Risk factors affecting crash injury severity for different groups of e-bike riders: A classification tree-based logistic regression model

IntroductionAs a convenient and affordable means of transportation, the e-bike is widely used by different age rider groups and for different travel purposes. The underlying reasons for e-bike riders suffering from severe injury may be different in each case.MethodThis study aims to examine the underlying risk factors of severe injury for different groups of e-bike riders by using a combined method, integration of a classification tree and a logistic regression model. Three-year of e-bike crashes occurring in Hunan province are extracted, and risk factor including rider’s attribute, opponent vehicle and driver’s attribute, improper behaviors of riders and drivers, road, and environment characteristics are considered for this analysis.ResultsE-bike riders are segmented into five groups based on the classification tree analysis, and the group of non-occupational riders aged over 55 in urban regions is associated with the highest likelihood of severe injury among the five groups. The logistics analysis for each group shows that several risk factors such as high-speed roads have commonly significant effects on injury severity for different groups; while major factors only have significant effects for specific groups.Practical applicationBased on model results, policy implications to alleviate the crash injury for different e-bike riders groups are recommended, which mainly include enhanced education and enforcement for e-bike risky behaviors, and traffic engineering to regulate the use of e-bikes on high speed roads.     

Can a unique appearance of e-bikes,coupled with information on their characteristics,influence drivers’ gap acceptance?

Abstract

Objective: Car drivers tend to underestimate the speed of e-bikes and accept smaller gaps for crossing in front of them compared to conventional bicycles. As an explanation, it has been suggested that car drivers rely on their previous experience with conventional bicycles, which tells them that those mostly travel at low speeds. E-bikes, which look just like regular bicycles, do not conform to this expectation, resulting in potentially dangerous interactions. Based on this assumption, researchers have suggested to increase other road users’ awareness of e-bikes’ higher speeds by giving them a distinct appearance. The goal of our experiment was to investigate the effects of such a unique appearance, aided by clear instructions about the higher speeds of e-bikes, on gap acceptance.

Method: In order to investigate the effect of appearance independent of the effect of bicycle type, we used video sequences of conventional bicycles and e-bikes approaching at different levels of speed. The riders (regardless of what type of bike they were actually riding) either wore an orange helmet as an indicator for an e-bike, or a gray helmet indicating a conventional bicycle. Fifty participants were asked to indicate the smallest acceptable gap for a left turn in front of the cyclist or e-bike rider.

Results: The results showed significantly smaller acceptable gaps when confronted with the gray helmet (signal for bicycle) compared to the orange helmet (signal for e-bike), whereas there was no difference between the actual bicycle types.

Conclusions: Overall, the results indicate that informing about e-bikes characteristics in combination with a unique appearance can lead to a more cautious behavior among car drivers.     

Mobile phone use while riding a motorcycle and crashes among university students

Objective: Motorcycle crashes are a significant road safety challenge, particularly in many low- and middle-income countries where motorcycles represent the vast majority of their vehicle fleet. Though risky riding behaviors, such as speeding and riding under the influence of alcohol, have been identified as important contributors to motorcycle crashes, little is understood about the effect of using a mobile phone while riding on motorcycle crash involvement. This article investigates crash involvement among motorcycle riders with risky riding behaviors, particularly using a mobile phone while riding.

Methods: Data were obtained from an online survey of university students’ risky riding behaviors in Vietnam administered between March and May 2016 (n?=?665).

Results: Results show that 40% of motorcycle riders reported to have experienced a crash/fall and nearly 24% of motorcycle riders indicated that they had been injured in a crash/fall. Effects of mobile phone use while riding on safety of motorcycle riders are highlighted. Specifically, more frequent use of a mobile phone for texting or searching for information while riding is associated with a higher chance of being involved in a crash/fall. The results also show that drink riding is associated with a higher chance of being injured.

Conclusions: Overall this article reveals significant safety issues of using a mobile phone while riding a motorcycle, providing valuable insight for designing education and publicity campaigns.     

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.     

Using CyclePhilly data to assess wrong-way riding of cyclists in Philadelphia

ProblemThe increasing use of smartphones and low cost GPS have provided new sources for collecting data and using them to explain travel behavior. This study aims to use data collected from a smartphone application (CyclePhilly) to explain wrong-way riding behavior of cyclists on one-way segments to help better identify the demographic and network factors influencing the wrong-way riding decision making.MethodsThe data used in this study consist of two different sources: (a) Route trips data downloaded from the CyclePhilly Website contained trips detailed up to segment level, collected from May 2014 to April 2016 (12,202 trips by 300 unique users); and (b) Open Street Maps (OSM). Using ArcGIS, we calculate detour routes for each wrong way segment. We then built a mixed logistic regression model to identify the trip and riders' characteristics affecting wrong-way riding behavior. Next, we explore the characteristics of road facilities associated with wrong-way riding behavior.Results and discussionOnly 2.7% of travel distance is wrong-way, yet 42% of trips include a wrong-way segment. Commute trips have a higher chance of wrong-way riding. The longer the trips also include more wrong-way riding. Segments with higher detour ratios (ratio of distance with a detour to the wrong-way distance) are found to be associated with more wrong-way behavior. Compared to roads with no bike lane, roads with sharrow markings and buffered bike lane discourage wrong way riding.Practical applicationsThis study proposes new methods that can be adapted to use naturalistic and probe data and analyze city-wide aberrant riders' behavior. These help planners and engineers choose between various types of bike infrastructure. Wrong-way riding is one application that can be investigated, but probe bicycle datasets provide unprecedented resolution and volume of data that will allow for more sophisticated safety and planning analyses.     

Pediatric electric bicycle injuries and comparison to other pediatric traffic injuries

Objective: The objective of this study was to conduct a comprehensive analysis of demographics, injury characteristics and hospital resource utilization of significant pediatric electric bicycle (e-bike) injuries leading to hospitalization following an emergency department visit in comparison to pediatric injuries caused by other traffic related mechanisms.

Methods: A retrospective review of all pediatric traffic injury hospitalizations following an emergency department visit to a level I trauma center between October 2014 and September 2016 was conducted. Data regarding age, sex, number of computed tomography (CT) scans obtained, number of major procedures, length of hospital stay (LOS), Injury Severity Score (ISS), and number of injuries per patient were collected and compared between e-bike injuries and other traffic injuries.

Results: Three hundred thirty-seven admissions were analyzed: 46 (14%) were due to e-bike injuries (29% of patients >12 years). Age, proportion of brain injuries, and use of CT were significantly increased compared to mechanical bicycle injuries (13.1?±?3.4 vs. 10.6?±?3.6, 13% vs. 3%, 1 [0–3] vs. 1 [0–1], P < .01, P = .03, P = .05). Age, LOS, and use of CT were significantly increased compared to injuries caused to automobile passengers (13.1?±?3.4 vs. 7.4?±?5.3, 1 [1–3] vs. 1 [1–2], 1 [0–3] vs. 0 [0–1], P < .01, P = .03, P = .01), as well as ISS and number of injuries per patient (P = .04, P < .01). Injuries caused by e-bikes were similar to injuries caused to pedestrians, except for age (13.1?±?3.4 vs. 8.5?±?3.7, P < .01). Multivariable analysis revealed a significant association between mechanism of injury and ISS, with increased ISS among e-bike injuries compared to mecahnical bike injuries (OR 2.56, CI 1.1–5.88, P = 0.03) and automobile injuries (OR 4.16, CI 1.49–12.5, (P < .01).

Conclusion: E-bikes are a significant cause of severe injury in children compared to most other traffic injuries, particularly in older children.     

Motorists' knowledge,attitudes and practices toward alcohol-impaired driving/riding in Ghana

Objectives: The main objective of this study was to establish the knowledge, attitudes, and practices toward drink driving/riding as a risk factor for road traffic crashes in 3 regional capitals in Ghana.

Methods: The study used a face-to-face approach to randomly sample motorists who were accessing various services at fuel/gas stations, garages, and lorry terminals in 3 cities in Ghana.

Results: Over the previous 12 months, 24% of all motorists and 55% of motorists who were current alcohol users reported driving or riding a vehicle within an hour of alcohol intake. On average, motorists/riders who were current alcohol users consumed 4 standard drinks per drinking occasion. Generally, 83% of motorists who currently use alcohol walked, rode, or drove home after consuming alcohol away from their homes. Motorists/riders who reported drink driving were 4 times more likely to have had previous traffic violation arrests compared to those who reported no drink driving/riding (P =.001). Respondents were of the opinion that speeding was the major cause of traffic crashes, followed by driver carelessness, poor road conditions, inexperienced driving, and drink driving, in that order. Thirty-six percent of motorists who use alcohol had the perception that consuming between 6 and 15 standard drinks was the volume of alcohol that will take them to the legal blood alcohol concentration (BAC) limit of 0.08%. Compared to females, male motorists/riders were more likely to report drink driving (adjusted odds ratio [AOR] = 5.15; 95% confidence interval [CI], 2.31 to 11.47). Private motorists also reported a higher likelihood of drink driving compared to commercial drivers (AOR = 3.36; 95% CI, 1.88 to 6.02). Only 4% of motorists knew the legal BAC limit of Ghana and only 2% had ever been tested for drink driving/riding.

Conclusion: The volumes of alcohol that motorists typically consume per drinking occasion were very high and their estimates of the number of drinks required to reach the legal BAC limit was also very high. Provision of authoritative information advising motorists about safe, responsible, or low-risk levels of alcohol consumption is imperative. Many traffic violations including drink driving were reported, thus suggesting a need for enhanced policing and enforcement. However, given the low level of knowledge of the legal BAC limit, educating motorists about how many drinks will approximate the legal BAC should be intensified prior to an increase in enforcement; otherwise, the desired outcome of enforcement may not be achieved.     

The casualties from electric bike and motorized scooter road accidents

Objective: The objective of this study was to describe demographic and injury characteristics of hospitalized injured patients involved in e-bike and motorized scooter accidents at a national level in Israel divided by different road user groups: riders and pedestrians.

Methods: This was a retrospective study based on data from the National Trauma Registry, between January 1, 2013, and December 31, 2015. All hospitalized casualties due to the involvement of an e-bike or motorized scooter were included. The type of hospitalized road user was further categorized and described by different variables.

Results: During the study period, the Israel Trauma Registry identified 795 hospitalized patients due to an e-bike or motorized scooter accident, with a dramatic 6-fold increase from 2013 to 2015. Although the majority of the injured patients were riders, 8% were pedestrians. Among the total casualties, 33% were children aged 0–14 years and among pedestrians 42% were children and 33% were seniors (ages 60+). Five persons died in hospital, 3 riders and 2 pedestrians.

Conclusions: E-bike and motorized scooter riders represent the majority of patients hospitalized due to related traffic incident. This finding questions the social and economic advantages of electric-powered 2-wheeled vehicles.     

Modeling faults among e-bike-related fatal crashes in China

Objectives: This article aims to model fault in e-bike fatal crashes in a county-level city in China.

Method: Three-year crash data are retrieved from the crash reports (2012–2014) from the Taixing Police Department. A mixed logit model is introduced to explore significant factors associated with fault assignment, as well as accounting for similarity among fault assignment and heterogeneity within unobserved variables.

Results: The modeling results indicate some interesting new findings. First, precrash behaviors of both drivers and e-bike riders are found to be significant to fault assignment. Second, bike lane and median type are significantly associated with e-bike rider fault commitment. Third, specific groups of e-bike riders (low-educated and older) and drivers (heavy good vehicles) are more likely to be at fault in e-bike crashes. Last, crash location and the built environment have significant correlations with faulty behaviors of e-bike riders.

Conclusions: Safety countermeasures are proposed including (1) the deployment of traffic design and control elements including physically separated bike lanes, medians, video surveillance systems for e-bike riders, and left-turning treatments for nonmotorists (e.g., a 2-step e-bike left turning); (2) the amendment of the current traffic regulations on drunk e-bike riders and child e-bike passengers; (3) the development of a license system for specific e-bike rider groups (older and low-educated) and a safety campaign for drivers (to increase safety awareness when parking on-street or driving heavy good vehicles). Some interesting future research topics are also suggested: e-bike riders' behaviors at unsignalized intersections and mid-block openings, e-bike safety in suburban areas, and an in-depth study of the effect of the built environment on e-bike safety.     

Risky behaviors and helmet use among young adolescent motorcyclists in Southern Thailand

Background: In Thailand, road traffic injuries are the leading cause of death for youth ages 15–19 years, with 80% of the injuries and deaths from motorcycle accidents. Objectives: To determine the prevalence of child and young adolescent motorcyclists in Hat Yai municipality and their risk behaviors. Method: A cross-sectional study was conducted between June 2011 and March 2012 in which 2,471 students, ages 8 to 18 years, were recruited from 9 primary and secondary schools in Hat Yai municipality. The questionnaire included questions on being a motorcycle rider or passenger, risky behaviors, and helmet use while riding. Results: Of the total, 1,573 (63.7%) were riders and 898 (36.3%) were pillion passengers. The majority of the riders younger than 15 years rode their motorcycle mainly only in narrow streets for a short trip. Only 30% of the riders wore a helmet every time they rode a motorcycle. About 10% of the participants riding or a passenger on a motorcycle had consumed alcohol at least once before riding their motorcycle. Multiple logistic regression analysis found that motorcycle injuries were significantly associated with speeds greater than 60 km/h, not wearing a helmet while riding, and alcohol consumption before riding (odds ratios 1.63, 1.59, and 3.09, respectively). Conclusion: Nearly two thirds of young adolescents in Hat Yai municipality were motorcycle riders. These young adolescents were at risk of traffic injuries because more than 50% of them had ridden at high speed or not worn a helmet while riding, and some of them had consumed alcohol before riding.     

Drink driving and risky behavior among university students in southwestern Nigeria—Implications for policy development

Background: Drink driving contributes significantly to road traffic injuries. Little is known about the relationship between drink driving and other high-risk behaviors in non-Western countries. The study aimed to assess the relationship between drink driving and other risky behaviors including making phone calls, sending text messages, nonuse of protective gear, and driving against traffic.

Methods: A cross-sectional survey of risky behavior among undergraduates was conducted. A stratified random sampling method was used to identify young undergraduates who had driven a motorized vehicle in the past year. The Alcohol Use Disorder Identification Test (AUDIT) and other tools developed by researchers were used to identify the risky behaviors.

Results: Of 431 respondents, 10.7% had engaged in drink driving in the past 12 months. The most common risky behavior was making phone calls (63.7%), followed by nonuse of helmets (54.7%), driving against traffic (49.2%), nonuse of seat belts (46.8%), and sending text messages (26.1%). Alcohol use was significantly associated with making phone calls (U = 1.148; P < .0001), sending text messages (U = 1.598; P = .021), nonuse of helmets (U = 1.147; P < .0001), driving against traffic (U = 1.234; P < .0001), and nonuse of seat belts (U = 3.233; P = .001). Drink driving was associated with all risky behaviors except nonuse of seat belts (U = 1.842; P = .065).

Conclusion: Alcohol use and drink driving were associated with multiple risky driving behaviors. This provides useful insight for policy development and presents additional challenges for traffic injury prevention.     

Prevalence of alcohol-impaired driving and riding in northern Ghana

Objective: The objective of this study was to determine the roadside prevalence of alcohol-impaired driving among drivers and riders in northern Ghana. The study also verifies motorists' perceptions of their own alcohol use and knowledge of the legal blood alcohol concentration (BAC) limit in Ghana.

Method: With the assistance of police, systematic random sampling was used to collect data at roadblocks using a cross-sectional study design. Breathalyzers were used to screen whether motorists had detectable alcohol in their breath and follow-up breath tests were conducted to measure the actual breath alcohol levels among positive participants.

Results: In all, 9.7% of the 789 participants had detectable alcohol, among whom 6% exceeded the legal BAC limit of 0.08%. The prevalence of alcohol-impaired driving/riding was highest among cyclists (10% of all cyclists breath-tested) followed by truck drivers (9%) and motorcyclists (7% of all motorcyclists breath-tested). The occurrence of a positive BAC among cyclists was about 8 times higher (odds ratio [OR] = 7.73; P < .001) and it was 2 times higher among motorcyclists (OR = 2.30; P = .039) compared to private car drivers. The likelihood for detecting a positive BAC among male motorists/riders was higher than that among females (OR = 1.67; P = .354). The odds for detecting a positive BAC among weekend motorists/riders was significantly higher than on weekdays (OR = 2.62; P = .001).

Conclusion: Alcohol-impaired driving/riding in Ghana is high by international standards. In order to attenuate the harmful effects of alcohol misuse such as alcohol-impaired driving/riding, there is the need to educate road users about how much alcohol they can consume and stay below the legal limit. The police should also initiate random breath testing to instill the deterrence of detection, certainty of apprehension and punishment, and severity and celerity of punishment among drink-driving motorists and riders.     

Calling,texting, and searching for information while riding a motorcycle: A study of university students in Vietnam

Objective: The objective of this study was to investigate the prevalence of calling, texting, and searching for information while riding a motorcycle among university students and the influences of sociodemographic characteristics, social norms, and risk perceptions on these behaviors.

Methods: Students at 2 university campuses in Hanoi and Ho Chi Minh City, the 2 largest cities in Vietnam, were invited to participate in an anonymous online survey. Data collection was conducted during March and May 2016.

Results: There were 741 respondents, of whom nearly 90% of students (665) were motorcycle riders. Overall prevalence of mobile phone use while riding is 80.9% (95% confidence interval [CI], 77.9–83.9%) with calling having a higher level of prevalence than texting or searching for information while riding: 74% (95% CI, 70.7–77.3%) vs. 51.7% (95% CI, 47.9–55.5%) and 49.9% (95% CI, 46.1–53.7%), respectively. Random parameter ordered probit modeling results indicate that mobile phone use while riding is associated with gender, motorcycle license duration, perceived crash risk, perceived risk of mobile phone snatching, and perceptions of friends' mobile phone use while riding.

Conclusions: Mobile phone use while riding a motorcycle is highly prevalent among university students. Educational programs should focus on the crash and economic risk of all types of mobile phone use while riding, including calling, texting, and searching for information. In addition, they should consider targeting the influence of social norms and peers on mobile phone use while riding.     

The determinants of motorcyclists helmet use: Urban arterial road in Khon Kaen City,Thailand

IntroductionCurrently, Thailand incurs the highest death toll of motorcyclists in the world. The aim of this study was to explore the factors influencing helmet use of motorcyclists in Khon Kaen City, Thailand by using the Logistic regression analysis.MethodThe samples, consisting of 27,977 riders and 6,947 riding passengers, were collected by CCTV installed at several signalized intersections along urban arterial roads.ResultsThe observation results reveal that only 67% of motorcyclists wore the helmets. The analysis results reveal that the helmet use of motorcyclists was significantly associated with the riding status, number of passengers, apparent age, motorcycle class, time of day, the presence of police booths at intersections and, especially, red light running behavior. The riders tended to wear helmets at 2.7 times higher rates than passengers. Adult motorcyclists tended to wear the helmets at 2.8 times higher rates than children. The motorcyclists riding the motorcycles over 125 cc tended to wear the helmets 1.9 times higher than those riding motorcycles under 125 cc. The motorcyclists riding in the morning and the afternoon tended to wear the helmets 5.0 and 3.8 times higher than in the evening. The motorcyclists riding through intersections with police booths tended to wear the helmets 2.2 times higher than those riding through intersection without police booths. However, the red light running riders intend to wear the helmets 0.6 times less than the legal riders.ConclusionsThe outcome of this study could determine the factors influencing motorcyclist's helmet use.Practical ImplicationsIt will be useful for a development of 100% helmet use program designed to lessen the fatality of motorcyclists along the urban arterial roads.     

Motorcycle helmet use in Calicut,India: User behaviors,attitudes, and perceptions

Objectives: The objectives of this study include assessing the motorcycle helmet use pattern in Calicut, India, and analyzing the factors influencing helmet use including motorcyclists' perceptions.

Methods: Field observational studies at 15 locations were conducted to determine the helmet use rate among motorcyclists and pillion passengers. A structured questionnaire interview survey was conducted with 709 motorcyclists to evaluate the users' perceptions and opinions regarding the use of motorcycle helmets.

Results: There was a considerable difference in the level of motorcycle helmet use observed between the locations within and outside the city limits, where different levels of helmet law enforcement were exercised. The helmet use was observed at a maximum of 89% within the city and a minimum of 23% in some locations outside the city. The decreasing percentage of helmet use while moving toward the locations outside the city was confirmed statistically through t tests (t = 1.771, df = 13, P < .05). It was found that only 42% of users revealed that helmets are comfortable and 42% expressed that helmets affect hearing ability. It is important to note that 57% of users are of the opinion that there is no need to use a helmet if you drive slowly and carefully. The price of the helmet was not a deterrent for helmet use. In addition, it was observed that only 45% of helmets used by the motorist were standard helmets with an Indian Standards Institute (ISI) mark.

Conclusion: The widely varying helmet use pattern observed in the study area may be attributed due to the users' behaviors; that is, using a helmet only when the helmet law is strictly enforced rather than using a helmet as a protective device. Further, some of the problems and beliefs associated with helmet use prevent motorcyclists from using a helmet. Hence, the road safety of motorcyclists can be improved only through addressing the identified measures comprehensively.     

What is the relationship between self-reported aberrant driving behaviors,mindfulness, and self-reported crashes and infringements?

Objectives: This study investigated the relationship between self-reported aberrant driving behaviors, mindfulness, and self-reported crashes and infringements.

Methods: Three hundred and eighteen participants (M = 46.0 years, SD = 13.7 years; female: 81.8%) completed an online survey that assessed aberrant driving behaviors, mindfulness (including regular mindfulness meditation [MM]), and self-reported crashes and infringements during the past 2 years. Structural equation modeling (SEM) was used to examine the relationship between self-reported aberrant driving behaviors and mindfulness simultaneously, as well as with participants' age and estimated kilometers driven over the past year.

Results: The results of the SEM showed that mindfulness was negatively related to each self-reported aberrant driving behavior, with the strongest relationships being between mindfulness and driving-related lapses (?0.58) and errors (?0.46). Participants who practice MM had significantly fewer crashes in the past 2 years and reported significantly fewer driving-related violations and lapses compared to participants who did not practice MM (crashes: 9.3% vs. 18.8%, P < .05; violations: M = 6.66 [SD = 3.44] vs. M = 7.68 [SD = 4.53], P < .05; errors: M = 5.17 [SD = 3.44] vs. M = 6.19 [SD = 4.12], P < .05).

Conclusions: More research is needed to understand whether MM results in more mindful and attentive drivers or whether individuals who practice MM may have other traits or behaviors that are linked to improved safety.     

E-bikers’ braking behavior: Results from a naturalistic cycling study

Abstract

Objective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.

Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5?h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.

Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.

Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation.