Electric scooter injuries: Incidence and injury patterns at a level I trauma center.

PURPOSE: Electric scooters (e-scooters) have become an increasingly popular mode of public transportation in recent years. As the incidence of related injuries rises, it is important to understand specific fracture patterns unique to e-scooters and electric bikes (e-bikes) to help guide management. The purpose of this study was to review the prevalence and describe specific fracture patterns of e-scooter and e-bike related injuries at the busiest level 1 trauma center in the borough of Manhattan. METHODS: Chart review to determine mechanism of injury was performed on all patients for whom an orthopedic consult was requested from 1/1/2021 to 12/31/2021. All patients whose injuries were sustained due to an e-scooter or e-bike were further reviewed for demographics, injury characteristics including fracture pattern, and definitive injury management. Any patients who had an orthopedic consult placed for a reason other than an acute injury were excluded. Descriptive statistics are reported as frequency (percentage) for categorical variables and means for continuous variables. RESULTS: Of the 1815 orthopedic consults requested, 1357 (74.8%) were for acute injury management. Of those with acute injuries, 119 (8.8%) sustained 136 e-scooter or e-bike related injuries. There were 92 (77.3%) males at an average age of (33.8 ± 15.7) years. Approximately one-fifth of all patients presented in June 2021 (26, 21.8%). There was a 9.2% rate of open fractures. The 136 injuries were evenly split between the upper and lower extremities, with 57 (47.9%) upper extremity, 57 (47.9%) lower extremity injuries, and 5 (4.2%) concomitant upper and lower extremity injuries. The most common fracture patterns were ankle fractures (16, 11.7%), followed by tibial shaft (14, 10.2%), tibial plateau (13, 9.5%), and radial head fractures (11, 8.0%). There was a 33.3% incidence of associated posterior malleolar fractures in the spiral tibial shaft fractures, 31.0% of posterior malleolar involvement and 18.8% of isolated vertical medial malleolar fractures in the ankle fractures, and 61.5% of posterior comminution in the tibial plateau fractures. CONCLUSION: E-scooter and e-bike related injuries have a high incidence of tibial shaft fractures, ankle fractures, tibial plateau fractures, and radial head fractures. There should be a high index of suspicion for posterior and medial involvement in lower extremity fractures sustained due to e-scooter or e-bikes. Identifying specific fracture patterns seen in e-scooter and e-bike related mechanisms will help guide management of these injuries.

Travel patterns of free-floating e-bike-sharing users before and during COVID-19 pandemic.

Free-floating micro-mobility as a mobility solution is becoming increasingly popular in cities. In this study, the travel patterns of free-floating electric bike-sharing service (FFEBSS) users before and during the COVID-19 pandemic were explored using big data and data mining. Existing real-time data studies provide a limited understanding of trip patterns and the characteristics of each user. Interpretations concerning the occurrence of life-changing events such as the COVID-19 pandemic are important. This study aimed to understand each user over 13 months comprising multiple time frames of market trends, seasonal change, and the COVID-19 pandemic outbreak. Multiple features were extracted from each user to explain the hidden data characteristics, and a data mining method was employed for clustering and evaluating user similarities with the extracted features. The results showed that FFEBSS users demonstrated a moderately stable travel pattern despite the COVID-19 pandemic, indicating the possibility of micro-mobilities being well adoptedas our future urban transportation.

Systematic review and meta-analysis evaluating the effects electric bikes have on physiological parameters.

BACKGROUND: There is a universal need to increase the number of adults meeting physical activity (PA) recommendations to help improve health. In recent years, electrically assisted bicycles (e-bikes) have emerged as a promising method for supporting people to initiate and maintain physical activity levels. To the best of our knowledge, there have been no meta-analyses conducted to quantify the difference in physiological responses between e-cycling with electrical assistance, e-cycling without assistance, conventional cycling, and walking. METHODS: A systematic review and meta-analysis was conducted following PRISMA guidelines. We identified short-term e-bike studies, which utilized a crossover design comparing physiological outcomes when e-cycling with electrical assistance, e-cycling without electrical assistance, conventional cycling, or walking. Energy expenditure (EE), heart rate (HR), oxygen consumption (VO2 ), power output (PO), and metabolic equivalents (METs) outcomes were included within the meta-analysis. RESULTS: Fourteen studies met our inclusion criteria (N = 239). E-cycling with electrical assistance resulted in a lower energy expenditure (EE) [SMD = -0.46 (-0.98, 0.06), p = 0.08], heart rate (HR) [MD = -11.41 (-17.15, -5.68), p < 0.000, beats per minute], oxygen uptake (VO2 ) [SMD = -0.57 (-0.96, -0.17), p = 0.005], power output (PO) [MD = -31.19 (-47.19 to -15.18), p = 0.000, Watts], and metabolic equivalent (MET) response [MD = -0.83 (-1.52, -0.14), p = 0.02, METs], compared with conventional cycling. E-cycling with moderate electrical assistance resulted in a greater HR response [MD 10.38 (-1.48, 22.23) p = 0.09, beats per minute], and VO2 response [SMD 0.34 (-0.14, 0.82) p = 0.16] compared with walking. CONCLUSIONS: E-cycling was associated with increased physiological responses that can confer health benefits.

E-Bike-Related Trauma in Children and Adults.

BACKGROUND: Electric bike (e-bike) usage is growing worldwide, and so is the e-bike-related injury rate. OBJECTIVE: This study was undertaken to characterize e-bike-related injuries. METHODS: Data of all e-bike-related injuries presenting to our level I trauma center between 2014 and 2016 were collected and analyzed. Adult and pediatric (<18 years of age) e-bike-related injuries were then analyzed separately and compared. RESULTS: Forty-eight patients suffering from e-bike-related injuries presented to our trauma center between January 1, 2014 and December 31, 2016. Seventeen (35%) patients were <18 years of age and 40 (85%) were male. The overall most common mechanism of injury was falling off the e-bike in 24 patients (50%), followed by collision with a static object in 9 patients (18.8%). Head (38%) and facial (33%) injuries were most common in children. In adult patients, orthopedic trauma was predominant, with extremity fractures in 35 (73%) followed by significant lacerations in 14 patients (29%). Severe trauma (Injury Severity Score >15) was found in 17 (35%) patients. The duration of hospital stay was 10.8 ± 6 days, 12 patients (25%) required a stay in the intensive care unit, and 21 patients (43.7%) required surgery. Compared to adults, children (<18 years of age) had significantly more head and face injuries (p = 0.05). CONCLUSION: Our study suggests that e-bike-related trauma may involve serious injuries and have typical injury patterns that resemble those seen in motorcycle-related injuries. Children are more likely to suffer head and face injuries because of their higher head to body ratio. We suggest that these injuries should therefore be triaged appropriately, preferably to a medical facility with proper trauma capabilities.

Riding practices of e-bike riders after the implementation of electric bike management regulations: An observational study in Hangzhou, China.

Objective: This study aimed to understand the riding behaviors of electric bike (e-bike) users in Hangzhou after the "Regulations of Zhejiang Province on the Administration of Electric Bicycles". Methods: The study consisted of two parts, including a questionnaire survey of local e-bike users in Shangcheng District and Jiande County in Hangzhou City, and a cross-sectional observational study of 16 intersections. Results: A total of 789 e-bike riders participated in the questionnaire survey, and the riding behavior of 99,407 e-bike users was observed. The main purpose of using e-bike was work and daily life, 46.0% of them used e-bikes more than 5 days a week, and 58.5% used e-bikes for less than 30 min each time. A vast majority (81.7%) of e-bike riders believe that the implementation of Zhejiang Regulations has significantly improved the safety level of e-bike riding in the region. The field survey found that the correct rates of helmet wearing by e-bike riders and passengers were 78.83% and 42.27%. The main violations were invalid/non-helmet wearing (21.17%), followed by carrying passengers and running red lights (7.94% and 4.26%). The rates of invalid/non-helmet wearing and running red lights were significantly higher during non-morning rush hour, weekends, and roads without separate non-motorized vehicle lanes than in other conditions (all P < 0.05). Additionally, sunny days and crossroads were risk factors for passenger-carrying and invalid/non-helmet wearing compared to rainy/cloudy days and T-intersections. Conclusions: The phenomenon that e-bike users' correct practice lags far behind the awareness of various violations has shown some improvement. To further enhance safety measures for e-bike riders, it is necessary to promote education, improve infrastructure, and strengthen law enforcement, in support of the "Zhejiang Regulations" and behavioral interventions.

E-scooter and E-bike injury pattern profile in an inner-city trauma center in upper Manhattan.

BACKGROUND: Electric bikes and scooters are becoming popular means of short-distance transportation in major cities. Regulations for safe riding established by ride-sharing companies and local governments have not been effectively implemented. Inner-city hospitals are at the frontline of receiving traumas related to e-bikes and e-scooters and are receiving an increasing number of injuries. The works of literature reporting these injuries are limited. METHOD: This study reviewed all the trauma activations at a major trauma center in NYC from 04/2019 to 08/2021. Patients with e-bike and e-scooter injuries were included in the study. Socio-demographics of riders, passengers, injury patterns, and outcomes were reviewed. Logistics regression was used to analyze the factors associated with Injury Severity Scale. RESULTS: We reviewed 1979 patient charts of trauma activation in the Emergency Department. We included 88 scooters, 24 E-bike, and 5 nonrider scooter injuries. 91% were male and 9% were Female victims. The majority were African American patients (34%) and Hispanic patients (46%). 87% belonged to the 18-50 years age group, and 13% were above 50 years and below 18 years were excluded from the study. 36% of victims were under the influence of drugs or alcohol and only 25% of riders wore helmets. 58% of patients were discharged from the ED, 42% required hospital admission, and 14% required ICU care. Odds of non-mild injury (moderate to critical injury) in comparison to mild injury were significantly greater with increasing age. CONCLUSIONS: The use of e-bikes and e-scooters is increasing as a means of affordable short-distance transportation but with evidence of significant injuries with varying severity. These findings suggest a need to review public policy regarding e-bike and electric scooter use regulations for the safety of riders and pedestrians; Driving While Intoxicated (DWI) law enforcement, mandatory helmet, education, speed control, creation of special lanes, and no car zones.

Electric bike (non)users' health and comfort concerns pre and peri a world pandemic (COVID-19): A qualitative study.

INTRODUCTION: The unprecedented COVID-19 pandemic affects different domains of society, including the transport system. Due to the impacts of social distancing, research concerning electric bike (e-bike) applications and non(user) health and comfort concerns is needed. This research aims to understand the health and comfort concerns of e-bike (non)users in both pre (PR) and peri (PE) pandemic situations and explore how the PE situation triggers (non)users to use e-bikes. METHODS: An interpretive description qualitative method in the form of semi-structured interviews was used to gather the empirical material for this research. RESULTS: Twenty-three (non)user participants were interviewed in the PR situation, and 12 of these participants were interviewed again in the PE situation. The comfort provided by the e-bike did not outweigh its cost as a factor for nonusers considering investing in the e-bikes in the PR situation. However, nonusers acknowledged that e-bikes can serve as substitutes for public transport by eliminating social interactions and consequently potential health concerns, in addition to providing comfortable mobility. E-bike users were in agreement concerning physical activity and the health benefits of using e-bikes in the PR situation. Their opinions differed slightly, as women placed less emphasis on the physical activity provided by e-bike use. However, gender opinions converged regarding health concerns about using public transport in PE situations. Infrastructure facilities and e-bike performance are evident as users' comfort concerns in the PE situation. CONCLUSION: The results highlight the role of the e-bike in PE situations as a reliable transport mode and suggest that there is considerable potential for e-bikes as substitutes for public transport in the post-pandemic situation. The findings are applicable to e-bike level-of-service studies in order to provide an overview of the user's experience of comfort.

Road safety situation of electric bike riders: A cross-sectional study in courier and take-out food delivery population.

OBJECTIVE: Almost all courier and take-out food delivery riders in China use electric bikes as the main transport mode. This study aims to understand their riding behaviors and road traffic injury information of this population. METHODS: A cross-sectional field study focused on this population was conducted, including roadside observation and face-to-face retrospective street intercept interviews. RESULTS: Six hundred target delivery riders were observed and 480 were interviewed. The rate of overspeeding was 91.3%, and windshield use during winter was 91.2%. Traffic violation behaviors observed included riding in the motor vehicle lane (32.8%), not waiting behind the white line at a red light (23.3%), and using cell phone when riding (21.2%). Helmet use was significantly more common during the day (73.0%) than at night (64.7%; P = .028). About 46.5% of respondents rode an e-bike more than 8 h per day. In addition, 76.5% of interviewees had been involved in a traffic crash at least once. About 13.9% of crashes happened in motor vehicle lanes and 8.2% on sidewalks. Logistic regression analysis indicated that compared with uninjured riders, injured riders showed significantly greater odds ratios of unsafe behaviors for running red lights (odds ratio [OR] = 1.75) and protective factors for wearing a helmet (OR = 0.56). CONCLUSIONS: The courier and take-out food delivery population is a vulnerable occupational group and road traffic injuries related to e-bike use require more attention.

Analyzing E-Bikers' Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model.

To identify and quantify the factors that influence the risky riding behaviors of electric bike riders, we designed an e-bike rider behavior questionnaire (ERBQ) and obtained 573 valid samples through tracking surveys and random surveys. An exploratory factor analysis was then conducted to extract four scales: riding confidence, safety attitude, risk perception, and risky riding behavior. Based on the exploratory factor analysis, a structural equation model (SEM) of electric bike riding behaviors was constructed to explore the intrinsic causal relationships among the variables that affect the risky e-bike riding behavior. The results show that the relationship between riding confidence and risky riding behavior is mediated by risk perception and safety attitudes. Safety attitude was found to be significantly associated with risky riding behaviors. Specifically, herd mentality is most closely related to safety attitudes, which means that those engaged in e-bike traffic management and safety education should pay special attention to riders' psychological management and education. Risk perception has a direct path to risky riding behaviors. Specifically, stochastic evaluation and concern degree are significantly related to e-bike riders' risk perception. The findings of this study provide an empirical basis for the creation of safety interventions for e-bike riders in China.

Awareness, riding behaviors, and legislative attitudes toward electric bikes among two types of road users: An investigation in Tianjin, a municipality in China.

OBJECTIVE: This study aimed to understand the awareness, riding behaviors, and legislative attitudes of electric bike (e-bike) users and non-e-bike road users toward e-bikes in Tianjin, a municipality in China. METHODS: This cross-sectional investigation included 2 components. The field survey was conducted in 9 districts (4 urban and 5 rural) from 2015 to 2017. Adult participants were interviewed using a street intercept method. The online survey was conducted using the WeChat social platform. A series of questions related to awareness and practice of e-bike safety-related issues was asked. RESULTS: A total of 16,859 interviews were completed, including 1,653 (794 e-bike users and 859 other road users) in-person interviews by field survey and 15,206 (4,426 e-bike users and 10,780 other road users) by online survey. Except for ignoring a red light when making a left turn (P = .000) and waiting across the white line at a red light (P = .000), which e-bike users were lower than other road users, there were no significant differences between e-bike users and other road users in regards to the correct awareness rate of riding in the opposite direction, riding in a motor vehicle lane, running red lights, jaywalking, speeding, carrying adult passengers, and riding on the expressway (P > .05). In addition, 74.2% of e-bike users considered helmet use necessary (P = .000) and 54.7% thought that installing a windshield is wrong (P = .000), which was higher than other road users (49.1 and 48.4%, respectively). Other road users had greater awareness than e-bike users regarding whether turning left at a red light is wrong (91.7 vs. 85.1%), waiting across the white line when the light is red is wrong (86.6 vs. 75.9%), lighs should be turned on at night (94.8 vs. 90.3%). Correct practices were far behind awareness in all kinds of violation behaviors (P = .000) among e-bike users in the field survey. The rate of public support for legislation including those who very much support and support legislation was 93.34% in the field survey and 87.68% in the online survey. CONCLUSIONS: E-bike users had lower correct awareness rate than other road users regarding e-bike violation behaviors but were more concerned about safety protection than other road users. E-bike users' correct practices were far behind their awareness for all kinds of violation behaviors. Public education on the traffic law needs to be strengthened among e-bike users. The public strongly supported special regulations for e-bike use, such as helmet use.

Underreporting, crash severity and fault assignment of minor crashes in China - a study based on self-reported surveys.

Unreported minor crashes have importance as a surrogate for more serious crashes that require infrastructure, education, and enforcement strategies; and they still inflict damages. To study factors that influence underreporting, cause, and severity of minor crashes; a survey was performed in Kunming and Beijing to collect self-reported personal characteristics and crash history data of the three major urban road users in China: automobile drivers, bicycle riders and electric bike (e-bike) riders. Underreporting rates of automobile to automobile, automobile to non-motorized vehicle, and non-motorized vehicle to non-motorized vehicle crashes are 56%, 77% and 94%, respectively. Minor crashes with higher reported injury severity levels are more likely to be reported. E-bike riders without a driver's license are more likely to cause crashes. Licensing and education could be an effective way to reduce their crashes. The party that is not at fault in a crash is more likely to sustain high level of injury.

HEALTHeBIKES - Smart E-Bike Prototype for Controlled Exercise in Telerehabilitation Programs.

E-Bikes in telerehabilitation programs could be a new intervention for more sustainable rehabilitation results. The aim is to design and build a prototype of an E-Bike usable for rehabilitation - a HEALTHeBIKE. It should avoid over-exercising, work independently of the environment and it should enable cycling in a group despite different reference exercise intensities. To achieve these goals, requirements for this system architecture have been identified. A system architecture including an Arduino microcontroller, an Android smartphone and a telemonitoring platform was presented. A power output regulated proportional-integral controller to adjust the motor assistance has been implemented. A feasibility study with two subjects cycling in a group was performed. Seven test rides on varying terrain (flat, hilly, mountainous and uphill) with the same and different exercise intensities were completed. The mean power output was close to or below the target power output of the cyclist for all test rides with a maximal error of 6.7% above and 27.6% below the target. Although the exercise intensities of the two subjects were clearly different, cycling in a group was possible without over-exercising.

Road traffic injuries among riders of electric bike/electric moped in southern China.

OBJECTIVE: Electric bike/moped-related road traffic injuries have become a burgeoning public health problem in China. The objective of this study was to identify the prevalence and potential risk factors of electric bike/moped-related road traffic injuries among electric bike/moped riders in southern China. METHODS: A cross-sectional study was used to interview 3,151 electric bike/moped riders in southern China. Electric bike/moped-related road traffic injuries that occurred from July 2014 to June 2015 were investigated. Data were collected by face-to-face interviews and analyzed between July 2015 and June 2017. RESULTS: The prevalence of electric bike/moped-related road traffic injuries among the investigated riders was 15.99%. Electric bike/moped-related road traffic injuries were significantly associated with category of electric bike (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI], 1.01-1.82), self-reported confusion (AOR = 1.77, 95% CI, 1.13-2.78), history of crashes (AOR = 6.14, 95% CI, 4.68-8.07), running red lights (AOR = 3.57, 95% CI, 2.42-5.25), carrying children while riding (AOR = 1.96, 95% CI, 1.37-2.85), carrying adults while riding (AOR = 1.68, 95% CI, 1.23-2.28), riding in the motor lane (AOR = 2.42, 95% CI, 1.05-3.93), and riding in the wrong traffic direction (AOR = 1.63, 95% CI, 1.13-2.35). In over 77.58% of electric bike/moped-related road traffic crashes, riders were determined by the police to be responsible for the crash. Major crash-causing factors included violating traffic signals or signs, careless riding, speeding, and riding in the wrong lane. CONCLUSION: Traffic safety related to electric bikes/moped is becoming more problematic with growing popularity compared with other 2-wheeled vehicles. Programs need to be developed to prevent electric bike/moped-related road traffic injuries in this emerging country.

Training with an Electric Exercise Bike versus a Conventional Exercise Bike during Hemodialysis for Patients with End-stage Renal Disease: A Randomized Clinical Trial.

OBJECTIVE: Hemodialysis (HD) patients have lower fitness levels than healthy subjects because of various structural, metabolic, and functional abnormalities secondary to uremic changes in skeletal muscles. Aerobic and resistance exercises are beneficial in improving not only physical function, including maximal oxygen uptake and muscle strength, but also anthropometrics, nutritional status, and hematologic indices. The use of electric ergometers that place light loads on patients has been implemented at many dialysis facilities in Japan. However, reports comparing the effects on body function of electric and variable-load ergometers are few. This study aimed to compare electric ergometers and variable-load ergometers in terms of exercise outcomes in HD patients. METHODS: A total of 15 ambulatory HD patients were randomly divided into two groups: the variable-load ergometer group (n=8) and the electric ergometer group (n=7). HD patients exercised at a level based on their physical function three times a week for 12 weeks. RESULTS: After the 12-week intervention period, only the variable-load ergometer group experienced significant increases in lower extremity muscle strength and exercise tolerance. CONCLUSION: This study confirmed that conventional aerobic training and electric bike exercise during HD were efficacious and safe without causing sudden hypotension or any other side effects. However, exercise using a variable-load ergometer may be more effective than exercise using an electric bike in improving the physical function of HD patients. Exercise using a variable-load ergometer elicited specific whole-body and local effects.

[Life Cycle Assessment of Traction Lead-acid Batteries for Electric Bikes in China].

This research undertook a life cycle assessment (LCA) for lead-acid batteries (LABs) used in electric bikes, the fastest growing LABs in China. A cradle-to-grave LCA model was established to identify the key materials or processes that contribute most to environmental impacts within the life cycle of LABs, including material production, battery manufacture, transportation, use, and end-of-life. A large amount of primary data obtained from enterprisers and a Chinese LCA database were used in this research to reflect the status of technology and environmental management for the related industries in China. The results indicate that material production and LAB use dominate in resource consumption and environmental impacts during the life cycle of LABs. Material production is the most important driver of such impacts as abiotic resources depletion (699%), eutrophication (89%), photochemical smog production (98%), ozone depletion (117%), total human toxicity (159%), and ecological toxicity (484%). Battery use is responsible for 83% of primary energy use and contributes the highest potentials to the impacts related to energy, including global warming potential (86%) and acidification potential (70%). Recovery of materials at the end-of-life stage will significantly mitigate the overall life cycle impacts by reducing virgin material consumption. Based on the findings, there are several substantial opportunities to reduce the overall environmental impacts of batteries, such as prolonging the lifetime of batteries, reducing the metal consumption in batteries, and improving the technology and management in recovery of end-of-life batteries.

Mobile phone use among motorcyclists and electric bike riders: A case study of Hanoi, Vietnam.

Motorcyclist injuries and fatalities are a major concern of many developing countries. In Vietnam, motorcycles are involved in more than 70% of all road traffic crashes. This paper aims to explore the prevalence and factors associated with mobile phone use among motorcyclists and electric bike riders, using a case study of Hanoi, Vietnam. A cross-sectional observation survey was undertaken at 12 sites, in which each site was surveyed during a two-hour peak period from 16:30 to 18:30 for two weekdays and one weekend day. A total of 26,360 riders were observed, consisting of 24,759 motorcyclists and 1601 electric bike riders. The overall prevalence of mobile phone use while riding was 8.4% (95% CI: 8.06-8.74%) with calling having higher prevalence than screen operation: 4.64% (95% CI: 4.39-4.90%) vs. 3.76% (95% CI: 3.52-3.99%) respectively. Moreover, the prevalence of mobile phone use was higher among motorcyclists than electric bike riders: 8.66% (95%CI: 8.30-9.01%) vs. 4.43% (95% CI: 3.40-5.47%) respectively. Logistic regression analyses revealed that mobile phone use while riding was associated with vehicle type, age, gender, riding alone, weather, day of week, proximity to city centre, number of lanes, separate car lanes, red traffic light duration, and police presence. Combining greater enforcement of existing legislations with extensive education and publicity programs is recommended to reduce potential deaths and injuries related to the use of mobile phones while riding.

Risky riding: Naturalistic methods comparing safety behavior from conventional bicycle riders and electric bike riders.

As electric bicycles (e-bikes) have emerged as a new transportation mode, their role in transportation systems and their impact on users have become important issues for policy makers and engineers. Little safety-related research has been conducted in North America or Europe because of their relatively small numbers. This work describes the results of a naturalistic GPS-based safety study between regular bicycle (i.e., standard bicycle) and e-bike riders in the context of a unique bikesharing system that allows comparisons between instrumented bike technologies. We focus on rider safety behavior under four situations: (1) riding in the correct direction on directional roadway segments, (2) speed on on-road and shared use paths, (3) stopping behavior at stop-controlled intersections, and (4) stopping behavior at signalized intersections. We find that, with few exceptions, riders of e-bike behave very similarly to riders of bicycles. Violation rates were very high for both vehicles. Riders of regular bicycles and e-bikes both ride wrong-way on 45% and 44% of segments, respectively. We find that average on-road speeds of e-bike riders (13.3kph) were higher than regular bicyclists (10.4kph) but shared use path (greenway) speeds of e-bike riders (11.0kph) were lower than regular bicyclists (12.6kph); both significantly different at >95% confidence. At stop control intersections, both bicycle and e-bike riders violate the stop signs at the similar rate with bicycles violating stop signs at a slightly higher rate at low speed thresholds (∼80% violations at 6kph, 40% violations at 11kph). Bicycles and e-bikes violate traffic signals at similar rates (70% violation rate). These findings suggest that, among the same population of users, e-bike riders exhibit nearly identical safety behavior as regular bike riders and should be regulated in similar ways. Users of both technologies have very high violation rates of traffic control devices and interventions should occur to improve compliance.

A hazard-based duration model for analyzing crossing behavior of cyclists and electric bike riders at signalized intersections.

This paper presents a hazard-based duration approach to investigate riders' waiting times, violation hazards, associated risk factors, and their differences between cyclists and electric bike riders at signalized intersections. A total of 2322 two-wheeled riders approaching the intersections during red light periods were observed in Beijing, China. The data were classified into censored and uncensored data to distinguish between safe crossing and red-light running behavior. The results indicated that the red-light crossing behavior of most riders was dependent on waiting time. They were inclined to terminate waiting behavior and run against the traffic light with the increase of waiting duration. Over half of the observed riders cannot endure 49s or longer. 25% of the riders can endure 97s or longer. Rider type, gender, waiting position, conformity tendency and crossing traffic volume were identified to have significant effects on riders' waiting times and violation hazards. Electric bike riders were found to be more sensitive to the external risk factors such as other riders' crossing behavior and crossing traffic volume than cyclists. Moreover, unobserved heterogeneity was examined in the proposed models. The finding of this paper can explain when and why cyclists and electric bike riders run against the red light at intersections. The results of this paper are useful for traffic design and management agencies to implement strategies to enhance the safety of riders.

Unsafe riding practice among electric bikers in Suzhou, China: an observational study.

BACKGROUND: Electric bike (E-bike)-related deaths have been increasing rapidly in China and such injuries may be partly attributable to unsafe riding practice. OBJECTIVES: To describe potentially unsafe riding behaviours among electric bikers (E-bikers) and to investigate factors influencing these practices in China. METHODS: In September 2012, a cross-sectional observation study including a speed measurement component was conducted in Wuzhong (an urban district) and Zhangjiagang (a rural district) of Suzhou, Jiangsu Province, China. Hand-held radar speed metres were used to read travelling speeds of E-bikes and a pro forma observation checklist was used to collect data on road riding practice. Mixed-effect logistic regressions were used to calculate adjusted ORs and 95% CIs for the association between speeding, road rule violations and helmet use and their influencing factors. RESULTS: Among 800 E-bikes with a speed reading, 70.9% exceeded the designed speed limit of 20 km/h. Among a further 20 647 E-bikers observed, 38.3% did not comply with the road rules when entering intersections; and only 2.2% wore helmets. No regional variation was identified between urban and rural areas. Male E-bikers were associated with more speeding and road rule violations, whereas riding a pedal-equipped E-bike was associated with less road rule violations and less helmet use. CONCLUSIONS: Unsafe riding practices such as speeding, road rule violations and lack of helmet use were commonplace among E-bikers, especially among men. The study findings indicate that measures aimed at improving E-bike safety are required in China.

Understanding on-road practices of electric bike riders: an observational study in a developed city of China.

Although millions of electric bikes (E-bikes) operate in China and many associated deaths and injuries have been reported, E-bikers' on-road practices are poorly characterized and few direct observational studies have been performed. This study aims to describe riding behaviors among E-bikers and to investigate factors influencing these practices to inform injury prevention. In March 2012, a cross-sectional observational study was conducted at 14 randomly selected intersections in Suzhou during a 7-day period. A pro-forma observation checklist was used to collect data on road riding practice. Adjusted Odds Ratios (OR) and 95% Confidence Intervals (CI) to assess the likelihood of specific riding practices among E-bikers were evaluated using mixed-effects logistic regression. Among 18,150 E-bikers observed, 37.6% rode E-bikes with cycling pedals, 86.0% of E-bikes were registered, 26.6% did not comply with the road rules, and 41.1% wore at least one safety item. The overall prevalence of carrying passengers, riding in a motor vehicle lane, running red lights, riding in opposite directions (i.e., facing oncoming traffic), mobile phone use, and helmet use were 12.4% (95%CI: 11.9-12.9%), 1.9% (95%CI: 1.7-2.1%), 4.8% (95%CI: 4.5-5.1%), 3.4% (95%CI: 3.1-3.7%), 0.4% (95%CI: 0.3-0.5%), and 9.0% (95%CI: 8.5-9.4%), respectively. Male E-bikers was associated with increased helmet use and riding in motor vehicle lanes, whereas riding a registered E-bike was associated with reduced likelihood of carrying passengers. This study demonstrates common road rule violations and low helmet use among E-bikers and supports the urgent need to develop additional regulations and behavioral interventions to improve safety practice among E-bikers in China.