assessing safety and other policies.

Methodology
To investigate key micromobility safety trends and risks, an extensive review of the scientific and “grey”
literature was conducted. This research explores the following aspects: 1. crash trends, 2. injury trends, 3.
issues related to crash under-reporting and exposure data and their implications with the safety outcome,
4. risk factors related to vehicles, users and infrastructure, 5. findings and usability of surrogate safety data.
Findings at the international level regarding the two modes were summarised and synthesised. 145
relevant studies were identified and considered appropriate for this review. The year of publication of escooter studies range from 2018 and 2023. The majority of these studies are based on 2018-2021 data.
Publications on e-bikes range from 2007 to 2022 and are based on data from the same period.
In addition, a questionnaire was developed and completed by a group of five micromobility Operators:
Bolt, Dott, Lime, TIER Mobility, and VOI. This questionnaire served two purposes. Firstly, it was tailored togather comprehensive insights into safety aspects encompassing both the physical and digital aspects of
micromobility vehicles and services. Secondly, it aimed to identify challenges and lessons learned from thedeployment of such vehicles.

Structure
The section “Key Micromobility Safety Trends “ discusses studies that analysed crash and injury data toassess the safety of e-scooters and (e-)bikes. It analyses the findings from the literature on micromobility
injury severity level and addresses types of crashes, crash and injury risk, and under-reporting andassociated risk factors with riding behaviour, infrastructure, and vehicle design.

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The section “Key Micromobility Risk Factors” synthesises the key risks associated with micromobility
safety.
The section “Recommendations” presents targeted safety recommendations for both micromobility
operators and local authorities, categorized into three critical areas: safe infrastructure, safe users, andsafe micromobility vehicles.

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KEY MICROMOBILITY SAFETY TRENDS

Key Micromobility Safety Trends
This chapter presents the analysis of the findings from the literature on:• e-scooter and e-bike crashes and injuries,• risk factors considering various exposure measures related to users,• risk factors related to road and cycling infrastructure,• the design features of micromobility vehicles, that have been found to affect safety.

Micromobility crash and injury data
Micromobility crashes

The great majority of the literature on micromobility safety focuses on the injury outcomes of e-scooter
and e-bike or conventional bike crashes. Table 1 presents the findings of recent studies on injury severity
and injury type. Minor injuries emerge as the most prevalent severity level within reported micromobilityrelated crashes, while more severe injuries comprise a small portion of total reported injuries. With respect
to all injuries, according to available data and studies, fatal injury rates are very low (<1%) and without
clear difference between e-scooters, e-bikes, and conventional bikes (Table 1).
Considering only severe trauma injuries, the rates are higher (<10%) than rates reported for all-injury
crashes. Considering only patients displaying severe trauma symptoms and accordingly admitted into
major trauma centres in France, in-hospital fatality rates among severely injured patients are predictably
higher than rates reported for all-injury crashes -- 9.2% for e-scooters, 10% for conventional bicycles and5.2% for motorbikes (James et al., 2023). James et al. (2023) also registered a near tripling of e-scooter
admissions (+185%) to major trauma centres from 2019 to 2022, compared to a 24% increase for bicycles(electric and conventional) and a 12% decrease for motorbikes. This growth indicates an increase in severe
trauma-related e-scooter crashes in France. The relative shares of the overall trauma centre admissions
for e-scooterists, cyclists and motorcyclists over the same period were 4%, 17% and 78%, respectfully(James et al., 2023). Furthermore, according to Clough et al. (2023), 2.7% of e-scooter riders and 1.7% of
cyclists experienced major trauma leading to fatalities.
The severity of injuries is correlated with the crash mechanism, the vehicle type and road users involved(Kazemzadeh et al., 2023). E-scooter crashes mainly result in head and face injuries, as outlined in Table 1
and Figure 2, with a notable concentration of maxillofacial injuries observed in the lower third of the face(i.e., chin and jaw) (Benhamed et al., 2022; Grill et al., 2022; Kim et al., 2022; James et al., 2023;). Cyclists
also present with maxillofacial injuries even when wearing helmets (Benjamin et al., 2019), albeit at lower
rates than e-scooterists (Niemann et al., 2023). Severe trauma e-scooter and bicycle patients presented
with traumatic brain injuries at double the rate of motorcyclists (22% for e-scooterists and 19% for cyclists
vs. 11% for motorcyclists) (James et al., 2023).
Besides head/face injuries, upper and lower extremities injuries are also common among e-scooter crashes(Toofany et al., 2021; Serra et al., 2021; Stormann et al., 2020). Fractures, particularly involving the lower
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KEY MICROMOBILITY SAFETY TRENDS

arm and wrist, are common among e-scooter riders, as is lower extremity trauma (Benhamed et al., 2022;
Cicchino et al., 2021; National Academy, 2023). It is important to highlight that the majority of injury
categories are not mutually exclusive, and numerous patients presented with more than one injury typeor location.
The mechanics of e-scooter crashes explain some of these outcomes. E-scooter riders are free-standing
and upright and present a high and forward centre of gravity. Loss of control crashes result in riders either
attempting to hop off the e-scooter (contributing to lower extremity and foot injuries) or – in the case of
forward obstacle crashes – being catapulted forward and over the handlebar and steering column. Suchvaulting injuries result in upper extremity injuries as riders seek to break their fall or in a high incidence offace and head injuries as face- or head-first ground contact occurs before the rider can brace themselves(Arbel et al., 2022; Como et al., 2022; Chontos et al., 2023; Matt et al. 2022; Fournier et al., 2023; Paudel,
2019; Paudel and Yap, 2021; Serra et al., 2021; Wei et al., 2023). Alcohol consumption further suppresses
reaction times, leading to a high incidence of head and face injuries for alcohol-inhibited e-scooterists(Shiffler et al., 2021).
Table 1 summarises recent studies describing e-scooter, conventional bike and e-bike injury types andseverity. “No injury” events are crashes where the persons involved experience no injury at all. “Minor
injuries” refer to injuries ranging from lacerations to minor wounds to hospital visits with no significant
medical procedures (e.g., no hospitalization, imaging, surgery, etc.). Severe injuries refer to injuries that
require significant medical attention and, in some cases, hospitalisation. A lack of common terminology
describing injury severity level complicates analysis. Some records refer to Injury Severity Scores (ISS) or
the Maximum Abbreviated Injury Scale (MAIS) code, while others simply note whether the patient arrived
at the medical facility as a “walk-in” or by ambulance. E-scooter injuries have an ISS ranging from 1 to 5.5(Toofany et al., 2021).
Table 1. Synthesis of the findings on e-scooter and e-bike injury severity and type
Injuries

Incident description

VehicleType

EffectNo injury(% of riders)

es

6-9%

es

56-70%

eb

65-70%

es

8-13%

eb

5-17%

es

<1%

eb

<1.3%

cb

<0.2%

Minor injury

Severity(% of casualties)

Severe injury

Fatality

15

SourceBadia and Jenelious, 2021; Weidemannet al., 2022
Siman-Tov et al., 2017; Badia andJenelious, 2021; PACTS, 2021;
Weidemann et al., 2022; Tian et al., 2022;
Stray et al., 2022
Siman-Tov et al., 2017; Chen and Dai,
2018
Siman-Tov et al., 2017; Stray et al., 2022;
Weidemann et al., 2022; Meyer et al.,2022; Vesselinov et al., 2023
Siman-Tov et al., 2017; Chen and Dai,
2018; Meyer et al., 2022
PACTS, 2021 (1%); MMfE, 2021 (0.07%);
Williams et al., 2022 (0%); Benhamed etal., 2022 (0.1%); Younes et al., 2023
(0.09%)
Qian & Shi, 2023 (1.3%); Younes et al.,2023 (0.15%)
Benhamed et al., 2022 (0.2%); Younes etal., 2023 (0.23%)

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Injuries

Upper extremity

VehicleType
es

Lower extremityes

23-45%

es

Head: 18-41%
Face: 30-60%

cb

Head: 20-24%
Face: 20%

Alwani et al., 2020; PACTS, 2021; Stigson
et al., 2021; Uluk et al., 2021; Benhamed
et al., 2022; Orozco-Fontalvo et al., 2023;
Leyendecker et al., 2023
English et al., 2020; Alwani et al., 2020;
Toofany et al. 2021; Stigson et al., 2021;
Benhamed et al., 2022; Kleinerzt et al.,2021 & 2023; ; Leyendecker et al., 2023
Benhamed et al., 2022; Laverdet et al.,
2023

eb

Head: 35%

Laverdet et al., 2023

Incident description

Injured Body
Region (% ofcasualties)
Head/ Face

EffectSource25-55%*es: e-scooters, eb: e-bikes, cb: conventional bikes*casualties: persons injured and fatalities

E-scooter injury patterns are different from the ones observed in the case of injured cyclists; conventional
cyclists reported lower percentages in the above injury types and mainly in head/face and lower limbs(Stray et al., 2022; Benhamed et al., 2022; Clough et al., 2023; Laverdet et al., 2023; Niemann et al., 2023).
E-scooter riders experience up to twice the incidence of severe head injuries and between 50% to 100%
more maxillofacial injuries compared to conventional cyclists, potentially leading to a higher proportion of
hospital admissions due to substantial trauma associated with e-scooter use (Benhamed et al., 2022;
Clough et al., 2023; James et al., 2023). However, a comprehensive study analysing records from around
100 U.S. hospitals in 2021-2022 revealed that individuals with e-scooter injuries are more likely to betreated and released (85%) compared to e-bike (81%) or bicycle injuries (79%), albeit not by a significant
margin. Despite variations in injury patterns, fatal incidents remain uncommon across micromobility
modes, with a slightly higher proportion noted among cyclists based on 2021-2022 datasets (Younes et al.,2023).
Figure 2 illustrates the differences in injury types and severity between nearly 3,000 e-scooterists andcyclists presented to hospitals in the Rhône Department of France. E-scooterists presented with a greater
share of head, face, and neck injuries than cyclists. This may partly be explained by the much lower
incidence of helmet use amongst e-scooterists, though helmets generally do not prevent head, face andneck injuries. A higher incidence of alcohol-involved crashes for e-scooterists may also help explain thesedifferences. Injuries to lower extremities are more prevalent in this population for e-scooterists ascompared to cyclists – possibly reflecting injuries sustained as e-scooterists hopped off their e-scooter justbefore, or at the moment at which, they lost control.

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Figure 2. Comparative description of e-scooter and bicycle riders’ injuries (AIS≥1) as a percentage ofpatients presenting with injuries to hospitals in the Department of the Rhone in France in 2019
E-scooter

Bicyclen=825 (29.7%)

n=1954 (70.3%)

Helm et use 6.1%
Head 24.2%
Severe injury (>AIS3) 1.9%

Helmet use 30.7%
Head 19.9%
Severe injury (>AIS3) 1.0%

Face 30.6%

Face 20.5%

Neck 3.3%

Neck 2.5%

Thorax 7.3%

Thorax 9.0%

Spine 6.7%

Spine7.9%

Upper
extrem ities
48.9%

Upper
extremities
57.6%

Abdomen Pelvis
3.4%

Abdom en Pelvis
3.2%

Lower extremities
41.8%

Lower extrem ities
38.8%

Admitted tointensive care
2.1%

Adm itted tointensive care
1.7%

E-bike injury patterns are also distinct from e-scooter and conventional bicycle injury profiles. E-bike riders
are more likely to suffer internal injuries compared to e-scooter riders, whose injuries are nearly threetimes more likely to result in concussion (DiMaggio et al., 2022). Several studies conclude that injuries
involving e-bikes were more severe than injuries involving e-scooters, with the higher relative speed oftravel cited as a contributory factor (Arbel et al., 2022; Cicchino et al., 2021; Hamzani et al., 2021; DiMaggio
et al., 2022). Laverdet et al. (2022) present a contrary finding that e-scooter injury severity was higher
compared to e-bike and conventional bike injury severity. However, a study in the United States concludes
that injuries associated with e-scooters exhibited greater similarities to injuries related to conventional
bikes rather than to those related to e-bikes (National Academy, 2023).
The literature on the safety of e-bikes compared to conventional bikes is relatively sparse and mainly
covers the pre-pandemic era. Existing studies tend to be concentrated in certain European countries, some
US states, and China. Several studies in European countries where e-bikes are allowed to offer pedal
assistance up to 25 km/h showed that e-bike crashes are, in general, equally severe as conventional bikecrashes (Schepers et al., 2014; Weber et al., 2014; Weiss et al., 2018; Fyhri et al., 2019; Schepers et al.,2020).
Micromobility crash risk

While crash data provide valuable insights into the absolute frequency and severity of crashes, acomprehensive safety assessment involves understanding crash risk. Risk reflects both the crash severity
as well as the probability of its occurrence. It is characterised as the number of crashes or casualties(fatal
crashes, crashes with hospitalised or fatally injured victims, fatalities, persons injured) over a metric of
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exposure (such as the overall distance travelled). Crashes may be captured in aggregate but a policyrelevant expression of crash risk should account for disaggregate crash characteristics. Accordingly,
crashes may be characterised according to severity, type or type of injured party. Exposure metrics canvary as well – when no trip-related data is available, risk may be expressed as a crash rate per population.
More policy-relevant exposure metrics capture either trip numbers, distances travelled or commuting
duration. Distance-based metrics are appropriate for exposure of motorized vehicles, but they are notideal for comparing motorized and non-motorized modes (e.g., bikes) as the latter tend to have trips of ashorter length (Vanparijs et al., 2015). Crash risk in this study is expressed as a rate of crashes (or varying
severity) per number of trips or, alternatively, per vehicle kilometres travelled.
Policy should seek to avoid all crashes and eliminate all severe or fatal injury ones. Paradoxically, however,exposure-adjusted crash risk may diminish even with a rise in absolute crash numbers if trips or distances
travelled increase at a higher rate than crashes. According to Safe System frameworks, there is a clear
difference between measuring crash risk and its evolution and the formulation of policy objectives –theseshould not be conflated. It is one thing to note that increased crashes are accompanied by a reduction of
overall crash risk, but quite another to target decreased crash risk as an objective, even when this isdelivered despite a concomitant increase in crashes. Policy targets should not solely target incremental
crash risk improvements but, rather, should primarily aim to eliminate the risk of severe or fatal crashes.
Challenges persist in determining whether observed micromobility safety trends result due to changes insafety or exposure. Addressing these challenges requires improved collection of micromobility-related
crash data, particularly for light-injury and non-injury crashes, from hospital/health authorities and thepolice, ensuring proper vehicle coding in crash/injury reports and more detailed data on micromobility
exposure, categorized by vehicle type. These processes are distinct and involve different authorities.
Available evidence indicates that, as shared e-scooter travel activity outpaces the growth of injuries
requiring medical attention, shared e-scooter risk has diminished in Europe and the US. The following tableprovides a comparative overview of casualties requiring medical treatment (on-site emergency or
hospitalisation) per million shared e-scooter trips across various markets (MMfE, 2023), highlightingchanges between 2022 and 2021, together with existing micromobility regulations in each market (ETSC,
2023). As this data refers to commercial shared e-scooter services involving certain types of vehicles, users,
experience levels and uses, these findings do not reflect the evolution of overall e-scooter risk-taking also
into account not negligible underreporting, especially of single-vehicle crashes.

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Table 2. Shared e-scooter risk and e-scooter safety regulations across European markets
Shared e-scooter
casualties requiring
medical treatment
per Mio trips

E-scooter Safety Regulations

Market

2021

2022

YoY%

Min
age
(y/o)

Max
Max
Ride onDrink-ride
speed powerpavements?
limit(km/h)(w)

Austria4.1

1.5-63.6%

12

25

600

No1

Belgium

7.1

7

-1.8%

16

25

NA

Bulgaria

NA

NA

NA

16

25

Cyprus

NA

NA

NA

14

Czech Rep

9.2

15.6

69.3%

Denmark

8.6

14.8

Finland

5

FranceHelmetrequired

Mandatory
insurance

0.8<12 y/oNo

No

Same as
car

No

No

NA

Yes1

NA

<18

No

20

NA

Yes1

0.5

Yes

No

NA

25

250

>10 y/o

No

<18

No

72.3%

15

20

NA

No

Same asmopeds2.9-41.6%

No

25

1000

No

9

12.1

34.8%

12

25

NA

No1

Germany

4.3

4

-7.7%

14

20

500

No1

Greece

NA

NA

NA

15

25

NA

Yes1

No

Yes

No

Italy

12.1

4.4

-63.3%

14

202

500

No

NA

<18

No5

Norway3.2

2.7-17.5%

12

20

NA

No

<15

No

Poland

4.9

4.5

-8.0%

10

20

NA

Yes1

No

No

Portugal

22.3

25

12.0%

No

25

1000

>10 y/oNo

No

Slovenia

NA

NA

NA

144

25

NA

No

0.5

<18

No

Spain

22.4

14.8

-34.1%

14-16

25

1000

No

Same ascars

Sweden

5.2

5.3

0.5%

NA

20

250

NA

NA

Switzerland

2.2

4.4

100.3%

163

20

500

No1

UK

31.9

20.6

-35.5%

1625

500(trials)

No

Cumulative-25.7%

Yes(>Jan 2022)
Yes - asNo
bikes
Forbidden Recommen
to ridededSame asNo
car

Same ascars
Forbidden
to rideSame ascars

Same ascars
Same ascars

Yes(>March2022)<15 - as
bikes

Yes
No
Yes
Yes

No5
NA

No

No

No

Trial51“local” authorities can make exceptions (e.g., if no cycling lane, travel speed up to 6 km/h, if the road speed limit is<30km/h or <50 km/h, riders aged 14-16 should only ride them on bicycle lanes etc.).
2
6km/h in pedestrian areas.

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3

14 with moped license.
12, with cycling licence.
5
required for sharing providers.
Sources: MMfE, 2023; ETSC, 2023
4

Table 2 reveals a wide variation in micromobility regulations across European markets, reflecting the
evolving nature of e-scooters as a travel mode. Safety regulations like helmet requirements and age limits
exhibit considerable variation based on the market, type of micromobility vehicle, and whether they are
privately-owned or shared. Shared e-scooter casualty risk has fluctuated across markets, with some seeing
substantial increases (e.g., Denmark and Switzerland) and others experiencing decreases (e.g., Austria and
Italy). The decrease of shared e-scooter risk can be partly attributed to increased attention to safety andthe uptake of a “safety culture” among operators and users. Italy's remarkable safety performance canalso be credited to the recent mandatory enhancements in e-scooter features, such as the incorporationof front and rear brakes along with direction indicators (yellow flashing lights, both front and rear). These
specifications are required for all new e-scooters introduced to the market since October 2022 (European
Consumer Centre Germany, 2023). It is noteworthy that these safety regulations collectively contribute to
the cumulative e-scooter casualty risk reduction across markets (-25.7%).
In markets where a reduction in shared e-scooter casualty risk is observed, several common regulatory
measures were taken aiming to improve risk, yet further investigation is required to provide clarity on their
specific road safety impact. These include the enforcement of minimum age requirements for riders, theimposition of maximum design speed limits and helmet use.
MMfE also reports that the risk of injury requiring medical treatment is comparable between shared escooters and shared e-bikes (MMfE, 2023a). Furthermore, the insurer AXA's findings for the period
between 2019 and 2022 highlight that the crash risk of shared e-scooters in Europe is 20 times lower
compared to mopeds (MMfE, 2023b). However, an analysis of the UK Department for Transport STATS19
data on shared e-scooters reveals a provisional rate of 13 casualties per million miles, approximately threetimes higher than the rate for pedal cycles (DfT, 2022). In alignment with these findings, a study by Cicchino
et al. (2021b) indicates that the estimated Emergency Department (ED) visit rates per million miles
travelled were higher among e-scooterists compared to cyclists (E-scooters: 20.7 emergency department
visits per million miles travelled, Bikes: 5.5 Emergency Department visits per million miles travelled).
Finally, it should be noted that e-scooters are riskier than cars for their users (Rix et al., 2021) even if cars
are a much greater source of danger to other traffic participants.
Collision types

E-scooter-related crashes differ from other modes in that their great majority involve the rider and noother road user. Toofany et al. (2021) refer to those events as single-road user collisions and found thatthey account for almost 93% of all reported e-scooter-related injuries. Single road user collisions usuallyrefer to falls, collisions with stationary objects, loss of vehicle control etc. In addition, it is essential toacknowledge the potential risk of collisions involving e-scooters tripping over pedestrians.
As shown in Table 3, several studies and analyses have quantified the number of single-road user collisions
as a percentage of the total e-scooter-related crashes and injuries. Lime analysed data from their records
and found that in Paris and New York City, single road user collisions accounted for 79% and 80% of allrecorded crashes of their shared e-scooters (Lime, 2022). Looking at police-recorded crash statistics,
Heydari et al. (2022) found that only 4% of all police-recorded crashes in the UK were due to single-road
user collisions compared to 79% involving other motorised vehicles and other parties and 17% involving

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pedestrians. The low-fall rate in the UK data likely reflects a known bias in police records towards crashes
involving motor vehicles or crashes resulting in serious injuries, and thus UK data under-represents overall
single-road user collisions since these generally do not involve motor vehicles and result in injuries thatare generally less severe.
E-scooter-related casualties resulting from falls constitute a substantial proportion of overall e-scooterrelated casualties(64-85%). This range compares with the respective percentage of cyclists’ casualties due
to falls (75%; Kleinertz et al., 2021). Also, Benhamed et al. (2022) confirm that most e-scooter and bicycle
road collisions are consequent to a fall or loss of vehicle control. Single road user collisions also involve
collisions with stationary objects. Compared to falls, the latter concerns a lower percentage of all escooter-related injuries, as shown in Table 2.
Several studies have analysed injuries and fatalities data to assess the impact of motor vehicles on escooter safety. Across these studies, injuries resulting from e-scooter-motor vehicle collisions account for
8-19% of all e-scooter-related injuries, a slightly higher proportion than bicycle injuries stemming fromcollisions with motor vehicles. In the United States, multiple studies conclude that motor vehicle collisions
are greatly responsible for e-scooter-related fatalities (NTSB, 2022), accounting for more than 80% of escooter fatalities. This percentage is comparatively smaller than bicycle fatalities attributed to motor
vehicle collisions, which range from 93 to 96% based on National Highway Traffic Safety Administration(NHTSA) statistics from 2020 and 2019, respectively (NHTSA, 2022; NHTSA, 2021). Shah et al. (2021) notethat 1 in 10 reported motor vehicle crashes with e-scooters or bicycles result in the injury or death of thee-scooterist or cyclist.
Pedestrians are uniquely exposed to e-scooter crash risk. This is partially because, in some countries, escooters operate legally or illegally on the sidewalk in the presence of pedestrians, especially in theabsence of bicycle infrastructure (Badia and Jenelius, 2021). Additionally, pedestrians are affected byillegally or poorly parked e-scooters (Zuniga-Garcia et al., 2021; Brown et al., 2020; James et al., 2019). The
co-existence of pedestrians and e-scooterists results in pedestrian injuries (1 to 10% of all e-scooterrelated casualties). Pedestrians are injured through a collision (30%) or by tripping over a parked e-scooter(59%).
Table 3. Micromobility collision types.
Vehicletype

EffectSingle road user

es

93%

Multiple road userses

7%% of tot. crashes

es

79-90%

es64-85%

cb

75%

es

1-39%

es

8-19%

cb

10%

Collisions
Involved road
users (% ofcasualties)

Falls% of casualties% of casualties
with objects
with
motor
vehicles21% of casualties

SourceToofany et al. 2021
Badia and Jenelious, 2021;
Heydari et al., 2022;
Lime, 2022
Bloom et al. 2020; English etal., 2020; Kleinertz et al.,2021; Azab et al., 2022
Kleinerzt et al., 2021;
Weidemann et al., 2022;
Neuroth et al., 2022
Bloom et al. 2020; Cicchino
et al., 2021b; English et al.,2020; Lavoie-Gagne et al.,2021; Schisman et al., 2021;

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Vehicletype

Collisions

EffectSourceShah et al., 2021; Neuroth etal., 2022

es>86%(24% hit-and-run)cb

93-96%

Involved pedestrians (% oftot. crashes)

es

4-17%

Injured pedestrians(% of casualties)

es

1-10%

es

30%

Toofany et al. 2021

es

59%

Toofany et al. 2021

% of tot. fatalities

with pedestrians

tripped over(of non-rider casualties)
Struck(of non-rider casualties)*es: e-scooters, cb: conventional bikes*casualties: persons injured and fatalities

Karpinski et al. 2022a
NTSB, 2022; NHTSA, 2021 &2022
Badia and Jenelius, 2021;
Heydari et al., 2022
APH, 2019; Portland Bureauof Transportation, 2019;
Trivedi et al., 2019;
Weidmann et al., 2022;
PACTS, 2021; Stigson et al.,2021

Crash and injury under-reporting

E-scooter crashes (like bicycle-involved crashes) generally suffer from under-reporting. Two factors
contribute to this:• Differences in the total number of recorded injuries and crashes among different databases.
• Under-reporting of non-injury or mild injury crashes/incidents.
A recent study by the National Traffic Safety Board (NTSB) compared their findings on fatalities reported
in media reports to the recorded fatalities in three databases and found that the records in the databases
always showed fewer fatalities (NTSB, 2022). This suggests that when analysing fatalities and injury data,some records might be missing.
Indirect evidence for crash under-reporting is the fact that most of the scientific literature focuses on
hospital, emergency room, or trauma centre data when assessing the safety impacts of e-scooters. These
records only cover incidents that resulted in injuries requiring immediate medical treatment. On the other
hand, studies that analyse falls and collisions of e-scooterists of all injury severity types are survey-based(e.g., Department for London, 2022). No- or light-injury bicycle crashes face similar under-reporting as well
(De Mol and Lammar, 2006; Shinar et al., 2018). In some US states, the police only record crashes thatinvolve significant injuries or property damage. In certain states (e.g., Oregon), crashes can be selfreported, so it is likely that crash datasets are more representative of the actual situation.
Studies looking to document the magnitude of under-reporting in micromobility crashes and injuries
compare hospital and police crash records. They notably reveal a strikingly low overlap, with only 3 to 12%
of e-scooter patients documented in both hospital and police records (PACTS, 2021; Tian et al., 2022;
Laverdet et al., 2023). Among reported crashes in the USA, data on helmet use was only recorded in 42%
of bicycle-related cases (Tian et al., 2022) and from 40% to 85% of e-scooter-related cases (National
Academies, 2023). Another additional aspect concerns the misreporting of crashes. A crash is recorded,
but the road users involved are misclassified. NTSB (2022) discusses this issue as a US-wide phenomenon.

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Safe infrastructure
The type and quality of the road infrastructure have been found to affect e-scooter collisions (Table 4).
Poor road infrastructure (e.g. where the surface is poorly maintained and has potholes and otherdiscontinuities) has been found responsible for 30-40% of e-scooter crashes. Unpaved versus paved
surfaces have been associated with higher crash risk. Surface quality for cycling infrastructure is equallyimportant, as poor quality has been found to be associated with single road user crashes, particularly for
e-scooters.
Both pavements/sidewalks and higher-speed traffic lanes have been found to be the least safe locations
to ride, while separated bicycle tracks prove to be the safest location and are associated with a lower injury
risk (Table 4). Several studies suggest that e-scooter incidents occur primarily on roadways and secondarily
on pavements/sidewalks (APH, 2019; Bloom et al., 2022; English et al. 2020), while other studies conclude
to the opposite finding (Cicchino et al. 2021). This difference may be linked to the prevalence of riding on
pavements/sidewalks and the presence of bicycle infrastructure. Ma et al. (2021) find that e-scooter travel
conditions are better on the roadway or on cycling infrastructure than on pavements/sidewalks that arecharacterised by more obstacles and vibration-inducing discontinuities. In the US, e-scooterists generally
ride on bike infrastructure when it is present (27-67%), on the road (20-49%) and on the sidewalk (1036%). In Europe, the trend is similar, although the shares are different, with a higher prevalence of bicycle
infrastructure use up to 93%) compared to traffic lanes (11-36%) and pavements/sidewalks (4-24%) (Badia
and Jenelius, 2021).
When it comes to geometry, a narrow lane width can elevate the risks for micromobility users, increasing
the likelihood of collisions (Sabbaghian et al., 2023). Ma et al. (2021) investigated obstacle proximity to escooter riders, emphasising the critical importance of evaluating the surrounding environment of escooters to ensure safety.
Table 4. Risk factors related to infrastructure associated with micromobility safety
Risk factor

Vehicletype

EffectSourcePoor roadinfrastructure(% of tot. crashes)es

30-40%

Badia and Jenelius,
2021; Ma et al. 2021;
DfT, 2022

Paved vs unpaved roades

2.66 greater crash risk

Tian et al., 2022

es

Traffic lane: 23-55% (all)esSidewalk: 17-58% (all)esBike lane: 0.04-25% (all)Badia and Jenelius,
2021; APH, 2019;
Cicchino et al., 2021a;
Cicchino et al., 2021b;
Bloom et al., 2022

es

Intersection: 65% (% of tot. fatalities)

cb

Intersection: 67% (% of tot. fatalities)es

Non-junction: 17% (% of tot. fatalities)cb

Non-junction: 17-27% (% of tot. fatalities)

Road environment

Karpinski et al. 2022b

Karpinski et al. 2022b*es: e-scooters, cb: conventional bikes

Two studies in China and one in Germany have assessed the safety of e-bikes at signalised intersections(Huang et al., 2020; Bai et al., 2013; Petzoldt et al., 2017). According to these studies, the conflict rate of

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e-bikes is higher than that of conventional bikes irrespective of fault. According to Bai et al. most observed
conflicts were caused by the dangerous driving behaviour of car drivers. Liang et al. (2021) observed thaton pavements/sidewalks and bike lanes, the probability of traffic conflicts is highest between e-bikes andpedestrians and lowest between two conventional bicycles.

Safe Riders
This section analyses micromobility crash outcome and crash risk, considering various factors related tousers. Specifically, factors associated with micromobility crashes, injuries and/ or a particular injury levelor type are presented. Crash and injury risk factors associated with bicycles are quite different to those of
e-scooters, namely, nighttime riding, alcohol consumption, and helmet use. There is a broad convergenceacross the international literature on micromobility and e-scooter crash risk factors. These are summarisedin Table 5.
Surrogate safety studies can provide information on road user behaviour and rules compliance, aspects
that have been found associated with crash and injury risk. Nighttime and reduced lighting conditions are
positively correlated with both injury and fatal crashes. Riders under the influence of alcohol are more
likely to be involved in injury collisions (Arbel et al., 2022; Shiffler et al., 2021; Benhamed et al., 2022;
James et al., 2023; Kobayashi et al., 2019; Hennocq et al., 2020). Haworth et al. (2021) observed thefollowing types of illegal riding behaviour among e-scooter riders in Brisbane, Australia: no helmet use(35.6% of all observed users- helmets are required by law in Australia), more than one rider per e-scooter(2%), underage riding (6.7 to 10.3%), and riding on the road (which is illegal in Brisbane). Illegal behaviours
were significantly higher for shared e-scooter users. Hong et al. (2022) observed that 96% of shared escooter riders on the Virginia Tech University campus in the US were helmetless. Low levels of helmet use,
ranging from 0.4% to 10.9% for shared e-scooter riders, has also been observed in several otherinternational studies (Hayworth, et al., 2022). Many e-scooterists also occasionally ride with an additional
passenger (dual riding). According to a Berlin-based survey, 42% of people who have ridden an e-scooter
before said they had at one point ridden with two people onboard (Siebert et al., 2021a). Observational
studies of dual-use riding find that between 2% and 5% of all observed trips involve two riders on a single
e-scooter (Siebert et al., 2021b).
Helmet use, which is very low among injured e-scooter riders, could help reduce head injuries, which arecommon among e-scooter injuries (English et al., 2020; Toofany et al., 2021; Cicchino et al., 2021b; Bloom
et al., 2022). However, several studies conclude that while current bicycle helmet standards (ASTM F144718, 2018; NF EN 1078) are well adapted to evaluate helmets for linear impacts, there is a need to address
oblique impact conditions and the evaluation of head rotation injuries (Bourdet et al., 2021; Fournier etal., 2023; Wei et al., 2023) which are common during e-scooter riders’ falls. Also, considering that a large
proportion of the impacts are to the face (Table 1; Posirisuk et al., 2022; Kim et al., 2022), the use of riskappropriate helmet protection should be incentivised for e-scooter riders.
Mobile phone use while riding an e-scooter (Siebert et al., 2021) and cycling (Huemer et al., 2022) is a
distraction that can impair a rider's focus and reaction time. The act of using a mobile phone while riding
diverts a rider's focus from their immediate surroundings, potentially leading to reduced situationalawareness and an increased likelihood of crashes.

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Table 5. Risk factors related to users associated with micromobility safety
Vehicletype
es
Nighttimeeb(% of fatal crashes)cb
eses
Nighttime & Reduced lighting (% cbof casualties)eb
Risk factor

Nighttime crash risk

Effect
82%
48%
57%
43%
30-44%
14-28%
18%es

4.8 crashes per 100,000 trips
vs 2.2 for daytime crashes
0-7%

cb

16-64%

eb

53%

es

Fatalities: 41%esCasualties: 7-53%

cb

Casualties: 6-13%

es

14-17%: >one riders/ vehiclees24-37% of injured riders were injured
during their 1st rideesHelmet use(% of casualties)

Alcohol

Double riding(% of casualties)

Experience

SourceKarpinski et al., 2022b
Yang et al., 2020
Weidemann et al., 2022;
Kleinertz et al., 2021;
Kleinerzt et al., 2023;
Laverdet et al., 2023
Shah & Cherry, 2022
Harbrecht et al., 2021;
Cicchino et al., 2021b; Grillet al., 2022; English et al.,2020; Bloom et al., 2022;
Stray et al., 2022; Meyer etal., 2022; Laverdet et al.,2023; Clough et al., 2023;
Leyendecker et al., 2023
Karpinski et al. 2022b
Weidemann et al., 2022;
Puzio et al., 2020; Grill etal., 2022; Bekhit et al.,2020; Harbrecht et al.,2021; Kleinerzt et al., 2021;
Neuroth et al., 2022;
Leyendecker et al., 2023
Weidemann et al., 2022
Hennocq et al, 2020
Austin Public Health, 2019;
Cicchino et al., 2021;
Williams et al., 2022; Sexton
et al., 2023

78% of crashes involved riders with low
DfT, 2022
riding rates*es: e-scooters, eb: e-bikes, cb: conventional bikes*casualties: persons injured and fatalities
es

When e-scooterists travel on bicycle infrastructure, their speed has been found to be comparable to, butslightly higher than, that of conventional cyclists (~15.4 km/hour) (Pazzini et al., 2022). During overpassing
manoeuvres, e-scooter speed has been found to increase, especially for close-distance interactions (e.g.,<50 cm); this might affect cyclists’, and other users’ perceived safety. Excessive speeding has been
identified as a significant risk factor contributing to e-scooter injuries, with statistics from the US Centers
for Disease Control and Prevention (CDC, nd) suggesting it plays a role in approximately 30% of such
incidents. Lastly, Almannaa et al. (2021) concluded that the average speed of e-bikes is higher than the
average speed of e-scooters, leading potentially to a higher severity of injury.

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The research on surrogate safety for e-bikes is limited and mainly based on old research without a common
methodological framework. The majority of the studies in the literature and under consideration aim toinvestigate the safety performance of e-bikes, comparing it with the safety performance of conventional
bikes. The travel speed of e-bikes is a significant factor influencing safety performance. Hertach et al.
(2018) conclude that speeding typically occurs before recorded e-bike crashes. Cherry & MacArthur (2019)reviewed eight studies investigating the average operating speed of e-bikes compared to conventional
bikes, finding that e-bikes travel about 3.0 km/h faster than conventional bicycles. A similar margin was
also found in a naturalistic study of German cyclists (Schleinitz, K. et al., 2017). In China, three studies foundthat e-bikes travel speeds were 40–50% faster than conventional bicycles, reflecting the larger share ofthrottled e-bikes able to operate above 25km/hr (Cherry & He, 2010; Lin et al., 2008; Yang et al., 2014).
Similarly, speed-pedelec speeds (able to travel up to 45km/hr) in Germany were found to be 62% higher
than conventional bicycles (Schleinitz, K. et al., 2017). Finally, red light violations are observed to be thesame between e-bikes and conventional bikes (Cherry and MacArthur, 2019).
In several injury-related studies, there is a discussion on the gender of the rider and e-scooter crashoutcomes. E-scooter riders are mostly younger males, as found in various demand-related studies (e.g.,
Laa & Leth, 2020; Christoforou et al., 2021; Department for London, 2022). With driving and cycling,
younger males are associated with higher incidences of risky behaviour, crash rates and severe crashoutcomes (Prati et al., 2019). However, evidence to-date indicates that male and female e-scooterists havebeen found to have the same injury and crash probabilities (Harbrecht et al., 2010; Cicchino, Kulie, andMcCarthy, 2021).
Similarly, seasonality of e-scooter injuries and fatalities has not been found to be a significant risk factor.
The higher number of collisions during the spring and mostly summer months is due to the increase inridership. This trend is similar to bicycle crashes (NHTSA, 2021; NHTSA, 2022) and is explained by increased
seasonal riding (Fournier et al., 2017).
Evidence suggests that experience operating micromobility vehicles improves safety performance. Thishas been found to be the case with cycling – for example, Branion-Calles et al. (2020) found that crash
rates decreased with increased rider cycling frequency in seven European cities. For the case of e-scooters,
two types of inexperience should be considered: users who have not completed many rides and users who
are not familiar with the local context. The latter is particularly relevant to shared e-scooter use, as in many
cities, it has been found that shared e-scooters are used by a considerable number of non-residents or
tourists (Laa & Leth, 2020; Christoforou et al., 2021; Austin Public Health, 2019). A study in Austin, Texas,
found that 33% of the injured e-scooterists were not Austin residents, and 21% were not even Texas
residents (Austin Public Health, 2019). Collisions are predominantly linked to infrequent riders, with 78%
of crashes involving this group, while first-time renters face a threefold higher risk compared toexperienced users who have rented e-scooters over 20 times, emphasizing the importance of safety fornewcomers (DfT, 2022).
There is some research on user frequency between privately-owned and shared e-scooter riders. A study
in Belgium surveyed e-scooterists six months after the introduction of shared e-scooters and found thatshared e-scooter riders rode less frequently than riders using their own e-scooter (Lefrancq, 2019). In a
six-month period, 46% of shared e-scooter riders had ridden less than 10 times, and only 16% of them had
ridden more than 50 times. Twenty-nine per cent (29%) of e-scooter owners had ridden up to 10 times,
while most of them (41%) had ridden more than 50 times. Similar are the findings from the survey of Laa
and Leth (2020) in Vienna. Therefore, it can be assumed that e-scooter owners are more frequent riders
and, so, have acquired better riding skills.

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KEY MICROMOBILITY SAFETY TRENDS

Brownson et al. (2019) note that most of the hospital admissions (93%) for e-scooter-related injuries in
Aukland, New Zealand, involved shared e-scooter riders, while only 1% of the patients were e-scooter
owners. Additionally, an Australian study by Haworth et al. (2021) observed e-scooters in Australia in
February 2019, revealing that illegal and risky driving behaviour, such as not wearing a helmet, riding on
the road, or double riding, were more prevalent among shared e-scooter riders compared to owners(49.6% for shared e-scooters vs. 12.2% for privately-owned e-scooters).

Safe vehicles
In ever-evolving urban landscapes, powered micromobility solutions like e-scooters and e-bikes have
reshaped urban transportation. However, their rapid uptake has brought forth an array of safety concerns
linked to vehicle design. E-scooters and e-bikes – as well as conventional bikes -- differ greatly in theirdesign, stability, and speed (Arbel et al., 2022). This chapter extends the discussion, delving into various
vehicle design elements and their broader implications for enhancing micromobility safety, such as thevehicle’s maximum design speed, wheels’ size, brake mechanism, lights and bells.
A key distinction between e-scooters and bicycles lies in the rider's position. Unlike bicycles, e-scooter
users stand on the vehicle while riding and can fall freely from the vehicle, absorbing the full impact of thefall (Arbel et al., 2022). The standing posture on e-scooters has been identified as risky, particularly during
braking to manoeuvre around or away from obstacles. Conversely, the seated posture offers improved
braking and handling performance for both seated e-scooters and bicycles.
The maximum design speed of powered micromobility vehicles remains a pivotal determinant of safety.
The European Committee for Standardisation has issued EN 17128: 2020, which establishes design
standards for personal light electric vehicles (PLEV), including e-scooters. The standard mandate restricts
the maximum speed of e-scooters to 25km/h or less and does not apply to powered light vehicles having
a maximum design speed above 25 km/h. Though there are no universal guidelines for its application, most
European countries adhere to EN 17128: 2020.
Several studies highlight that the reduction of e-scooter riding speed can lead to a significant reduction in
the mean head-ground impact speed (Posirisuk et al., 2022; Fournier et al., 2023). A study investigating
differences in vehicle kinematics among standing and sitting e-scooters and 26-inch wheel bicycles,
concluded that seated e-scooter stability begins at a relatively higher riding speed, becoming stable when
speed exceeds 20 km/h, while certain standing posture designs, though stable in lower riding speeds, still
fall short of the stability achieved by the reference 26 inch-wheel bicycle (Paudel and Yap et al., 2021).
Enhancing the current e-scooter design could address stability challenges faced by riders during low
speeds, simultaneously improving rider and overall safety.
Standing e-scooters feature a central column with handlebars to ensure stability and facilitate steering,
complemented by a foot platform for the standing rider (SAE International, 2019). As with bicycles,changing the fork-steerer column angle (e.g. fork offset) impacts front wheel handling characteristics andshifts the rider/vehicle centre of mass – in some instances, bringing it nearer to the self-stability range ofa larger-wheeled bicycle. Likewise, shifting the angle of the steering column with respect to theheadtube/fork angle also has an incidence of the centre of gravity and steering performance.
Paudel (2019) and Paudel and Yap (2021) have highlighted that the vertical location of the centre of massfor bicycle riders and standing e-scooterists is comparable, though slightly higher for the latter for thesame rider. The horizontal position of the centre of mass for e-scooters with a rider is more forward thanfor bicycles or seated e-scooters (Paudel, 2019). Compared to bicycles, the slightly higher and more

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forward-facing centre of mass has an incidence on forward obstacle crashes for e-scooters. In these
instances, e-scooter riders exerting weight on the steering bar and column can induce a fulcrum effect,
potentially leading to over-the-handlebar vaulting (Arbel et al., 2022; Como et al., 2022; Chontos et al.,2023; Matt et al. 2022; Fournier et al., 2023; Paudel, 2019; Paudel and Yap, 2021; Serra et al., 2021; Weiet al., 2023). Dynamically or statically shifting the centre of mass backwards and downwards improves theself-stability range of e-scooters, especially at lower velocities, just as shifting it forward degrades stability(PACTS, 2021; Paudel, 2019; Paudel and Yap et al., 2021). Many recent-generation shared scootersaccordingly place weight lower and to the rear of the e-scooter, thus, alongside the adoption of larger
front wheels (see below), improving stability (National Academies, 2023). These considerations underscorethe significance of understanding the dynamic interplay between design features and rider behaviour inshaping the safety outcomes of e-scooter operation.
Wei et al. (2023) find that head-ground impact velocities during e-scooter falls align with those observedin bicycle falls, though the difference in injury characteristics discussed earlier suggests dissimilar headground impact configurations, as noted by Matt et al. (2022). Fournier et al. (2023) note that critical factors
influencing the risks of head injury from e-scooter crashes include the initial speed of the device, its
inclination with respect to obstacles, and the size and weight of the rider.
The width of the foot platform determines the stability of the e-scooter rider (Masquelet et al., 2023).
Shichman et al. (2023) observe that the prevalent narrow-based design of e-scooters is more hazardous
than a wider foot platform, with orthopaedic fracture rates significantly higher in the more commonly used"foot-behind-foot" riding position compared to a ”side-by-side“ position.
The size of wheels and tyres in micromobility vehicles has a substantial impact on safety, with larger wheels
emerging as a salient safety feature, preventing deflection, improving obstacle clearing and providing
gyroscopic stability. Bicycles have larger wheels (16” to 29”) that generate stabilising gyroscopic forces andgenerally employ shock-absorbing tubed or tubeless tyre designs. E-scooters have much smaller wheels(6” to 12”) and more solid and less forgiving tyres (García-Vallejo et al., 2020; PACTS, 2021). Bicycle wheels
have a shallower angle of attack than smaller e-scooter wheels and are thus more stable when
encountering obstacles of the same height (Paudel, 2019). E-scooters with smaller wheels have been
linked to a higher likelihood of falls, elevating the risk of head injuries for riders. A noteworthy finding
underscores that increasing e-scooter wheel size decreases the likelihood of falls caused by potholes, witha critical pothole depth range estimated to be between 3 and 6 cm for 10-inch wheel e-scooters (Posirisuk
et al., 2022). Therefore, larger wheels offer more stability and safety.
Moreover, the choice of wheel type is a crucial consideration, with air-chambered wheels being found toconfer more stability than solid rubber or honeycomb ones (Leoni et al., 2022). These air-chambered
wheels can absorb vibrations and shocks better, thereby enhancing overall ride comfort and safety. Manye-scooters – especially those designed for shared use – compensate for the relative lack of passive shock
absorption with active front-fork suspension systems.
Braking systems represent a critical aspect of micromobility vehicle design, and their diversity warrants
attention. The types of braking systems for e-scooters and e-bikes vary widely depending on the specificmodel and manufacturer. Nonetheless, there are some common types used internationally. Notably, moste-scooters are equipped with two independent braking systems (in some cases, this is a legal requirement).
Some models feature two-hand lever brakes, while others incorporate a foot-brake in addition to a single
left-hand brake (Siebert et al., 2021). This diversity highlights the need for establishing a universal mental
model for lever-to-brake coupling, mitigating potential confusion surrounding lever and front/back-wheelbrake coupling.

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KEY MICROMOBILITY SAFETY TRENDS

Dozza et al. (2022A) investigated the distinct braking and manoeuvrability characteristics of e-scooters andbikes, concluding that e-scooters typically require a longer braking distance compared to bikes. Recent
research by Li et al. (2023) emphasises that braking performance, measured in terms of deceleration andjerk, exhibits variations across different vehicle types. Notably, e-scooters show lesser efficacy in braking
compared to bicycles. For standing e-scooters, the maximum allowable deceleration to prevent flipping
over is approximately 5 m/s², significantly lower than for seated e-scooters (6.7 m/s²) or bicycles (7.5 m/s²)(Paudel and Yap, 2021). These findings are crucial in comprehending the dynamics of road interactions, as
it implies that e-scooters have a lower probability of safely stopping in emergency situations compared tobicycles. However, e-scooters exhibit superior performance in steering manoeuvres, attributed to theirshorter wheelbase and the absence of a pedalling requirement (Paudel and Yap, 2021). Li et al. (2023)
conclude that steering could be a more efficient collision-avoidance strategy for e-scooters than braking
in a front collision scenario.
E-scooters and bicycles also display different acceleration profiles. Throttled acceleration as found on moste-scooter models, is more rapid and responsive than pedal-powered acceleration, even in cases where it
is motor-assisted. In most cases of the latter, pedal torque-input linked acceleration is smoother and lesssudden than torqueless motor engagement.
Ensuring visibility and audibility on the road is paramount for the safety of both micromobility riders andpedestrians. Bikes often come equipped with front and rear lights, offering visibility in various lighting
conditions, while pedal and wheel reflectors offer extra visibility. In contrast, e-scooters often feature justa single headlight, and due to their small wheel size, side reflectors show small movement. Without turn
indicators on most e-scooters, riders risk instability when resorting to hand signals, unlike bike riders who
maintain stability during such manoeuvres due to the gyroscopic effect of the larger wheels. This
discrepancy underscores the importance of a well-lit path for safe e-scooter operation and accentuates
the need for robust lighting standards across micromobility vehicles. Furthermore, both e-bikes and escooters should incorporate auditory signalling devices, such as bells, to alert other road users to theirpresence, enhancing overall road safety.
In addition to the above design features, it is essential to consider the impact of combined vehicle-rider
weight on micromobility safety. Considering the standing riding position of the e-scooter rider and the factthat the overall average weight of the scooter (15-30 kg for private and up to 55 kg for rental (PACTS, 2021)
is less than the average weight of the rider, the position of the rider drastically impacts the centre of gravityof the vehicle (Garman et al., 2020). Leoni et al. (2022) suggest that, when riding on the same surface witha similar road profile, a vehicle's weight plays a critical role in dampening vibrations and enhancing stability.
E-scooters with the same wheel size but greater weight are found to be more stable. Also, a heavier escooter (31.5 kg) demonstrates superior braking performance when compared to its lighter counterpart(11.3 kg) (Li et al., 2023). This underscores the significance of engineering considerations that balance
weight and performance to ensure a safe and comfortable riding experience.
The collective findings imply that a holistic consideration of multiple factors, including rider size, vehicle
dynamics, and environmental conditions, is crucial for understanding and mitigating head injury risks inmicromobility.
Finally, it should be noted that standing e-scooters usually pose physical accessibility challenges for thosewith mobility-related disabilities as compared to seated e-scooters, bicycles and tricycles, but for somepeople, they may be more easily accessible. Ongoing debates surround the regulatory classification ofseated e-scooters, with additional intricacies arising when considering distinctions between fixed andremovable seats (National Academies, 2023).

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Figure 3. Various e-scooter and bicycle characteristics and safety
E-scooters

BicyclesHead height

Head height

Lower head height means less freefall distance and lower acceleration to
the ground in a crashHigher head height and distance to theground due to standing position increases
head acceleration in crashes

Cent re of gravit yCent re of gravit y

Higher and more forward centre of gravity reduces
stability and makes the rider more prone to vaulting
over the handlebar in forward crashes.

Lower and less forward centre of gravity
contributes to more stability, better
emergency braking and less risk of vaulting
over the handlebar in crashes

Braking
Single front braking reduces stability andcontributes to loss of rear wheel groundcontact in emergency braking

BrakingStandard dual mechanical or hydraulicbrakes and a low centre of gravity provide
improved emergency braking

St eering colum n
Steering column serves as a fulcrum, increasing
the risk of the rider vaulting over the handlebar inforward crashes if the rider places weight on it

St eering column
Steering column near centre of gravity, highframe attachment point and large wheel
size reduce handlebar vaulting risk

Wheel size
Smaller wheel sizes are more agile but more
prone to deflection and stoppage by obstacles.
Less gyroscopic stability

Wheel size
Larger wheels prevent deflection, improve
obstacle clearing and provide gyroscopic
stability, but are less agile

Accelerat ion
Throttle-initiated acceleration
can be more sudden

Plat form
A narrow or insufficiently large platform
reduces rider stability

Accelerat ion
Newer shared e-scooter models
address these design issues withlarger wheels, wider tyres, lower andmore anterior frame/battery weight
distribution, dual front and backbraking and wider foot platforms.

E-bikes are generally heavier andoperated at higher speeds than
traditional bikes, increasing kinetic
energy in self-crashes and crashes
with pedestrians and other users.

Pedalling-initiated acceleration can be lesssuddenIn conclusion, this chapter underscores the paramount importance of safety in micromobility and extends
the discussion to encompass the broader implications of vehicle design features. Compliance withestablished standards, the incorporation of larger (front) wheels and both active and passive suspension
and wider e-scooter foot platforms, optimisation of braking systems, and the implementation of effective
lighting and auditory signalling mechanisms all play crucial roles in enhancing the safety of e-scooters ande-bikes. These measures are vital for fostering the responsible growth of micromobility in urban
environments, ensuring that these modes of transportation contribute positively to modern urban mobility
while minimising risks to riders and all road users alike.

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SUMMARY OF KEY MICROMOBILITY RISK FACTORS

Summary of Key Micromobility Risk Factors
This section provides a comprehensive synthesis of the key risk factors associated with micromobility,
shedding light on the multifaceted challenges that must be addressed to ensure the safe integration of
micromobility options into urban landscapes. A systematic analysis of key factors, behaviours, andregulatory considerations provides a holistic understanding of the safety landscape, paving the way for
effective recommendations and informed decision-making.
Speeding (Fu1) emerges as a significant concern, as excessive travel speed of both micromobility modes
and other vehicles (in particular trucks, vans and cars) has been identified as a key risk factor for e-scooter
and e-bike injuries. Riders who exceed safe speed limits are more susceptible to crashes, making it crucial
to address this issue for reasons of fairness, particularly in privately-owned micromobility devices (but also
in all vehicles) lacking geofencing technology present in shared counterparts. Managing speeds of othervehicles is essential for reducing micromobilty crash risk. The use of helmets (Fu2) and, in particular – theuse of appropriate helmets for e-scooter riders is another critical factor. Additionally, the influence ofalcohol and drugs (Fu3), mainly among e-scooter riders, is a significant concern, as riders under the
influence are more likely to be involved in injury collisions and are more likely to suffer serious injuries.
Visibility (Fu4) also emerges as an essential safety factor, with nighttime and reduced lighting conditions
being positively correlated with both injury and fatal crashes. Low rider experience (Fu6) is a recurrent
factor in e-scooter collisions, contributing to most crashes, with falls being a prevalent consequence.
Furthermore, mobile phone use (Fu7) while riding is a distraction that can impair a rider's focus andreaction time. Rider stability (Fu8) is a key contributory factor to crashes and falls and is linked toparameters such as the rider's position, vehicle dimensions and riding experience.
Poorly maintained roads and unpaved surfaces (Fi1) are linked to a heightened crash risk. Particularly
concerning is that these infrastructure-related issues often result in falls, further emphasizing the need forinfrastructure improvements to bolster rider safety. The riding location (Fi2) can also influence crashprobability, with intersections and sidewalks the least safe locations due to high conflict rates, indicating
the necessity for urban planning and regulations that address the integration of e-scooters into pedestriandense areas. Lastly, the risk for other road users is heightened by e-scooters being parked inappropriately(Fi3).
Larger wheels (Fv1) contribute to stability and vehicle control, as does centring weight lower and further
back. Optimized braking systems (Fv2) enhance a rider's ability to slow down or stop safely. Setting
appropriate maximum speeds (Fv3) for e-scooters and e-bikes helps prevent excessive travel speed, asignificant risk factor for e-scooters, e-bikes and pedestrian injuries. Shared micromobility incorporates
geofencing technology, capping shared e-scooters and e-bike speeds to a defined maximum threshold(20/25 km/h in the EU) in designated “low-speed zones”. The existence of effective lighting and auditory
signalling mechanisms (Fv4) ensures visibility and communication with other road users, reducing the riskof crashes in low-light conditions or situations where awareness is critical. Finally, optimizing the width ofthe e-scooter's foot platform (Fv5) can greatly enhance safe riding by providing improved stability.

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Additionally, the availability of micromobility safety data (Fm1) and exposure data (kilometre or time
travelled)is crucial for informed decision-making and effective policymaking. Consistently gathering andanalysing data on micromobility crashes, injuries, and near-miss incidents can provide valuable insights
into the root causes and patterns of these events and address the under-reporting. Promoting post-care(Fm2) for micromobility riders can offer a safety net in case of crashes.
In summary, a holistic approach that combines safe riding behaviour, improved infrastructure, vehicle
design standards, and safety data collection is essential to mitigate the crash risks associated withmicromobility in our urban environments.
The table below outlines these main risk factors primarily associated with e-scooter riding and to someextent, with e-bikes as well. It also underscores the correlation between these risk factors and road users,
infrastructure, and micromobility vehicles.
Table 6. Key micromobility risk factors.
Code

Risk Factors

Safe Users

Safe Infrastructure

Safe Vehicles

Fu1
Fu2
Fu3

Speeding
Helmet use
Under the influence

●
●
●

●
●
●

●
●
●

Fu4

Visibility

●

●

●

Fu5
Fu6

Double riding
User experience/ Riders age

●
●

●
●

●
●

Fu7

Mobile phone use

●

●

●

Fu8

Rider’s stability

●

●

●

Fi1
Fi2
Fi3

Poor road infrastructure
Riding location
Parking

●
●
●

●
●
●

●
●
●

Fv1

Wheel size

●

●

●

Fv2

Maximum design speed

●

●

●

Fv3

Braking system

●

●

●

Fv4
Fv5

Lights and auditory
E-scooter foot platform

●
●

●
●

●
●

Fm1
Fm2

Micromobility safety data availability
Post - care

●

●

●

●

●

●

●high correlation, ●medium correlation, ●low correlation

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RECOMMENDATIONS

Recommendations
Safety Recommendations for Authorities
Safe Infrastructure

Establish micromobility parking policy and designate parking areas where needed
Authorities should formulate consistent micromobility parking guidelines that enhance its use. This
includes establishing clearly delineated parking zones for e-scooters and bicycles in high-traffic areas.
These should be placed at the curb or, where legal and where it does not impede pedestrian activity, inpedestrian or shared zones. Their implementation requires uniform and systematic enforcement. It also
involves careful planning and traditional and digital signage to guide riders to these designated zones. This
ensures that parked micromobility vehicles do not impede pedestrians, contributing to safer urban
environments. Authorities should simultaneously enforce motor vehicle parking policy to ensure
micromobility infrastructure and parking zones are not encumbered by illegally parked cars, vans andtrucks. Shared micromobility parking should allow sufficient access for operators’ support cargo bikes andvans. Safe Infrastructure
Proactively maintain micromobility infrastructure
Authorities should implement proactive and regular maintenance for micromobility infrastructure, sharedpaths and road surfaces, with priority in high micromobility traffic areas. Proactive maintenance ensuresthat infrastructure elements like bike tracks, sidewalks and roads remain in good condition. This minimises
the risk of crashes caused by potholes, debris or poorly maintained surfaces. Prompt reporting of
infrastructure issues by road users and near-crash hot spots by micromobility operators contributes toefficient, proactive maintenance. Implementing this measure could reduce falls, a major contributor to escooter and (e-)bike-related injuries, and facilitate a smoother learning curve for inexperienced e-scooter
riders.
Establish a dedicated and well-connected micromobility network
Authorities should develop a comprehensive urban plan incorporating mixed and protected micromobility
infrastructure, ensuring connectivity with existing transportation networks. Specific focus should be given
to junction treatments to ensure increased visibility and awareness for car and truck traffic. Seamlessconnections with public transport, sidewalks and shared mobility services should be encouraged to create
a well-connected micromobility network. The effective implementation of this recommendation can
reduce collisions of micromobility vehicles with motor vehicles (especially in junctions) and pedestrians on
sidewalks.
Safe Riders

Implement a 30km/h (or lower) speed limit in areas with high micromobility use

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RECOMMENDATIONS

Authorities should default to a 30 km/h (or 20 km/h) speed limit for car and truck traffic in areas with highmicromobility traffic. Lowering the speed limit to 30 km/h or lower provides a crucial safety buffer,
allowing motorists to react more effectively to unexpected situations and reducing the severity of potential
micromobility vehicle-motor vehicle collisions.
Establish low-speed limits for micromobility vehicles in pedestrian or shared zones
In areas where micromobility riders legally can or must share pedestrian spaces, authorities should default
to establishing a safe (~6-10 km/h) speed limit for micromobility modes to enhance pedestrian safety.
Implementation involves clear signage, providing access to geospatially-referenced speed control zones.
It also involves educating road users on speed limitation rules and enforcement to reduce the risk ofcrashes and conflicts. This ensures a safe co-existence between micromobility riders and pedestrians.
Take enforcement action against risky micromobility riding
Authorities should impose penalties for illegal micromobility riding, including:• speeding for micromobility vehicles in speed-restricted zones,• riding under the influence of drugs and alcohol,• riding under the age limit,• riding with two or more people,• riding on sidewalks when it is forbidden,• riding outside designated infrastructure where its use is obligatory,• illegal parking.
Authorities should define a common limit for alcohol and drug levels and establish minimum age
requirements for micromobility.
Promote the use of appropriate helmets
Authorities should encourage helmet use for private and shared micromobility in a way that does notdiscourage using active micromobility, which would diminish overall health benefits. Further research isneeded regarding closed-face helmets or equivalent protection to protect against maxillofacial injuriescommon in e-scooter crashes. Authorities should require adapted helmets for riders of high-speed escooters and e-bikes (e.g. with a maximum speed between 25 km/h and 45 km/h and above).
Introduce rider education in secondary schools
Micromobility training should be integrated into the curriculum of secondary schools. Introducing
micromobility training at this level equips students with the knowledge and skills necessary for safe andsustainable urban mobility. Implementation should involve developing age-appropriate micromobility
training modules, training qualified instructors, and integrating these lessons into the school curriculum toensure students are well-prepared for micromobility usage.
Safe Vehicles

Set universal technical requirements for e-scooter design••

Establishing and joining technical standards for e-scooters is essential. E-scooter standards should
account for the following:
maximum speed (e.g. <20/25 km/h. Vehicles operating at higher speeds would be regulateddifferently and more stringently)

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RECOMMENDATIONS

•
•
•
•
•
•
•
•

maximum power (e.g. <250-500 W. Vehicles with higher power should be regulated differently
and more stringently)
minimum wheel size (the larger, the better)foot platform area (e.g. at least 150 cm2)
dual, separate and hand-initiated braking systems
independent front and rear lights
indicator lights (due to the difficulties of using hand signals)
reflective markings
phone attachment feature.

Further investigation into the impact of weight on e-scooter safety is needed due to the limited current
data and potential implications on collision energy.
Adopt riding support systems in micromobility vehicles
Authorities should foster the adoption of riding support systems in micromobility vehicles, including
automatic emergency braking assistance, audible warning devices providing alerts when speeding,detection technology capable of assessing factors like unsteady movement, occupancy detection sensors
and alerts when inappropriately parking.
Safe management

Establish and collect data on distinct micromobility categories in safety statistics
Creating distinct categories for each micromobility mode (i.e., conventional bikes, e-bikes, e-scooters,
speed e-scooters/e-bikes, monowheels/e-unicycles) in road traffic casualty records, including police
records and medical records, improves safety assessment. Micromobility-related incidents are oftengrouped under broad categories, making it challenging to track and understand the specific risks andinjuries associated with these modes. Additionally, collecting exposure data for each category is essential
to calculate casualty risk accurately.

Safety Recommendations for Operators
Safe Infrastructure

Establish collaborative partnerships with authorities for infrastructure condition reporting
Micromobility operators collect valuable data on potholes, falls, and near-crashes through in-vehicle
sensors. They should use this information to help authorities proactively maintain urban infrastructure byidentifying and reporting areas with subpar road conditions. This effort, fuelled by data-driven insights,
contributes to maintaining and improving micromobility infrastructure, ultimately enhancing overall safety
for riders and pedestrians. Additionally, operators should initiate programs to evaluate the effectivenessand costs of this reporting.
Integrate parking zones in shared micromobility apps and deploy smart docking in high-traffic areas
Shared micromobility apps should onboard designated parking areas and restrictions. Deploying smart
docking and charging stations in high pedestrian or vehicular traffic zones can reduce obstruction on
sidewalks. This ensures convenient access to charged shared micromobility vehicles. Such hubs could also
minimise the use of vans or other vehicles for re-positioning, swapping batteries or otherwise re-charging
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shared micromobility fleets, which may impose additional risks on all road users. Also, operators canreinforce responsible parking, e.g. by offering rewards for users who comply with parking requirements orin docks if these are available.
Safe Riders

Provide safety feedback via telematics data
Operators can use telematics data on speeding, acceleration/deceleration or distracted riding to provide
riders with post-trip feedback. This feedback gives riders insights into their habits and opportunities for
operators or insurers to incentivise safe behaviour. Real-time safety alerts to riders could also be
considered where these do not contribute to rider distraction. These alerts detect risky riding behavioursand notify riders of speed limits, especially in high-risk areas like sidewalks and junctions. Operators should
explore how real-time safety alerts impact micromobility safety.
Provide economic incentives for safe riding
Shared micromobility operators may encourage helmet use with economic incentives such as providing
free helmets or discounts to encourage safety-conscious ridership. They can also discourage inappropriate
parking and alcohol- or drug-impaired riding with incentives or automatic vehicle locking, pending a better
understanding of the necessary costs and potential public and private funding schemes.
Implement mandatory initial rider training
To enhance rider safety, shared micromobility operators can require new riders to pass through in-app
safe riding screens for the first few rides they make to help ensure that riders are familiar with local rules
and guidelines before embarking on their e-scooter trips.
Verify age to start riding
Operators should implement age verification procedures to ensure riders meet the minimum age
requirements defined in each city, ensuring compliance with local regulations and safety standards.
Safe Vehicles

Ensure systematic maintenance of micromobility fleets
Operators should maintain their fleets in good repair and follow state-of-the-art maintenance protocols,emphasising regular checks and upkeep of essential components, including brakes, lights and batteries.
This approach ensures the vehicles’ continued safety and optimal performance, enhancing the
micromobility service’s overall reliability.
Enable context-dependent maximum speed control using geofencing
Shared micromobility operators can employ geofencing technology to smoothly and dynamically lower
maximum speeds to designated speed limits in high-risk zones, such as pedestrian areas or during risky
hours like nighttime, prioritising safety for all road users.

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Restrict e-scooter access if tandem riding and/or alcohol use is detected
Shared micromobility operators should be encouraged to incorporate in-vehicle sensors to detect tandem
riding and introduce in-app tests to identify users under the influence of alcohol and drugs. If violations
are detected, e-scooter access can be disabled, ensuring responsible and sober usage.
Implement riding support systems in shared e-scooters
Operators should be encouraged to implement safe riding support systems in e-scooters, including
automatic emergency braking assistance and detection technology capable of assessing factors likeunsteady movement, tandem riding and inappropriate parking.
Safe management

Enable in-vehicle or in-app crash detection technology
Shared micromobility operators can enhance the safety and user experience of their services and address
the low availability of micromobility crash data by integrating crash detection technology into their vehicles
or mobile applications. In cases where the technology detects a potential crash and the user does not
respond within a specified timeframe, the app can automatically notify emergency services (e-call).
Micromobility operators can establish partnerships with local emergency services, medical facilities orroadside assistance providers to ensure a swift response to detected crashes and improve theeffectiveness of this app feature. However, it is crucial to conduct research and pilots to prevent theoverexposure of false calls to emergency services.

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Conclusion
This report examines and synthesises the most recent and key micromobility safety trends and risks andformulates safety recommendations for both authorities and micromobility operators regarding bothprivately owned and shared micromobility vehicles, with a particular emphasis on e-scooters and ebicycles (e-bikes). The analysis and formulation of safety recommendations are guided by the principles of
the Safe System Approach, with the primary goal of enhancing safety standards and proactively addressing
the inherent risks associated with the entire micromobility ecosystem. This comprehensive approachencompasses all facets, including riders, infrastructure, and vehicle design, ensuring a holistic and effective
strategy to mitigate safety challenges.
The uptake of micromobility vehicles, including e-scooters and e-bikes in many cities, has ushered insignificant changes in urban transportation, presenting new and pressing challenges for policymakers andstakeholders. This transformation coincides with a growing public concern surrounding an increase in
micromobility-related crashes. Crashes involving e-scooters and e-bikes are increasing, though so is theiruse. Injuries from these crashes are also increasing and are sometimes serious or fatal. E-scooter, and insome instances, e-bike crashes and injuries are different from those involving conventional bicycles,
suggesting the need for targeted safety measures. Nonetheless, a relatively small percentage of
micromobility collisions results in severe injuries or fatalities. Where good quality data on both crashes
and exposure exist, e-scooter crash risk has diminished as e-scooter travel volumes outpace the growth of
injuries requiring medical attention. This is especially the case for shared e-scooters, whose speeds arecapped at 20-25 km/h. Generally, however, comprehensive and comparable data across both shared andprivately owned e-scooters (including those that can travel up to 45 km/h) is not largely available. Privateand shared micromobility safety analysis would highly benefit from the existence of more consistent andavailable exposure and safety data to ensure more reliable risk estimations for injuries and crashes –especially for e-scooters and e-bikes.
This report underscores the multifaceted nature of micromobility and, particularly, e-scooter safety. Escooter-related incidents predominantly involve single road users, resulting in falls and collisions withstationary objects. Pedestrians are injured through collisions with either moving or stationary e-scooters.
The gravest danger emerges from conflicts between micromobility vehicles and larger motor vehicles,
often leading to fatalities. All of these factors contribute to depressing potential demand for travel by escooter or other forms of micromobility, even though a relatively small percentage of micromobility crashinjuries are severe and require hospitalisation. Nighttime riding, drug or alcohol-impaired riding, riding in
traffic lanes or on sidewalks and encountering poorly maintained road surfaces all contribute to elevatedcrash and injury risk. Helmet use is low among injured e-scooterists, and this contributes to the frequency,
severity and type of reported injuries. Vehicle design plays an important role in crash occurrence andseverity, with e-scooters displaying different and less stable characteristics than bicycles. Shared e-scooter
designs have evolved rapidly to incorporate safety-improving features and make these available to riders.
When it comes to e-bikes, much of the safety data concerns Europe, where multiple studies conclude that
there are no significant differences in the overall safety of e-bikes compared to that of conventional bikes,

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CONCLUSION

though the increased speed at which they are operated has been seen to be a factor in the types of injuries
that have resulted from crashes.
In the case of e-scooter safety, surrogate safety-based analyses have proven very useful as they shed lighton user behaviour and provide kinematics data on unsafe behaviours (e.g., helmet use). Surrogate safety
studies have the potential to provide additional datasets to assess micromobility safety. Reviewed studies
on both micromobility modes provided insightful information on unsafe behaviours, while they also havethe potential to provide exposure-related information. Due to advances in technology, surrogate safety
methodologies and analyses are expected to further grow.
The type and mechanism of micromobility collisions, in addition to the identified risk factors, suggest thatmany crashes and injuries are preventable if appropriate actions are taken by authorities andmicromobility operators. In this context, this report outlines specific safety recommendations for both
micromobility operators and local authorities, which are classified into four pivotal domains: safe
infrastructure, safe riders, safe micromobility vehicles, and safe management.
Authorities bear a crucial responsibility in fostering the safety of micromobility users and integrating
micromobility seamlessly into urban transportation systems. By prioritising safe infrastructure, authorities
can enhance micromobility safety by implementing proactive maintenance, creating dedicated, safe andconnected micromobility networks, and establishing designated parking areas for micromobility vehicles.
These measures not only reduce infrastructure-related risks but also promote safer coexistence between
micromobility users and pedestrians. Traffic rules enforcement, including lower speed limits for motorised
traffic and for micromobility modes on pavements/sidewalks (where allowed), enhances safety. Helmet
use promotion and rider education in secondary schools contribute to safer riding. Furthermore, setting
universal technical requirements for e-scooter design and promoting the adoption of riding support
systems in micromobility vehicles can significantly reduce risks. Creating a distinct micromobility category
in road traffic casualty records improves data collection and accountability. In collaboration withmicromobility operators, authorities play a pivotal role in creating safer and more sustainable urban
environments.
Micromobility operators play a significant role in ensuring the safety of micromobility users and enhancing
the overall urban mobility experience. By embracing a proactive approach, operators can actively
contribute to micromobility safety through measures such as infrastructure condition reporting,promoting the use of parking corrals, deploying smart docking and charging stations, and offline safety
feedback via telematics. These strategies not only promote safer riding practices but also enhance userconvenience. Moreover, by offering economic incentives for safe riding, mandating rider training, andemploying geofencing technology, operators can substantially mitigate risks associated with micromobility
usage. The adoption of riding support systems in shared micromobility vehicles further bolsters safety
efforts. Lastly, by integrating crash detection technology into their applications, operators can swiftly
respond to incidents, ensuring timely assistance when needed. Micromobility operators are key partners
in shaping a safer, more efficient urban mobility landscape.
While the literature on e-bikes is relatively sparse and does not fully reflect current levels of e-bike usage,
much of what improves the safety of e-scooters and conventional bikes will also improve the safety of ebikes as well (e.g., the presence of bike lanes, the presence of lighting, speed control software, etc.).
Effective application of these recommendations for safer micromobility must always be contextdependent and address local needs and desires. With a concerted effort from all stakeholders,micromobility safety can be improved.

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REFERENCES

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