Rider Behavior Research Articles

Understanding and Factors of Safety Riding Behavior Among Students

Safety ridingis one method to provide knowledge and broaden horizons for teenagers who often ignore good driving behavior.Bali International University is one of the private campuses in Baliwhich has students passing by on motorbikes every day. The initial survey found that students who came to campus behaved unsafely when driving and it was found that students did not understand safety riding and there were students who did not have a driving license (SIM). The aim of this research was to carry out this research. Efforts can be made to prevent accidents while driving. The method used is quantitative research with a cross-sectional observational analytical method. The sample is students at UNBI who can drive two-wheeled vehicles and a total of 165 respondents were obtained. The results of this research are between knowledge and safe riding. isthat there is no relationship pvalue 0.455, namely > 0.05, behavior and safety riding have a significant relationship pvalue 0.03, namely <0.05, ownership of a SIM C and safety riding have a significant relationship pvalue 0.003, namely <0.05. Safety Riding It can be an understanding for students to continue driving safely by having a SIM C, knowing the applicable regulations to minimize the risk of accidents and the campus can provide

Assessing the Self-Report Instruments of Younger Versus Older Riders Involved in Near-Miss Motorcycle Incidents

Road accidents pose severe and pervasive consequences, especially in low- and middle-income countries (LMICs), where both the population and fatal accidents among youth and the elderly are steadily increasing. Therefore, this study aims to develop a model for risky behavior in near-miss incidents among motorcycle riders in Thailand. It intends to compare models between younger and older riders utilizing structural equation modeling (SEM) with a multi-group approach. The data were examined employing modified instruments derived from the Motorcycle Rider Behavior Questionnaire (MRBQ). Samples depicting risky riding behavior were obtained from both younger and older rider groups. Parameter invariance testing revealed differences between the two groups. Control errors notably emerged as the predominant factor contributing to near-miss incidents for both age groups. Speeding was identified as the primary concern for the younger group, while adverse weather conditions were deemed crucial for the older group. Based on this study, policy recommendations endorse the creation of targeted training programs for novice riders, emphasizing adherence to legal speed limits and the adoption of safe riding practices. Additionally, the study underscores the importance of preparing riders, especially those in the older age group, for adverse weather conditions. Doi: 10.28991/CEJ-2024-010-02-019 Full Text: PDF

Factors Predicting Safe Motorcyclist Riding Behaviors among Thai Undergraduates

Background Despite the nationwide enforcement strategies in place to prevent road accidents, including wearing a helmet, not riding a motorcycle while drunk, using a safe motorcycle, obtaining a motorcycle license and avoiding speeding, accidents still occur, particularly among young motorcyclists. Objectives The study aimed to describe the level of behaviors and factors affecting safe motorcyclists' riding behaviors. Methods The cross-sectional study with single-stage cluster sampling was conducted to select 326 students in years 1–4 of the 1st semester of every faculty at Phranakhon Si Ayutthaya Rajabhat University. Data were collected using online self-administered questionnaires from December 2022 to January 2023. Descriptive and inferential statistics, including the Chi-square test, Pearson correlation coefficient and Stepwise multiple regression analysis, were used to analyze the data. Results Most respondents had safe motorcyclist riding behaviors at a safe level (54.6%), good knowledge-related traffic rules (41.1%), a positive attitude towards behaviors (67.8%) and a high level of support from influencing groups as subjective norms on behaviors including family members (69.6%), friends (58.3%) and favorite celebrities who participated in a road safety campaign (48.4%). Most had high perceived behavioral control (53.1%) and behavioral intention (64.7%). Eight factors were significantly associated with safe motorcyclist riding behaviors: student’s year, having a motorcycle driving license, driving a motorcycle after alcohol drinking, attitude towards behaviors, subjective norms concerning behaviors, perceived behavioral control, and behavioral intention. Based on the results, four factors could significantly predict safe motorcyclist riding behaviors up to 45.6% (Nagelkerke R2 = 0.456, p <0.001) composed of perceived behavioral control, having a motorcycle driving license, behavioral intention and subjective norm influenced by friends. Conclusion The study could provide valuable input for institutional administrators and related organizations to formulate policies promoting safe riding behaviors among motorcyclist students. Additionally, these results may be beneficial in organizing awareness-raising campaigns to prevent motorcycle-related accidents and monitor the process of acquiring a motorcycle driving license.

Road safety attitude and behaviour among motorcycle riders in Ghana: A focus on traffic locus of control and health belief.

Road traffic accident is a leading cause of death and various life deformities worldwide. This burden is even higher among motorcycle riders in lower-to-middle-income countries. Despite the various interventions made to address the menace, the fatalities continue to be on the ascendency. One major area that has received little attention is the attitude and behaviour of motorcycle riders. The present study aimed to examine the contribution of traffic Locus of Control (LoC) and health belief on road safety attitude and behaviour. 317 motorcycle riders participated in the study. The participants completed a questionnaire comprising various sections such as motorcycle riding behaviour, road safety attitude, risk perception, the intention to use helmets, and traffic LoC. The results showed a significant positive correlation between road safety attitude and behaviour (r (295) = .33, p < .001). Drifting towards internal LoC was associated with more positive behaviour on the roads (r (295) = -.23, p < .001). Intention to use helmet, health motivation, perceived susceptibility, perceived benefits, and perceived barriers were the factors in the health belief model that were associated with road safety attitude (r (295) = .404, p < .001). Finally, the multiple linear regression model showed that road safety attitude and traffic LoC made significant contributions to road user behaviour [F(3, 293) = 13.73, p < .001]. These findings have important implications towards shaping responsible behaviour among motorcycle riders.

Risk Factors associated with Stress-related Riding Behavior among Indonesian Motorcyclists

The risk of road accidents is influenced by various elements, particularly human factor. In Indonesia, motorcycles contribute significantly to accidents due to insufficient knowledge of traffic laws and a lack of awareness about safe riding practices. Stress-related riding behavior, which may lead to this incident, is closely linked to driving discipline. Therefore, this study aimed to examine stress-related behavior as the risk factor in road accidents among motorcyclists. To achieve this, a self-reported questionnaire was distributed to 300 motorcyclists in Banda Aceh City and surrounding areas in Aceh Province. Factor analysis was used to simplify the number of indicators included, after which they were prioritized in order of importance. The results showed the most influential indicators out of the 26 considered in this study. A total of 3 underlying factor were identified, comprising anxious riding, aggressive riding, and anger. By addressing the risk factor associated with stress-related riding behavior, road safety in Indonesia was enhanced.

PERILAKU BERKENDARA SEPEDA MOTOR 150 CC MENGGUNAKAN METODE NATURALISTIC DRIVING STUDY DAN DRIVERS BEHAVIOUR QUESTIONNAIRE

Driver behavior is the most dominant factor in accidents. Almost all accidents are preceded by violations of traffic signs. Through previous accident data, important and useful information can be known. The study aims to analyze two-wheeled motorbike riding behavior using Naturalistic Driving Study (NDS) and determine the influence of age and behavior of 150cc motorbike riders. Data taken from recordings taken by respondents and questionnaires. The results of the regression test to determine differences in age on motorbike rider behavior with a constant value of a = 196.03 show that this figure is a constant number which means that, if it does not involve age (X), the value of riding behavior (Y) is -5, 3956x. The regression coefficient is -5.3945. This figure is minus (-), which means that age (X) has a negative effect on driving behavior (Y).

Identifying Factors Causing Motorcycle Crashes Among Young Adults in India Using Modified Motorcycle Rider Behavior Questionnaire

Identifying Factors Causing Motorcycle Crashes Among Young Adults in India Using Modified Motorcycle Rider Behavior Questionnaire

Analysis of factors influencing aberrant riding behavior of food delivery riders: A perspective on safety attitude and risk perception

This study aims to find the influences of safety knowledge on food delivery riders’ aberrant riding behaviors and to discover the involvement of safety attitudes and risk perceptions in the influence process. The popularity of e-bikes and the development of the food delivery industry have jointly contributed to the growth of the population of food delivery riders, and the aberrant riding behavior of food delivery riders has become a social issue. In this study, the relationship between safety knowledge level and different aberrant riding behaviors was investigated along with the mediation effects of safety attitudes and risk perceptions. In total, 435 questionnaires were collected in a small city in China. Three factors of aberrant riding behaviors and five other factors were obtained through factor analysis, and the path coefficients between the factors were analyzed through structural equation modeling. Food delivery riders’ high self-evaluation of their safety knowledge was found to be significantly associated with their fewer aberrant riding behaviors, which were mediated by their higher risk severity perceptions and better attitudes toward laws, with general violations of traffic rules being the most strongly associated. In addition, particular findings were found on food delivery riders’ risk perception of possibility and influence paths to their distraction and mistakes. These results encourage the mitigation of aberrant riding behaviors among delivery riders through road safety education. They also provide theoretical support for road safety administrators and delivery platform companies to initiate driver safety training.

An E-scooter route assignment framework to improve user safety, comfort and compliance with city rules and regulations

The rapid expansion of dockless shared micromobility systems, particularly dockless e-scooters, presents major opportunities along with challenges that have led some cities to ban these services within their jurisdiction. The safe reintroduction of dockless shared micromobility services requires support through enhancement of e-scooter service implementation, improvement of rider behavior, and enforcement of rules and regulations. This paper develops the micromobility guidance tool (MGT) that guides a shared micromobility user going from a defined origin to a defined destination to a route that meets multiple criteria, including safety, comfort, and compliance. Thus, this tool emphasizes two network features, the type of infrastructure and the condition of infrastructure. Moreover, the tool locates shared micromobility parking that is closest to a user’s destination and sends alerts to avoid prohibited infrastructure types. For each trip, the proposed tool uses a shortest path routing algorithm to assign its route and the Euclidean distance to assign closest parking. A generalized cost function was developed to estimate the time needed to cross a link while considering e-scooter accessibility, user routing preferences, and ordinance restrictions. The effectiveness of MGT was tested through a case study of tens of thousands of dockless shared e-scooter trips within the City of Dallas, TX. As a validation step, several experiments were carried out to examine the developed tool under various scenarios. Routes generated by MGT were compared to actual routes taken by users and to scenarios corresponding to models previously published in the literature. When compared to actual routes taken by riders, case-study findings showed a notable increase in the use of preferred types of infrastructure (bike lanes, sidewalks, one-way roads, etc.), the use of bike infrastructure (bike lanes and bike trails), and the use of better conditions (i.e., less deficient infrastructure). Additionally, a marked reduction in regulatory violations was exhibited. The methodological approach presented here could be generalized to any city network or shared micromobility system. The proposed tool could be required by cities and adopted by shared micromobility providers seeking to improve rider safety, comfort, and compliance. This tool could be integrated into the provider application guiding the user to micromobility-friendly routes and designated parking, a feature not yet available to micromobility users. Finally, this paper has offered policy recommendations and guidance for practice, where the reintroduction of shared e-scooters is being considered by cities and expansion considered in new markets.

Analyzing Near-Miss Incidents and Risky Riding Behavior in Thailand: A Comparative Study of Urban and Rural Areas

Preventing near-miss incidents is considered a proactive measure, as it aims to prevent events that have a risk of resulting in accidents. This is regarded as a vital component of building a sustainable and secure society within communities. In the present day, low- and middle-income countries (LMICs) often experience the highest fatality rates from motorcycle accidents, which frequently involve mixed traffic scenarios with other vehicles. The distinct physical characteristics and environmental conditions of roads in urban and rural areas significantly contribute to different riding behaviors. Therefore, the objective of this study is to develop a behavioral model related to near-miss incidents among motorcycle riders in both urban and rural regions using multi-group structural equation modeling (SEM). Data collected from six Thai regions via adapted MRBQ assessed control errors, violations, and safety equipment use in a sample of 2002 riders (1066 urban, 936 rural). Through parameter invariance testing, differences in factor loadings, intercepts, and structural paths were identified between urban and rural areas. All three of these factors significantly influenced near-miss incidents among motorcycle riders in both urban and rural areas. The policy recommendations resulting from this study can contribute to enhancing safety measures for motorcycle riders.

Personality Traits Affecting Risky Riding Behavior: An Application of an Extended Theory of Planned Behavior

The primary objective of this study is to investigate the influence of personality traits such as anxiety, sensation seeking, altruism, anger, and normlessness on young powered two-wheeler riders’ risky riding behavior. The theory of planned behavior (TPB) is extended to include personality traits forming an extended TPB (ETPB). The ETPB model is used to examine how personality traits directly influence risky riding behavior and indirectly influence risky riding behavior through latent mediating factors. The secondary objective is to examine the differences in interactions between personality traits, mediating factors, and risky riding behaviors of those who have been and have not been involved in traffic accidents. The study sample included 535 high school students in Phu Yen, Vietnam. The results showed that personality traits, directly and indirectly, influence risky riding behaviors through the mediating construct. Young riders with sensation-seeking, anger, and normlessness have a higher frequency of risky riding behavior than those with anxiety and altruistic personality traits. Sensation seeking, anger, and normlessness indirectly influence risky riding behavior through risk perception and subjective norms. In addition, the results also show a clear difference in the relationship between the personality and behavior of people who have been involved in traffic accidents and those who have never been involved in accidents.

Exploration of Riding Behaviors of Food Delivery Riders: A Naturalistic Cycling Study in Changsha, China

Aimed at the riding safety issue of food delivery riders in China who mainly travel by electric bikes, a naturalistic cycling study was conducted by collecting the naturalistic cycling data of dozens of food delivery riders in Changsha, China, to identify their riding characteristics. It was found that the participating food delivery riders are mainly undereducated young male adults, and the primary reason for them to take the job is the flexible working hours. Furthermore, they frequently work overtime and admit to often committing risky riding behaviors to deliver food on time. The analysis of their riding trajectories indicates that they delivered orders all day long, rather than just at mealtimes. They mainly work within 3 km of the delivery station, and the average riding radius was 2.39 km. Male riders, riders working less than one year, and riders with high school education had a relatively fast riding speed. These findings provide valuable new insights for agencies to understand the riding characteristics of food delivery riders and to formulate the appropriate countermeasures to improve their occupational safety.

E-scooters: Still the new kid on the transport block. Assessing e-scooter legislation knowledge and illegal riding behaviour

The use of e-scooters is rapidly increasing in cities, leading to their integration into the transportation system. However, numerous collisions involving e-scooters, including some resulting in fatalities, have been reported since their introduction. These incidents indicate that the potential dangers posed by e-scooters may be underestimated. Research suggests that a significant factor contributing to these collisions is the prevalence of illegal riding behaviour exhibited by many riders. This paper presents three studies that aimed to assess the understanding of e-scooter riders and non-riders of the current legislation across various riding scenarios and link it to their profile, riding habits, and their proneness to engage in illegal riding behaviours. Study 1 utilised questionnaires to survey participants and gather information about their profiles and self-reported illegal riding behaviour. Study 2 focused on assessing participants' knowledge of the current e-scooter legislation through different everyday riding scenarios. Study 3 featured short video clips from the rider’s perspective to determine the proneness of participants to engage in illegal riding behaviour and explore the potential relationship between these behaviours and their understanding of e-scooter rules. The findings revealed that e-scooter riders were generally younger and exhibited a higher propensity for engaging in illegal riding behaviour than non-users. Both groups demonstrated limited knowledge regarding various aspects of the current e-scooter legislation, particularly related to parking, speeding, and designated infrastructure. While e-scooter riders demonstrated relatively greater knowledge of the e-scooter rules, this was not consistently observed across all areas, particularly in relation to riding on pavements (pedestrian footpaths). Furthermore, Study 3 revealed that participants with better knowledge of the current legislation were less likely to engage in illegal riding behaviour. These findings suggest a need for targeted interventions and educational campaigns to improve riders' understanding of regulations and promote safer riding practices. Implementing training programs for e-scooter safety could significantly enhance riders’ awareness of the associated dangers, fostering responsible e-scooter use.

Assessing Significant Factors Affecting Risky Riding Behaviors of Vietnamese Motorcyclists Using a Contextual Mediated Model

This study explores the significant factors affecting risky riding behaviors of Vietnamese motorcyclists using a contextual mediated model (CMM) in Hanoi, the capital of Vietnam, where motorcycle crashes are prevalent. The affecting factors include personality traits, riding self-confidence, riding attitude, and risk perception. Personality traits and riding self-confidence are distal factors of CMM that affect risky riding behaviors. On the other hand, riding attitude and risk perception are proximal factors in CMM. A survey was conducted to collect information on motorcyclists’ risky riding behaviors related to the four factors mentioned through a self-reported questionnaire. Statistical Package Social Science (SPSS) and structural equation modeling (SEM) with analysis of moment structures (AMOS) are used to determine the effects of the factors on risky riding behaviors. The results discovered that riding attitude and risk perception were the intermediate variables of personality trait and riding self-confidence affecting the risky riding behaviors, and personality trait and riding self-confidence also affected the risky riding behaviors directly. Findings in the model also show that riding attitude was perceived to play a significant role in increasing risky driving behavior. The recommendation is to increase the safety education programs that reduce risky driving behavior.

Understanding the behaviour of motorcycle riders: An objective investigation of riding style and capability

Human errors are the primary cause of powered two-wheeler crashes worldwide due to the demanding control required and the often ineffective rider-training programs. Literature on rider behaviour is limited, partly due to the lack of standard investigation methodologies.This work investigated the differences in riding style and capability of a diverse set of riders. It explored the impact of familiarisation and riding instruction through objective metrics. Correlation with experience was a particular focus.Seven riders of various experience levels performed trials on an instrumented motorcycle, following three riding instructions: ‘Free Riding’, ‘Handlebar Riding’, and ‘Body Riding’. Objective metrics assessed rider familiarisation, capability and willingness to excite motorcycle dynamics, riding style, and input preference.Results indicated that riders asymptotically converged to their motorcycle dynamics intensity level after a specific distance; both intensity and distance were positively correlated with experience. Experienced riders achieved higher longitudinal acceleration and utilised combined dynamics to a higher degree. The negative longitudinal jerk during braking varied greatly among riders and correlated with experience. A clustering approach identified two prominent trial groups concerning the motorcycle response intensity. Higher diversity emerged in the inputs, leading to five clusters with distinct riding style meanings. Instructions influenced behaviour, particularly regarding input usage.The unsupervised approach and metrics proposed should make rider behaviour research more straightforward and objective. It could be applied to naturalistic riding sessions for more conclusive evidence of inter-driver differences. The diversity that emerged concerning the command inputs used warrants a revision of training practices to promote riding safety.

Utilizing MRBQ to investigate risky rider behavior in Chinese young riders: combining the effect of Big Five personality and sensation seeking

The motorcycle rider behavior questionnaire (MRBQ) is one of the most extensively used questionnaires to explore risky rider behavior worldwide. However, whether previous research adopted other scales or other versions of MRBQ, neither of them fully cover the typicality of the risky behavior in Chinese motorcyclists. Moreover, past research investigated the MRBQ while combining the joint effect of Big Five personality (BFP) and sensation seeking lacks. Our study aims to revise the Chinese version of MRBQ in young riders and explore the relationship among BFP, sensation seeking, MRBQ, and self-reported traffic violations. 278 online participants filled out the Big Five Inventory measuring BFP, the sensation seeking scale, MRBQ items selected from previous versions in other countries, and self-reported traffic violations from the traffic management system (crashes, traffic violation frequency, penalty points, and fines). Exploratory factor analysis suggested 7 factors (safety equipment, traffic errors, speed violations, control errors, stunts, traffic violations, and safety violations), and the internal consistency reliability ranged from 0.58–0.91. The hierarchical linear regression analysis showed that agreeableness and conscientiousness in BFP negatively predicted the total MRBQ score, while openness in BFP and sensation seeking positively predicted the total MRBQ score. In addition, the Poisson regression analysis suggested that all kinds of self-reported traffic violations could be positively predicted by the total MRBQ score. Path analysis suggested the fully mediating role of sensation seeking. In conclusion, the Chinese version of the MRBQ is useful for future studies and the sensation seeking plays a mediating role between the Big Five personality and MRBQ.

Exploring User Experience in Sustainable Transport with Explainable AI Methods Applied to E-Bikes

Sustainable modes of transport are being promoted to achieve global climate goals. The perceived user experience is decisive for the choice of transport mode. To increase the share of sustainable transport in total traffic, the user experience is placed into the spotlight, raising the need for appropriate exploration methods. Machine learning (ML) techniques have become increasingly popular in the transport domain, but the black-box nature of ML models poses significant challenges in interpreting the relationship between model input and output. Explainable AI methods (XAI) can fill this gap by providing post hoc interpretation methods for black-box models. The aim of the present work was therefore to assess the potential of XAI to explore user experience in transport. The introduced method was based on a popular XAI method named SHAP (SHapley Additive exPlanations). Applied to the use case of e-bikes, we aimed to explore factors influencing the riding experience on e-bikes. We applied Gaussian process regression to data collected in a cycling study from 55 e-bike riders including rider behaviour, motor power and riding dynamics. Applying SHAP, we compared the riding experience of four rider types identified by hierarchical cluster analysis. The results provide insights into the riding experience on e-bikes: motor power, rider behaviour and riding dynamics were found to be meaningful predictors differing in their impact between rider types. Our results can be regarded as a proof of concept and demonstrate the potential of XAI to enhance the understanding of user experience in transport.

Investigating the relationship between self-reported (near) crashes, fined traffic offences, and risky riding behaviours among Flemish motorcyclists using the motorcycle rider behaviour questionnaire

Little research on motorcycling safety and rider behaviour has been performed in Belgium. This study used the Motorcycle Rider Behaviour Questionnaire (MRBQ) as part of a larger questionnaire on motorcyclist safety. Data was collected in Flanders (i.e., the Dutch speaking part of Belgium) through 560 motorcycle riders by means of a questionnaire that consisted out of the MRBQ, demographics, personal background, riding experience and exposure, vehicle information, and self-reported (near) crashes and fined offences. Results showed a factor structure consistent with previous studies, comprising the factors ‘traffic errors’, ‘speed violations’, ‘stunts’, ‘protective gear’, and ‘control errors’. Due to the limited number of crashes, only an effect on near-crashes and violations was observed for some of the MRBQ factors, as well as for the age and exposure of riders. This research indicated that the MRBQ has its merits in terms of both construct and predictive validity. Nonetheless, the MRBQ was found to be subject to limitations. The need for more research was raised to examine the potential presence and impact of a social desirability bias and common method variance. Additionally, Implications for practitioners and policy makers have been discussed.

Identification of factors influencing the riding experience on e-mountain bikes: An analysis of the rider-bicycle interaction

E-bike riding contributes to a more sustainable lifestyle by offering health and environmental benefits. Especially e-mountain bikes enjoy great popularity in hilly areas. Although the frequency of use depends substantially on the perceived riding experience, little is known about factors influencing the riding experience. The present work aimed to explore factors influencing the riding experience on e-mountain bikes using a two-step approach. Subjective and objective factors influencing the riding experience were determined through qualitative content analysis of data collected in an interview study (Study 1) with 23 active e-mountain bike riders. Results from Study 1 identified riding performance, consisting of perceived handling, exertion and motor performance as a subjective impact factor of the riding experience. Rider behaviour, which is composed of rider cadence and rider torque, motor power and riding dynamics such as speed were identified as objective impact factors of the riding experience. In a next step, the impact of the determined factors was examined with multiple linear regression analysis applied to data collected in a cycling study (Study 2) with 80 active mountain bikers. The data from Study 2 was recorded on a forest uphill track with e-mountain bikes that provided different motor assistance. Results from Study 2 confirmed that high motor performance, good handling and reduced exertion contributed to a positive riding experience (ad.R2=.68, F(3,446)=325.2, p<.001). Increased rider cadence and rider torque affected the riding experience negatively while increased motor power and speed affected the riding experience positively (ad.R2=.40, F(4,445)=75.89, p<.001). The findings of the present work help to improve the riding experience on e-mountain bikes by revealing influencing factors and their impact on the riding experience.

Analyzing Takeaway E-Bikers’ Risky Riding Behaviors and Formation Mechanism at Urban Intersections with the Structural Equation Model

To study the internal formation mechanisms of risky riding behaviors of takeaway e-bikers at urban intersections, we designed a takeaway riding risky behavior questionnaire and obtained 605 valid samples. An exploratory factor analysis was then conducted to extract five scales: individual characteristics, safety attitude, riding confidence, risk perception, and risky riding behavior. On this basis, a structural equation model was constructed to explore the intrinsic causal relationships among the variables that affect the risky riding behaviors of takeaway e-bikers. The results show that the influence of incentive compensation driven by the takeaway platform was the greatest one. Takeaway riders tend to fight against time to improve punctuality and income by red-light running and speeding. They usually need to pay attention to order information and the delivery routes and communicate with customers to pick up meals in real-time, which inevitably lead to the use of cell phone while riding. Road factors such as “no turnaround at the intersection” and “no non-isolation facilities between on-motorized and motorized lane” lead riders to riding against the traffic, riding on the motor lane, and parking outside the stop line. In addition, lax traffic regulations lead to frequent loopholes for takeaway riders. It means that improving the takeaway platform system, strengthening traffic safety education, and adopting mandatory restraint measures are extremely important. The empirical results provide theoretical support for the benign and healthy development of the takeaway industry, which is significant for preventing and reducing risky behaviors of takeaway riders and improving safety at urban intersections.