Rider Behavior Research Articles

Estimating spatio-temporal variations of taxi ridership caused by Hurricanes Irene and Sandy: A case study of New York City

Extreme weather days were usually removed as outliers in past studies of taxi ridership. However, taxis play an important role during extreme weather events when other public transportation service is suspended. Thus, estimating spatio-temporal variations of taxi ridership during extreme weather conditions can provide valuable information on heretofore relatively unknown behavior of taxi riders and help identify areas with unusual taxi demands. In this study, New York City (NYC) taxi ridership shortly before the landfall of Hurricanes Irene and Sandy was analyzed. It was found that taxi ridership began to drop about 24 h before each hurricane made landfall. Six multisource regression models were estimated to explain the variation of taxi ridership in the last 24 h. Characteristics of the approaching hurricane, local weather conditions, and zonal socio-demographic variables were entered as explanatory variables. It was found that taxi ridership during hurricane-affected periods has a strong linear association with the ridership in unaffected periods but the proportion decreases as the storm approaches; a storm has the greatest impact on taxi ridership during weekend and at night, and the least impact on a weekday during the day; and taxi users make fewer trips during conditions of heavy rain or strong wind.

Role of ADHD in risky riding behavior: a statistical modeling

Attention Deficiency and Hyperactivity Disorder (ADHD), as a predictor of injuries in motorcyclists, affects the risky behavior. Since there was no pre-established conceptual model, this study aimed at exploring a conceptual model. Following this model, the Structural Equation Modeling (SEM) was utilized to find the predictors of Motorcycle Riding Behavior (MRB), as well as the mediators and moderators of ADHD-MRB relationship. In the current cross-sectional study, 340 motorcyclists in Bukan city, Iran, were recruited through a randomized cluster sampling. A simple conceptual model was explored and utilizing the goodness of fit indices in SEM, an optimal model was chosen. Then, utilizing 3-step hierarchical regressions and SEMs, the relationship between ADHD and MRB was assessed by modeling the possible mediators/moderators such as answering the cell phone and using the helmet. The results of hierarchical regression showed that answering the cell phone had both moderating and mediating effects on the relationship between ADHD (and the ASS subscale) with MRB. The final SEM, by introducing the mediating role of underlying variables, had a good fit on data (Normed Chi2 = < 5.0, RMSEA < 0.08, SRMR < 0.05, CFI and TLI > 0.90), wherein ADHD score (and the subscales) predicted the MRB score directly/indirectly (P < 0.05). A simple conceptual model was found to assess the mediating role of ADHD in motorcyclist risky behavior. Based upon the findings, training the techniques of and/or enforcement for controlling and improving riding behaviors and skills among ADHD motorcyclists, those who answer their cell phones while riding, un-experienced riders, and those who ride without wearing the helmet is strongly recommended.

Evaluating rider steering responses to an unexpected collision hazard using a motorcycle riding simulator

Motorcycle rider steer responses to unexpected collision emergencies have not been studied experimentally. We used a motorcycle simulator with elastic steer mechanism and modified car driving model to simulate the input-output counter steering response of two-wheeled vehicles in combination with a car pop-up paradigm from driving studies to evaluate rider responses to unexpected collision hazards. We manipulated time-to-crash – either 1 s or 1.5 s – to probe the threshold between not enough and just enough time to respond. The median response time of 570 ms was similar to previously recorded latencies for motorcycle emergency braking responses. Although median response time and steer torque did not depend on time-to-crash (TTC), the distribution and variability of response measures were increased when TTC was shorter. Riders showed improved lateral displacement toward the road centerline by the third TTC1.5 trial and were almost 8 times more likely to produce a successful virtual swerve avoidance maneuver in TTC1.5 rather than TTC1 trials. With 1.5 s to respond, riders were more consistent, with net steering inputs more congruent with the maneuvering goal compared to when they had only 1 s to respond. Comparisons of ‘safe’ versus ‘crash’ outcomes show that average response times across trials and riders are not different, but the variance in timing is lower across successful trials. We have shown than it is possible to safely study rider reactions to an emergency and observe a realistic range of steer responses to a traffic conflict using a motorcycle riding simulator. The results have relevance for the design of automatic rider assistive systems, rider behavior prediction and decision logic algorithms, PTW rider modeling and targeted training interventions.

The Relationship Between Children Education in the Family and Car Driving and Motorcycle Riding Behaviour in Indonesia

Children received their first-hand education from family environment. This paper is intended to evaluate whether children education in the family is related to car driver and motorcycle rider behaviour. Firstly, a long list of bad and good norms received from family revealed from ten respondents from various religions and ethnicities. 4 constructs (explanatory variables which are not directly observable) were found as Indonesian Family values (IFV), i.e. religious, disciplinary, ethical and politeness norms and law norms. Car driver behaviour was measured using Indonesian Driver Behaviour Questionnaire (IDBQ) consist of 4 constructs, i.e. aggressive behaviour, ordinary violation, errors, and lapses. Motorcycle rider behaviour was measured using Indonesian Motorcyle Behaviour Questionnaire (IMRBQ) consisted of 6 constructs, i.e. traffic/ control errors, speed/ safety/ traffic violations, and stunts. Pearson correlation analyses were conducted between means of each construct in IMRBQ, IDBQ and 4 constructs in IFV. Some of the constructs in IFV were significantly correlated with some constructs in MDBQ and IMRBQ.

Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy

The rapid expansion of technologies, especially Internet and mobile technologies has enabled the development of many mobile applications that facilitate travel and tourism. This study proposes and empirically tests the extended expectation-confirmation model (EECM) with two additional constructs—self-efficacy and perceived value—to explain the continued usage of on-demand ride services/ride hailing applications (ODRHA) by riders. Results strongly support the integrated model of TAM and ECM for predicting post adoption behavior of ODRHA customers. They also show that perceived value, self-efficacy and satisfaction contribute significantly to the continued usage of app-based services. The study offers valuable insights for ODRHA service providers in understanding rider behavior and following best practices to achieve higher rate of continued usage of ODRHA services through mobile applications.

Sunday Drivers, or Too Fast and Too Furious? Analyzing Speed and Rider Behaviour of E-Scooter Riders in San Jose, California (2nd Highest Scoring Masters/Undergraduate Abstract Award Sponsored by HNTB Corporation - Great Lakes Region)

Sunday Drivers, or Too Fast and Too Furious? Analyzing Speed and Rider Behaviour of E-Scooter Riders in San Jose, California (2nd Highest Scoring Masters/Undergraduate Abstract Award Sponsored by HNTB Corporation - Great Lakes Region)

College Students’ Shared Bicycle Use Behavior Based on the NL Model and Factor Analysis

The rise and rapid development of bicycle sharing brings great convenience to residents’ travel and transfer, and also has a profound impact on the travel structure of cities. As college students make up a major share of shared bicycle users, it is necessary to analyze the factors that influence their travel mode and riding frequency choice and to explore how these factors affect their riding behavior. To analyze the bicycle riding characteristics of college students, this paper processes many factors with unknown correlations by using a factor analysis method based on revealed preference (RP) questionnaire data. Then, taking the significant common factors as explanatory variables, a two-layer nested logit (NL) model combining riding frequency and travel mode is established to study college students’ riding behavior. The results suggest that the comprehensive hit rate of the upper and lower levels of the model (riding frequency and travel mode) are, respectively, 76.8% and 83.7%, and the two-layer NL model is applicable. It is also shown that environmental factors (“cheap,” “mixed traffic,” “signal lights at intersection,” and so on) have a significant impact on the choice of travel mode and riding frequency. Also, improving the level of bicycle service can increase the shift from walking to riding. Such findings are meaningful for policy-makers, planners, and others in formulating operational management strategies and policies.

Parent-adolescent bicycling safety communication and bicycling behavior

IntroductionEfforts to encourage bicycling to school have increased in the United States. However, little is known about how parent-child communication affects bicycle safety. The purpose of this study was to examine parent-child agreement on biking instructions and their correlation with the early adolescents’ real-world riding behavior. MethodsParent-child dyads were asked open-ended questions about instructions they had given/received about bicycling. Answers were then coded into nine categories (e.g., crossing the road, bicycle control/handling). Distributions of parent-child agreement on parent-given bicycle safety instructions were examined in relation to the adolescent’s real-world riding behaviors. Results36 parent-child dyads were included. Average age was 11.9 (Range: 10–15) for adolescents and 43.3 (Range: 30–59) for parents. Common parental instructions included: wear helmet, ride on sidewalk, and trip routing specifications. High ‘ride on sidewalk’ instruction (38.9% both parent and adolescent, 22.2% parent only, 16.7% adolescent only) was concerning due to potential driveway conflicts. Agreement between parents and adolescents on reported instructions was low, overall. Mean safety-relevant event rates in real-world cycling did not differ significantly between bicycle safety instruction agreement groups (both parent & adolescent reported, parent only, adolescent only, neither). The proportion of time an adolescent rode on different infrastructure types (sidewalk, street, etc.) did not vary between dyads reporting parents had given instructions to ride on the sidewalk and those who had not. ConclusionsResults highlight lack of agreement between parents and adolescents on cycling instructions the adolescent receives from the parent. Parent instructions to adolescents regarding bicycling safety were not associated with actual riding behaviors. Results suggest parent messaging to adolescents may be ineffective. Given parents are in a position of influence, results indicate a need for parental training on effective safety-related communication strategies to assist them in capitalizing on their parental role to increase their child’s safety.

Analysis on the Riding Characteristics of Mobike Sharing Bicycle in Beijing City, China

Abstract. The development of the sharing economy has provided an important realization path for urban’s green and healthy development, and has also accelerated the speed of urban development. With the constant capital pouring into the public transport field, dock-less shared bicycle is a relatively new form of transport in urban areas, and it provides a bikesharing service to fulfil urban short trips. Dock-less shared bicycle, with a characteristic of riding and stopping anywhere, has successfully solved the last mile travel problem. Recently, studies focus on the on the temporal spatial characteristics of public bicycle based on public bicycle operation data. However, there are few studies on the identification of riding patterns based on the characteristics of temporal and spatial behavior of residents. In addition, researches have been conducted on public bicycles administered by the government, and the dock-less shared bicycle have different characteristics from public bicycles in terms of scale of use and mode of use. This paper aims to analyze the temporal and spatial characteristics of residents using shared bicycles, and attempts to explore the characteristics of the riding modes of the dock-less shared bicycles.Mobike sharing bicycle dataset of Beijing city were obtained for the research and this dataset contains a wealth of attributes with cover of 396600 shared bicycle users and 485500 riding records from May 10 to May 25 in 2017. Additionally, 19 types of POI (Point of Interest) data were also obtained through the API of Baidu Maps. To examine the patterns of shared bicycle trips, these POI data are categorized into five types including residential, commercial, institution, recreation and transport. Spatiotemporal analysis method, correlation analysis methods and kernel density methods were used to analyse the temporal and spatial characteristics of shared bicycle trips, revealing the time curve and spatial hotspot distribution area of shared bikes. Furthermore, a new matrix of riding pattern based on POI was proposed to identify the riding patterns during massive sharing bicycle dataset.This paper aims to explore the riding behaviour of shared bicycles, and the research results are as follows:(1) Temporal characteristics of riding behaviourThe use of the Mobike bicycles is significantly different on weekdays and weekends (Figure1). Figure 2 clearly shows a morning peak (7–9 h) and evening peak (17–19 h), corresponding with typical commute time. At noon, some users' dining activities triggered a certain close-distance riding behavior, which formed a noon peak. Different from the riding characteristics of the working days, there are many recreational and leisure riding behaviors on the weekends. The distribution of riding time is more balanced, and there is no obvious morning and evening peak phenomenon.(2) Spatial characteristics of riding behavior The spatial distribution of riding behaviour varies with different roads (Figure 2) and people prefer to choose trunk roads for cycling trips. Spatial hotpot detecting method based on the kernel density is applied to identify the active degree of bike sharing trip during a whole weekday (Figure 3). The red colour represents a high active degree and the green and blue colour means the low degree. Note that almost no riding occurred in the early hours of the morning and late at night. The characteristics of three riding peaks are obvious in the figure. A large number of travels occurred in Second Ring to Fourth Ring Road, and some travel activities were concentrated near traffic sites.(3) Patterns of riding behavior Different riding patterns happens in different space and change over the time at two scales of day and hour. During morning peak and evening peak on weekdays, more than 60 percent of riding trips are corresponding with typical commuting activities. The observed commuting pattern of morning peak (Figure 4(a) and (b)) implies that the majority of shared bicycle trips might relate to home, transports, commercial area and some institution. For example, students choose shared bicycles to do some school activities, people prefer to use shared bicycles as a connection tool to bus station and metro stops and people handle daily affairs in some government agencies. However, a large part of the shared bicycle trips on weekends shows the characteristics of non-commuting riding pattern, which means more leisure activities take place at weekends (Figure 4(c) and (d)). Non-commuting pattern of riding behavior mainly occurs among residential areas, metro stops, bus stations and recreational facilities, such as parks, playgrounds, etc.

Risk Riding Behaviors of Urban E-Bikes: A Literature Review.

In order to clearly understand the risky riding behaviors of electric bicycles (e-bikes) and analyze the riding characteristics, we review the research results of the e-bike risky riding behavior from three aspects: the characteristics and causes of e-bike accidents, the characteristics of users’ traffic behavior, and the prevention and intervention of traffic accidents. The analysis results show that the existing research methods on risky riding behavior of e-bikes mainly involve questionnaire survey methods, structural equation models, and binary probability models. The illegal occupation of motor vehicle lanes, over-speed cycling, red-light running, and illegal manned and reverse cycling are the main risky riding behaviors seen with e-bikes. Due to the difference in physiological and psychological characteristics such as gender, age, audiovisual ability, responsiveness, patience when waiting for a red light, congregation, etc., there are differences in risky cycling behaviors of different users. Accident prevention measures, such as uniform registration of licenses, the implementation of quasi-drive systems, improvements of the riding environment, enhancements of safety awareness and training, are considered effective measures for preventing e-bike accidents and protecting the traffic safety of users. Finally, in view of the shortcomings of the current research, the authors point out three research directions that can be further explored in the future. The strong association rules between risky riding behavior and traffic accidents should be explored using big data analysis. The relationships between risk awareness, risky cycling, and traffic accidents should be studied using the scales of risk perception, risk attitude, and risk tolerance. In a variety of complex mixed scenes, the risk degree, coupling characteristics, interventions, and the coupling effects of various combination intervention measures of e-bike riding behaviors should be researched using coupling theory in the future.

Unsafe riding behaviors of shared-bicycle riders in urban China: A retrospective survey

Shared-bicycle use has skyrocketed in urban China, but little is known about the safety of bicycle users. The Chinese popular media reports multiple risky riding behaviors among shared bicycle riders, but scientific research on the topic is lacking. Therefore, we conducted a retrospective WeChat-based online survey to examine how often shared bicycle riders report engaging in risky cycling behaviors in urban China. Eight unsafe shared bicycle riding behaviors were assessed: not wearing helmets, running red lights, cycling against the traffic flow, riding in lanes designed for motor vehicles, riding in lanes designed for pedestrians, carrying passengers on bicycles, using cell phones while riding, and eating while riding. In total, 1960 valid questionnaires were collected. The proportion of participants who reported always or often having unsafe riding behavior in the past month, ranged from 1.1% for carrying passengers on the bicycles to 97.6% for failing to wear a helmet. Demographic characteristics were associated with unsafe behaviors through multivariate logistic regression, with male riders and riders aged 25 years or younger more likely to ride while using cell phones than females (AOR = 2.94) and those 36 years or older (AOR = 3.57). Cyclists with undergraduate education were more likely to wear helmets than those with postgraduate education or higher (AOR = 0.21). Compared to riders from central municipalities governed directly by the central government, riders from provincial capitals, deputy provincial cities, and smaller cities were at higher risks of riding in lanes for pedestrians, respectively (AOR = 1.59, 2.82 and 1.61). Riders who rode over 5 h a week and who rode on weekends were more likely to carry passengers than those who rode less than 1 h a week (AOR = 4.72) and those who rode only on weekdays (AOR = 3.93). We conclude that shared-bicycle riders frequently engage in some unsafe riding behaviors in urban China. Younger age, lower level of education, and longer hours of riding each week are associated with greater risks of some unsafe riding behaviors. Shared bicycles offer substantial benefit to societal health and transportation, but evidence-based interventions should be considered to reduce risks from unsafe shared bicycle riding behaviors. A well-designed road infrastructure with dedicated on-road bicycle lanes and readily-accessible comfortable, low-cost, and safe helmets may also reduce unsafe riding behaviors and unwanted crashes and injuries for shared bicycle riders.

Investigating the Strategies for Reducing Motorcycle Mode Choice in Urban Trips: Case Study of Tehran City

Motorcycles in Iran, especially in metropolises such as Tehran, are used extensively for various reasons such as low maintenance costs, high maneuverability, and the possibility of entering congestion priced zones without paying a toll. Nevertheless, motorcycles are involved in 25% of accidents and produce almost 30% of air and 50% of noise pollution in Tehran. Current research aims to investigate possible scenarios for reducing the use of motorcycles in Tehran’s traffic and transportation master plan strategies. After designing the scenarios, a stated preference method is used for gathering the required data from various groups of motorcycle riders in Tehran. More than 2,000 questionnaires were completed of which 1,766 were deemed acceptable for data entering and further analysis. Increasing the price of motorcycle maintenance and charging motorcycles to enter the congestion priced zone of Tehran (CPZT) were two main scenarios which were considered in this research. Multinomial and nested logit models were applied to analyze the trip choice behavior of motorcycle riders who had participated in the survey. Results indicated that strategies such as increasing motorcycle maintenance costs could be effective in reducing the use of motorcycles. For instance, increasing motorcycle maintenance costs by 4.7 times and imposing a 70,000 IRR toll price to enter the CP zone resulted in a 66% reduction in motorcycle mode choice by motorcycle riders.

Crash Involvement and Risky Riding Behaviors among Delivery Riders in China: The Role of Working Conditions

Delivery riders (usually e-bike riders employed in the delivery industry), an emerging occupation as a result of the booming of online commerce in China, have attracted social controversies for the prevalence of unsafe riding and high rates of crash involvement. Given their ever-increasing number and stressful working conditions, more attention should be paid to safety issues involving delivery riders. To illuminate the role of working conditions in influencing safety-related risks of delivery riders, this cross-sectional study was conducted among 824 delivery riders, who answered a self-administered questionnaire gathering information about their demographics, working conditions, riding behaviors, and crash involvement. A mixed probit model of the number of crashes involving riders that allowed for hierarchical relationships between the latent variables identified (i.e., time pressure, fatigue, risky riding behaviors) was employed to determine the underlying association between factors surveyed. The results portrayed a picture of worrisome working conditions for delivery riders. Respondents reported an average of 9.1 daily working hours with insufficient rest. Frequent stair climbing, route planning, and disputes with customers also added to their physical and mental workload. The tested model indicated that a heavy workload, feelings of fatigue, as well as risk-taking behaviors all exerted direct and significant impacts on the involvement in crashes, and time pressure as well as several work-related traits affected crash involvement indirectly, through influencing riders’ feeling of fatigue and riding behaviors. Findings of this study may provide an empirical basis for road safety interventions for delivery riders in China.

Analysis of risk-taking behaviors of electric bicycle riders in response to pedestrian countdown signal devices

Objective: The primary objective of this study is to understand electric bicycle riders’ responses to pedestrian countdown signal devices (PCSDs), in particular, red light violations (RLVs) and early start behaviors.Methods: Descriptive analyses were performed to compare the frequency of electric bicycle riders’ risk-taking behaviors, including RLVs and early start maneuvers at signalized intersections with PCSDs and intersections without PCSDs. Binary logit models were deployed to evaluate the influence of the associated factors, including gender, presence of a pillion passenger, type of electric bicycle, and number of turning vehicles, on the RLV behaviors and early start maneuvers of electric bicycle riders at signalized intersections with PCSDs.Results: Descriptive analyses indicate that PCSDs are effective in reducing the number of red light running violations. Significant variables for RLV behaviors include being female, no pillion passengers, type of electric bicycle, and number of turning vehicles. In addition, a similar correlation between early start maneuvers and influential factors was observed.Conclusions: PCSDs are effective in preventing RLVs but increase the probability of early starts. Based on the findings in this article, practical countermeasures such as redesigning PCSDs could help improve safety at intersections for electric bicycle riders and should be further investigated.

Design and hardware selection for a bicycle simulator

Abstract. With the resurgence in bicycle ridership in the last decade and the continuous increase of electric bicycles in the streets a better understanding of bicycle rider behaviour is imperative to improve bicycle safety. Unfortunately, these studies are dangerous for the rider, given that the bicycle is a laterally unstable vehicle and most of the time in need for rider balance control. Moreover, the bicycle rider is very vulnerable and not easily protected against impact injuries. A bicycle simulator, on which the rider can balance and manoeuvre a bicycle within a simulated environment and interact with other simulated road users, would solve most of these issues. In this paper, we present a description of a recently build bicycle simulator at TU Delft, were mechanical and mechatronics aspects are discussed in detail.

Analyzing the influence of age groups of motorcycle riders on traffic violations and accidents in small city using a structural equation model

Over the last three years, there has been a tremendous increase in the amount of road accidents in Mataram City-Lombok with majority of the victims being motorcycle riders between the ages of 16-40 years. The age difference may have an impact on the rider’s behavior which in turn leads to road accidents. This study aims at investigating the influence of age groups on motorcycle riders resulting to traffic violations and road accidents in Mataram City. Data was collected using questionnaire survey for which 600 respondents participated covering 6 sub-districts in Mataram City. A Structural Equation Modeling (SEM) using AMOS V.22.0 was constructed to analyze the motorcycle rider behavior. The developed model was made up of behavioral, violation and accident latent variables, with four variables of behavior, three variables of violation, and two observed variables of accident. Three age groups were used in this study with three categories consists of 15-24 years, 25-44 years, and 45-64 years old. This study found that these riders behaviors varied significantly with regards to traffic violations. The age groups of riders between 15-24 years and 45-64 years has a 65% influence on traffic violation compared to those between the ages of 25-44 years. Traffic violations with regards to road accidents was however, found to be less significant for all age group. Traffic violations committed by riders between ages of 45-64 years were found to be 14% less than those between the ages of 15-44 years. The analysis obtained from the data indicates that there are differences among the three listed age groups.

Factors associated with Motorcyclist risky riding behaviors in southern Iran

Background: Motorcyclist’s behavior has significant relationship with increased accidents mortality rate among them. Determining the risky behaviors of motorcycle drivers is essential for preventing riders and other community members from accident risks. The aim of this study was to determine the risky driving behaviors of motorcyclists in Fars province of Iran in 2017. Methods: In this cross sectional study was done in 2017 total number of 1195 motorcyclist from Fars province were included. In this study we collected the data using the Persian version of Motorcycle riding behavior questionnaire (MRBQ) was used to study the risky behaviors of motorcycle riders while riding and a checklist designed by the researchers for demographic variables. SPSS 22 was used to analyze the data. Results: All participants were male and the mean age was 28.28±8.56 years. The mean score of MRBQ was 53.54±23.44. The mean score of MRBQ was higher among the motorcyclists with the history of accident in the past year, those who had more pleasure while driving motorcycle, those who used alcohol or substance two hours before driving, those who used more powerful motorcycle, drivers with lower education level, and those with higher usage of motorcycle (P<0.001). Conclusion: Finding of this study indicated that motorcyclists with the higher score of MRBQ are at the higher risk of traffic accidents. Therefore, designing and implementing appropriate training programs before giving driving license could improve knowledge and attitude of drivers toward the risky driving behavior.

Evaluating the relationship between adult attention-deficit/hyperactivity disorder and riding behavior of motorcyclists.

:Background:Motorcycling is one of the main causes of injury, and motorcyclists are vulnerable to road traffic injuries. Attention Deficit Hyperactivity Disorder (ADHD) in adults is presumably one of the determinants of road traffic injuries and motorcyclists’ risky behavior. Despite the few studies on the relationship between motorcycle injuries and adult ADHD, their association has not been investigated using standardized instruments. This study aimed to analyze the relationship between motorcyclists’ adult ADHD and risky riding behaviors.Methods:This community-based, cross-sectional study was performed on 340 motorcyclists in Bukan city, west Azerbaijan province, Iran in 2015 and 2016 using a cluster-random sampling in seven areas of the city. According to the city map used by Bukan’s Health Centers, the city was divided into 14 clusters. Then, seven clusters (out of 14) were selected randomly. To reach the anticipated sample size, the data were collected from these seven clusters. In this study, the data collection instruments were: standard Motorcycle Rider Behavior Questionnaire (MRBQ), Conners' Adult ADHD Rating Scales (CAARS) questionnaire and a checklist designed by the researchers. The Stata 13 software package was used to analyze the collected data. Pearson correlation coefficient and multiple linear regression were performed to study the linear relationship between ADHD screening and MRBQ scores.Results:All 340 participants were male and the mean age was 30.2 years (SD=9.1). In addition, 22.1% of motorcyclists had a history of motorcycle crash. Bivariate analysis showed a significant association between risky riding behaviors and age, motorcycling records, and mean of riding hours per day (P-value less than 0.05). Multivariate analysis confirmed the correlation between ADHD and risky riding behaviors in all subscales (A, B, D) (p less than 0.05).Conclusions:Those with a high ADHD screening score are more likely to have risky riding behaviors.

Quad Bike Riders’ Attitudes toward and Use of Safety Technologies

Worldwide, the number of quad bike-related injuries and fatalities has increased over the last 30 years and, although quad bike safety has become increasingly important over the last decade, greater understanding of the risks associated with these vehicles is required. This study aimed to improve understanding of the interrelationships between risk perception, risk management, and the use of safety technologies in quad bike operation. A total of 70 quad bike riders were interviewed in two sets of interviews: one targeting riders visiting two forestry fairs, and the other targeting riders with quad bikes equipped with ROPS. The interviews showed that the quad bike riders had a tendency for externalization of risk. This result possibly derives from the articulation and allocation of blame; the majority of respondents saw the problem of quad bike safety as a result of faulty rider behavior, thus shifting focus away from the technology as well as from themselves. This also applies to many of the interviewed ROPS owners, as one of their prime motivators in acquiring ROPS was to improve the safety of others rather than their own safety.

Risky riders: A comparison of personality theories on motorcyclist riding behaviour

ObjectiveFew studies have investigated the association between broad personality traits and motorcycle rider behaviours. Typically, studies have focused on specific variables such as Sensation Seeking and Aggression. This study extends the literature by investigating the trait facets of the Big Five and the Reinforcement Sensitivity Theory (RST). MethodAn internet-based questionnaire comprised of traditional (Sensation Seeking, Aggression) and novel (Big Five, Reinforcement Sensitivity Theory) personality scales, and the Motorcycle Rider Behaviour Questionnaire (MRBQ) were posted on various motorcycle internet forums. ResultsA North American sample of 550 motorcyclists completed the survey. Four separate hierarchical regression analyses were conducted with each personality theory entered step-by-step to predict the four riding behaviours from the MRBQ (errors, speeding, stunts, protective gear use) as the criterion variables. Consistent with previous literature the traditionally used personality traits, Sensation Seeking, and Aggression, were strongly associated with riding errors, speeding, and especially performing stunts. The addition of the Big Five facets contributed negligibly to riding behaviours with the greatest explained variance accounting for errors. The addition of the Reinforcement Sensitivity Theory was especially useful in accounting for motorcycle riding errors, and the use of protective gear. ConclusionAlthough research on personality theories and riding behaviour typically use more narrow trait scales this study demonstrates that physiologically-based, broader, measures such as the Reinforcement Sensitivity Theory have a strong association with riding behaviours. Future research would benefit from the inclusion of such measures.