Cyclists and drivers in road interactions: A comparison of perceived crash risk

Computer vision and statistical insights into cycling near miss dynamics

Across the globe, many transport bodies are advocating for increased cycling due to its health and environmental benefits. Yet, the real and perceived dangers of urban cycling remain obstacles. While serious injuries and fatalities in cycling are infrequent, "near misses"-events where a person on a bike is forced to avoid a potential crash or is unsettled by a close vehicle-are more prevalent. To understand these occurrences, researchers have turned to naturalistic studies, attaching various sensors like video cameras to bikes or cyclists. This sensor data holds the potential to unravel the risks cyclists face. Still, the sheer amount of video data often demands manual processing, limiting the scope of such studies. In this paper, we unveil a cutting-edge computer vision framework tailored for automated near-miss video analysis and for detecting various associated risk factors. Additionally, the framework can understand the statistical significance of various risk factors, providing a comprehensive understanding of the issues faced by cyclists. We shed light on the pronounced effects of factors like glare, vehicle and pedestrian presence, examining their roles in near misses through Granger causality with varied time lags. This framework enables the automated detection of multiple factors and understanding their significant weight, thus enhancing the efficiency and scope of naturalistic cycling studies. As future work, this research opens the possibility of integrating this AI framework into edge sensors through embedded AI, enabling real-time analysis.

Self-reported cycling behavior and previous history of traffic accidents of cyclists

BACKGROUND

Cyclists are vulnerable traffic users and studying the cycling behavior of professional and elite cyclists, their previous history of traffic accidents combined with the current knowledge on high-risk behaviors of this group can be a useful basis for further studies on ordinary cyclists. This study aimed to determine the relationship between cycling behavior and the previous history of traffic accidents among members of the Cycling Federation of Guilan province in 2022.

METHODS

A descriptive-analytical study was performed in which the Bicycle Rider Behavior Questionnaire (BRBQ) constructed in the Porsline platform was distributed using the WhatsApp social network. All participants were asked to self-report their cycling behavior. The final analysis was performed by using STATA software (version 14).

RESULTS

The study subjects included a total of 109 cyclists with a mean age of 38.62 ± 10.94 years and a mean cycling experience of 13.75 ± 11.08 years. Using the logistic regression model, the relationship between gender (P = 0.039), years of cycling experience (P = 0.000), and education level (P ≤ 0.00), with previous traffic accidents, was found significant. There was also a significant relationship between stunts and distractions (P = 0.005), signaling violation (P = 0.000), and control error (P = 0.011) with previous traffic accidents. A significant association existed between stunts and distractions (P = 0.001) and signaling violation (P = 0.001) with a previous history of traffic injury within the last 3 years.

CONCLUSIONS

The findings of this study can be used to establish cyclist safety and preventative planning in society. In behavior change intervention programs, it is best to target male cyclists with higher-level education. In addition, the behavior of the cyclists whose predominant term of signaling violations must be corrected should be targeted. It is necessary to shape information campaigns and educational programs aimed for cyclists with common high-risk behaviors, especially signaling violations.

The road safety and risky behavior analysis of delivery vehicle drivers in China

The delivery industry has seen dramatic growth in demand and scale in China. Due to the stock limitations and delivery time restrictions, the couriers may commit traffic violations while delivering, resulting in a pessimistic road safety situation. This study aims to reveal critical factors that influence delivery vehicle crash risks. A cross-sectional structured questionnaire survey is conducted to collect demographic attributes, workload, work emotions, risky driving behavior, and road crash involvement data among 824 couriers in three developed regions of China. The collected data is then analyzed through an established path model to identify the contributing factors of delivery road crash risks and risky behaviors. The road crash risk level (RCRL) indicator is defined by taking into consideration both frequency and severity. While the risky behaviors are defined by both their frequency and correlations to crash risks. The results indicate that 1) Beijing-Tianjin Urban Agglomeration has the highest road crash frequency and RCRL; 2) distracted driving and wrong-lane-use are among the top three risky behaviors for both Yangtze River Delta Urban Agglomeration and Pearl River Delta Urban Agglomeration. For Beijing-Tianjin Urban Agglomeration, distracted driving, aggressive driving, and lack of protection are the top three risky behaviors; 3) time demand and personal efforts are important factors contributing to the cognitive workload of couriers; 4) objective workload can affect the cognitive workload and both workloads influence drivers' emotions (anxiety and anger); 5) the objective, cognitive workload, drivers' emotions influence the RCRL through their impacts on risky behavior but in different paths for three agglomerations. The findings highlight the importance of developing targeted countermeasures to reduce the delivery workers' workload, improve their performance on roads, and mitigate severe crash risks.

Resilience engineering on the road: Using operator event sequence diagrams and system failure analysis to enhance cyclist and vehicle interactions

Future visions of transport systems include both a drive towards automated vehicles and the need for sustainable, active, modes of travel. The combination of these requirements needs careful consideration to ensure the integration of automated vehicles does not compromise vulnerable road users. Transport networks need to be resilient to automation integration, which requires foresight of possible challenges in their interaction with other road users. Focusing on a cyclist overtake scenario, the application of operator event sequence diagrams and a predictive systems failure method provide a novel way to analyse resilience. The approach offers the opportunity to review how automation can be positively integrated into road transportation to overcome the shortfalls of the current system by targeting organisational, procedural, equipment and training measures.

A quantitative traffic performance comparison study of bicycles and E-bikes at the non-signalized intersections: Evidence from survey data

As common transportation modes at non-signalized intersections, bicycles and e-bikes have been involved in most traffic crashes. Although a large number of studies have been dedicated to studying the safety problems caused by bicycles and e-bikes, there is still limited attention paid to the differences between them, especially at non-signalized intersections. This paper compares the differences between bicycles and e-bikes based on a self-administered questionnaire. This questionnaire was distributed to bicycle users (N = 453) and e-bike users (N = 439). The personal characteristics, decision-making capacity, the feeling of infrastructure, perceived level of service, and perceived level of risk were adopted as the performance indicators to depict the difference in the study area. Using statistical methodologies and the Structural Equation Model (SEM), key findings indicate that perceived level of service was found to be significantly different between bicycles and e-bikes at most non-signalized intersections. 43.4 % of e-bike riders often or always choose to avoid riding under extreme weather, while 58.7 % of bicycle riders avoid riding under extreme weather. Moreover, compared with bicycles, e-bikes' decision-making capacity is affected more by infrastructure quality. The difference between bicycles and e-bikes highlights the need for differentiated development of cycling safety education and law enforcement.

A Naturalistic Study Assessing the Impact of Daytime Running Lights and Vehicle Passing events on Cyclist's Physiological Stress

Bicyclists are vulnerable road users who are at a greater risk for injury and fatality during crashes. Additionally, the "near-miss" incidents they experience during regular trips can increase the perceived risk and deter them from riding again. This paper aims to use naturalistic bicycling data collected in Johnson County, Iowa to: 1) study the effect of factors such as road surface type, parked vehicles, pavement markings and car passing events on cyclists' physiological stress and 2) understand the effect of daytime running lights (DRL) as an on-bicycle safety system in providing comfort to cyclists and highlight of their presence on the road to other vehicles. A total of 37 participants were recruited to complete trips over two weekends, one weekend with DRL and the other without DRL. Recruitment was specifically targeted toward cyclists who expressed discomfort riding in traffic. Data were collected using a front forward facing camera, GPS, and a vehicle lateral passing distance sensor mounted on the bicycle and a Empatica E4 wrist band (providing physiological data such as electrodermal activity; EDA) worn by the cyclist. Data from those sources were cleaned, processed, merged, and aggregated into time windows depicting car passing and no car passing events. Mixed effects models were used to study the cyclists' skin conductance response (phasic EDA) and baseline skin conductance level (tonic EDA). Car passing, parked vehicles, and roads with dashed centerline markings were observed to increase the cyclists stress. The use of DRL had negligible impact on cyclist stress on roads.

Road Users’ Reports on Danger Spots: The Crowd as an Underestimated Expert?

As part of the project EDDA+ (Early Detection of Dangerous Areas in road traffic using smart data), a web-based crowdsourcing platform has been launched on which road users can report danger spots they face in everyday traffic. Whereas official police collision data can only be used reactively, these user reports are intended to warn other road users and provide road safety stakeholders with detailed information for proactive measures. Since this approach is relatively novel, the present pilot study aimed to evaluate the validity of these subjective road user reports. A quasi-randomized sample of N = 77 danger spots distributed over four major German cities was audited using a 70-item objective road safety deficit inventory to identify infrastructural deficits. Based on these items, an overall rating of objective hazardousness for each danger spot was derived. In more than half of the audited danger spots, infrastructural deficits were identified in the audit (=confirmed hazard). In another quarter of audited dangers spots, the reported hazard could not be identified without any doubt due to a lack of infrastructural deficit or detailed information about the nature of the hazard (=uncertain, no certain match between audit and report). Our analysis further revealed that an increased number of road user interactions for the respective danger spot yielded a higher likelihood of confirmation of a danger spot’s hazardousness. Descriptively, pedestrians and bicyclists were most often mentioned as exposed to danger, with the most prevalent nature of danger being areas with poor visibility and misconduct by drivers. The results were blended with police collision data in the next step. We did not find a significant relationship between our danger spots’ rating and the number of collisions at the respective spot. Our results indicate that reports of danger spots and the increased user related activity can serve as an indicator for the early detection of road traffic hazards.

Is safety in the eye of the beholder? Discrepancies between self-reported and proxied data on road safety behaviors—A systematic review

Recent studies have problematized on the lack of agreement between self-reported and proxied data in the field of road safety-related behaviors. Overall, and although these studies are still scarce, most of them suggest that the way we perceive our own road behavior is systematically different from the perspective from which we perceive others' behavior, and vice versa. The aim of this review paper was to target the number and type of studies that have researched the behavioral perceptions of different groups of road users, contrasting self-reported behavioral data with those reported by other users (proxied), and their outcomes. This systematic review followed the PRISMA methodology, which allows for the identification of relevant articles based on the research term. A total number of 222 indexed articles were filtered, and a final selection of 19 articles directly addressing the issue was obtained. Search strategies were developed and conducted in MEDLINE, WOS, Scopus and APA databases. It is remarkable how road users perceive themselves as behaviorally “safer” than the rest of road users in what concerns the knowledge of traffic norms and their on-road performance. In addition, and regardless of the type of user used as a source, self-reported data suggest their perceived likelihood to suffer a traffic crash is lesser if compared to any other user. On the other hand, proxied reports tend to undervalue third users' performance, and to perceive riskier behaviors and crash-related risks among them. The outputs of this systematic review support the idea that the perception of road users' behavior and its related risks substantially differ according to the source. It is also necessary to increase the number, coverage and rigor of studies on this matter, perhaps through complementary and mixed measures, in order to properly understand and face the bias on road users' risk-related behaviors.

How safe do you feel? - A large-scale survey concerning the subjective safety associated with different kinds of cycling lanes

There is ample evidence that adequate cycling infrastructure increases cyclists' safety. There is less research to what extent the specific design of cycling lanes affects subjective safety. We address this question by analysing data from a large-scale online survey, where participants rated images illustrating a wide range of cycling infrastructure designs for the anticipated level of subjective safety when imagining to cycle at the displayed location. Cycling tracks are perceived as safer than cycling lanes, which in turn are preferred over cycling on the street. Physical separations from the car lane, a greater lane width, and a coloured surface contribute most to a high subjective safety of cycling lanes. Additional buffers on the left- and right side of cycling lanes can have varying effects. On narrower cycling lanes, people experience extensive buffer designs as rather constraining and as impairing their safety. Combining several safety features (i.e. a sufficient demarcation of the left buffer and a coloured surface) is not necessarily beneficial for subjective safety. Our findings are mostly in line with findings on the factors benefitting or impairing objective safety. However, the relation of subjective and objective safety requires further attention.

A Rider-Centered Critical Decision Method Study to Better Understand the Challenges to Further Uptake of Cycling

Despite the many benefits of cycling, there is still a widespread perception that riding bicycles on public roads is unsafe. There has been a substantial increase in cycling research over the past decade, but little work has explored the challenges to greater uptake of cycling from a rider-centered perspective. To explore this, our research undertook a large international survey for experienced cyclists in which rider perspectives were explored using an in-depth process called the Critical Decision Method. The results revealed a wide range of self-reported cycling experiences, and most respondents classified themselves as either strong and fearless or enthused and confident. Few actual differences with respect to threatening incidents and rider countermeasures were present, illustrating how overall similarly experienced cyclists respond to threatening incidents. An overarching summary of all survey responses is presented with respect to each gender, then a more specific case study of two riders, one female and one male, is presented showing how many emotions and fear responses were similar for the different riders, but their coping strategies and reactions were somewhat different. It is concluded that further work to explore the issue from a rider-centered perspective is needed, and that the wide variety of cyclist types implies that there is no single recommendation for encouraging greater uptake of riding.

Crash risk and subjective risk perception during urban cycling: Accounting for cycling volume

Most research concerned with cyclists' safety has been focused on the crash risk (i.e. their objective safety). However, there has been a growing interest in the perceived level of this risk (i.e. the subjective safety of cyclists). Crash risk and subjective risk perception in urban cycling appear to be mostly well aligned. For example, reduced speed limits have been found to reduce both objective and subjective risks (although there is also evidence for some incongruences). This absolute number of incidents could be misleading, as it does not account for potential differences in cycling volume (i.e. cyclists are likely to prefer streets with reduced speed limits). Thus, it may be important to adjust the absolute number of incidents relative number to the local cycling volume. In this research, we investigate the relation of cycling crashes and subjective risk perception (operationalized through reports from a crowd-sourcing project) for different types of cycling infrastructure and different speed limits, while accounting for the local cycling volume. We find that the absolute number of VGI reports and crashes can be misleading: whereas the absolute incident numbers, for example, suggest few benefits of cycling lanes and tracks, adjusting for the cycling volume reveals an increase of both objective and subjective safety as compared to streets without cycling infrastructure. We also identify situations where cyclists apparently underestimate the crash risk (i.e. on cycleways opposing the cars' traveling direction, and at streets with a speed limit of 30 km/h intersecting streets with higher speed limits). Additional research is required to understand the sources of these discrepancies, and how to make cyclists aware of them.

Women cycling in Queensland: Results from an observational study

Women are less likely to ride than men in low cycling countries such as Australia. In Australia, self-reported cycling participation appears to be declining, particularly for women. This paper examines the rider and road environment correlates of women's cycling. While most earlier studies relied on self-report data to understand gender differences in cycling, this study video-recorded 24,868 riders (22 % female) at 17 sites across Queensland, Australia. The probabilities of an observed rider being female under different circumstances (e.g., speed limit, riding location, time of riding, group riding) at these sites were modelled in a binomial logistic regression framework. The likelihood of a rider being a woman was greater during the day (9am-8pm) than the early morning (5-9 a.m.); on weekends than on weekdays; in groups of two or more riders than among single riders; in lower speed zones than speed zones of 60 km/h or over; on roads with bike lanes or multiple traffic lanes or raised medians than on roads without these, and in urban areas than suburban areas. The likelihood of the rider being a woman was lower among those riding road bikes than other types of bicycles. The use of a naturalistic study design marks the key strength of this paper. Findings of this study should help better understand women's cycling patterns and preferred cycling locations, which cycling communities and organisations can use to advocate for better roads and paths that make female riders feel safe.

“Not as Safe as I Believed”: Differences in Perceived and Self-Reported Cycling Behavior between Riders and Non-Riders

Cycling behavior remains a key issue for explaining several traffic causalities occurring every day. However, recent studies have shown how the assessment of the own safety-related behaviors on the road may substantially differ from how third parties assess them. Thus, the aim of this study was to evaluate the differences between cyclists’ self-reported behavior and the proxy-reported behavior that other (non-cyclist) road users perceive from bike riders. For this purpose, this study used data from two samples: (i) 1064 cyclists (M = 32.83 years) answering the Cycling Behavior Questionnaire—CBQ, and (ii) 1070 non-cyclists (M = 30.83 years) answering an adapted version of the CBQ for external raters—ECBQ. The results show how the self-reported and proxy-reported behaviors of cyclists greatly differ in terms of all behavioral factors composing the CBQ model, i.e., traffic violations, riding errors, and positive behaviors. Also, external raters (non-cyclists) are those targeting significantly riskier behaviors than those self-reported by cyclists. These discrepancies between perceived behaviors may give rise to conflicting viewpoints on the interaction between bicycle riders and other road users. Therefore, this study underscores the importance of behavioral awareness, providing highlights for future studies on the behavioral interaction between cyclists and other road users. Results can be used to improve the road safety of all road users by giving indications on self-and proxy-perceived safety-related behaviors and visibility of protective riding habits.

Crash risk and subjective risk perception during urban cycling: Evidence for congruent and incongruent sources

BACKGROUND

Urban planners frequently neglect the role of subjective risk perception during urban cycling. Several findings suggest a complex relationship between the risk of being involved in a crash and the subjective anticipation of this risk.

DATA COLLECTION AND METHODS

We investigate the relation of objective risks (operationalized through crashes involving cyclists) and subjective risk perception (operationalized through citizens' reports in a crowdsourcing project) in a medium-sized German city. Using GIS methods, these datasets are linked to various infrastructure and traffic properties that have been found relevant for cycling safety.

RESULTS

Despite a generally high alignment of objective and subjective risk, our findings highlight that the subjective risk perception at a given location can deviate significantly from the actual crash risk. For example, the subjective perception of high risk on one-way streets with bikeways in opposing direction is not matched by a high level of objective risk. Vice versa, some rather dangerous situations (e.g., tram stops) are not perceived as particularly dangerous.

CONCLUSIONS

Understanding why and where cyclists over- or underestimate the actual crash risk may provide a foundation for the design of safer cycling infrastructures, as well as for promoting cycling as a comfortable mode of transportation.

Exploring the severity of bicycle-vehicle crashes using latent class clustering approach in India

INTRODUCTION

Bicyclists are vulnerable users in the shared asset like roadways. However, people still prefer to use bicycles for environmental, societal, and health benefits. In India, the bicycle plays a role in supporting the mobility to more people at lower cost and are often associated with the urban poor. Bicyclists represents one of the road user categories with highest risk of injuries and fatalities. According to the report by the Ministry of Road Transport and Highways (Accidents, 2017) in India, there is a sharp increase in the number of fatal victims for bicyclists in 2017 over 2016. The number of cyclists killed jumped from 2,585 in 2016 to 3,559 in 2017, a 37.7% increase.

METHOD

Few studies have only investigated the crash risk perceived by the bicyclists while interacting with other road users. The present paper investigates the injury severity of bicyclists in bicycle-vehicle crashes that occurred in the state of Tamilnadu, India during the nine year period (2009-2017). The analyses demonstrate that dividing bicycle-vehicle collision data into five clusters helps in reducing the systematic heterogeneity present in the data and identify the hidden relationship between the injury severity levels of bicyclists and cyclists demographics, vehicle, environmental, temporal cause for the crashes.

RESULTS

Latent Class Clustering (LCC) approach was used in the present study as a preliminary tool for the segmentation of 9,978 crashes. Later, logistic regression analysis was used to identify the factors that influence bicycle crash severity for the whole dataset as well as for the clusters that were obtained from the LCC model. Results of this study show that combined use of both techniques reveals further information that wouldn't be obtained without prior segmentation of the data. Few variables such as season, weather conditions, and light conditions were significant for certain clusters that were hidden in the whole dataset. This study can help domain experts or traffic safety researchers to segment traffic crashes and develop targeted countermeasures to mitigate injury severity.

Comparison of in-sight and handheld navigation devices toward supporting industry 4.0 supply chains: First and last mile deliveries at the human level

Last (and First) mile deliveries are an increasingly important and costly component of supply chains especially those that require transport within city centres. With reduction in anticipated manufacturing and delivery timescales, logistics personnel are expected to identify the correct location (accurately) and supply the goods in appropriate condition (safe delivery). Moving towards more environmentally sustainable supply chains, the last/first mile of deliveries may be completed by a cyclist courier which could result in significant reductions in congestion and emissions in cities. In addition, the last metres of an increasing number of deliveries are completed on foot i.e. as a pedestrian. Although research into new technologies to support enhanced navigation capabilities is ongoing, the focus to date has been on technical implementations with limited studies addressing how information is perceived and actioned by a human courier. In the research reported in this paper a comparison study has been conducted with 24 participants evaluating two examples of state-of-the-art navigation aids to support accurate (right time and place) and safe (right condition) navigation. Participants completed 4 navigation tasks, 2 whilst cycling and 2 whilst walking. The navigation devices under investigation were a handheld display presenting a map and instructions and an in-sight monocular display presenting text and arrow instructions. Navigation was conducted in a real-world environment in which eye movements and device interaction were recorded using Tobii-Pro 2 eye tracking glasses. The results indicate that the handheld device provided better support for accurate navigation (right time and place), with longer but less frequent gaze interactions and higher perceived usability. The in-sight display supported improved situation awareness with a greater number of hazards acknowledged. The benefits and drawbacks of each device and use of visual navigation support tools are discussed.

Personality and Behavioral Predictors of Cyclist Involvement in Crash-Related Conditions

In recent years, the increasing rate of road crashes involving cyclists with a disproportionate overrepresentation in injury statistics has become a major concern in road safety and public health. However, much remains unknown about factors contributing to cyclists’ high crash rates, especially those related to personal characteristics. This study aims to explore the influence of cyclist personality traits and cycling behaviors on their road safety outcomes using a mediated model combining these constructs. A total of 628 cyclists completed an online questionnaire consisting of questions related to cycling anger, impulsiveness, normlessness, sensation seeking, risky cycling behaviors, and involvement in crash-related conditions in the past year. After the psychometric properties of the employed scales were examined, the relationships among the tested constructs were investigated using structural equation modeling. The results showed that cyclists’ crash risks were directly predicted by risky cycling behaviors and cycling anger, and the effects of cycling anger, impulsiveness, as well as normlessness on crash risks, were mediated by cycling behaviors. The current findings provide insight into the importance of personality traits in impacting cycling safety and could facilitate the development of evidence-based prevention and promotion strategies targeting cyclists in China.

Seasonal variation in risk perception and travel behaviour among cyclists in a Norwegian urban area

The main purpose of the article is to examine the association between risk perception and cyclists' decision as to whether to cycle during the different seasons of the year. The study on which the article is based included worry as a feeling that emerges as a result of an individual's cognitive assessment of risk, attitudes toward traffic rules, risk tolerance and safety priority. The study was based on a questionnaire survey carried out among cyclists from Trondheim Municipality in Norway (n = 291) during spring 2017. The results revealed seasonal differences in perceived risk and that risk perception was an important predictor of both the decision as to whether to cycle and the frequency of cycling during wintertime. The same results were not found for cycling during the other seasons of the year. Additionally, an association was found between risk perception and worry. The respondents were more worried when cycling in winter conditions compared with cycling in summer conditions, and worry was a strong predictor of travel mode behaviour. The authors found that when the respondents' perception of risk was very low, they were not worried and hence their behaviour was not affected. Perceived risk and worry were only associated with cycling behaviour during wintertime. These findings may be used as a guide in measures implemented to increase the number of cyclists during winter and in communications to the public about the risks linked to cycling.

Risk perception during urban cycling: An assessment of crowdsourced and authoritative data

Subjective risk perception during urban cycling has been mostly investigated through questionnaire studies. However, newly available data sources promise extended possibilities for the investigation and understanding of the underlying factors. We validate the rationale for using both opportunistically available crowd-sourced data (i.e., volunteered geographic information or VGI) as well as more established but rarely investigated authoritative data as predictors of subjective cycling risk. We achieve this by correlating indicators of cycling risk extracted from both VGI and authoritative data for two different German cities with participants' risk estimates assessed in laboratory-based virtual reality experiments. In Case 1, 15 participants (mostly undergraduate students with a mean age of 22 years old; nine of them females) were tested as a sample representing frequent and experienced cyclists, but unfamiliar with the 19 tested locations and less likely to be affected by the virtual reality setup. In Case 2, 24 new participants (mostly undergraduate students; mean age 24 years; 13 of them females) were experienced cyclists and mostly familiar with the 40 test locations located in their city of residence. For both cases, our findings provide evidence that parameters extracted from VGI (e.g., the semantic severity of the contribution and the reception by other citizens) as well as from authoritative data sources (e.g., accident statistics or Space Syntax measures) represent valid indicators for the subjectively perceived risk of cycling at a specific location. On the basis of this validation, future research can use these data sources to investigate the sources of risk perception during urban cycling in greater detail.

Distraction of cyclists: how does it influence their risky behaviors and traffic crashes?

Background

Undisputedly, traffic crashes constitute a public health concern whose impact and importance have been increasing during the past few decades. Specifically, road safety data have systematically shown how cyclists are highly vulnerable to suffering traffic crashes and severe injuries derived from them. Furthermore, although the empirical evidence is still very limited in this regard, in addition to other human factors involved in cycling crashes, distractions while cycling appear to be a major contributor to the road risk of cyclists.

Objectives

The main objectives of this study were, first, to explore the prevalence and trends of cycling distractions within an international sample of bike users, and second, to determine the influence of such distractions on road crashes suffered by cyclists, simultaneously considering the explanatory role of risky behaviors (errors and traffic violations) as potentially mediating variables between cycling distractions and traffic crashes.

Methods

For this cross-sectional study, we analyzed the data obtained from 1,064 cyclists—61.2% male and 38.8% female—from 20 different countries, who answered an on-line questionnaire on cycling-related features, habits, behaviors and accidents.

Results

The prevalence of different cycling distractions oscillated between 34.7% and 83.6%. The most common distractions were those related to the behavior of other users, physical elements of the road, weather conditions and phone calls. Age trends and differences were also found, thus establishing a positive association between age and distractibility during cycling. Furthermore, the effect of distractions on traffic crashes of cyclists was significant when tested together with age, risk perception and risky behaviors on the road.

Conclusion

The results of this study support the hypotheses that distractions have a major prevalence among bike users, and that they play a significant role in the prediction of the traffic crash rates of cyclists, through the mediation of risky behaviors.

Crash risk: How cycling flow can help explain crash data

Crash databases are commonly queried to infer crash causation, prioritize countermeasures to prevent crashes, and evaluate safety systems. However, crash databases, which may be compiled from police and hospital records, alone cannot provide estimates of crash risk. Moreover, they fail to capture road user behavior before the crash. In Sweden, as in many other countries, crash databases are particularly sterile when it comes to bicycle crashes. In fact, not only are bicycle crashes underreported in police reports, they are also poorly documented in hospital reports. Nevertheless, these reports are irreplaceable sources of information, clearly highlighting the surprising prevalence of single-bicycle crashes and hinting at some cyclist behaviors, such as alcohol consumption, that may increase crash risk. In this study, we used exposure data from 11 roadside stations measuring cyclist flow in Gothenburg to help explain crash data and estimate risk. For instance, our results show that crash risk is greatest at night on weekends, and that this risk is larger for single-bicycle crashes than for crashes between a cyclist and another motorist. This result suggests that the population of night-cyclists on weekend nights is particularly prone to specific crash types, which may be influenced by specific contributing factors (such as alcohol), and may require specific countermeasures. Most importantly, our results demonstrate that detailed exposure data can help select, filter, aggregate, highlight, and normalize crash data to obtain a sharper view of the cycling safety problem, to achieve a more fine-tuned intervention.

Interaction driver-bicyclist on rural roads: Effects of cross-sections and road geometric elements

The interaction of motorists and bicyclists, particularly during passing maneuvers, is cited as one of the primary causes of bicyclist fatalities. This paper reports the results of a driving simulator study, which sought to analyze the effects that three cross-section configurations of a two-lane rural road and four geometric elements of the road have on driver behavior, during the interaction with a cyclist. A two-lane rural road, about 11km long, was designed and implemented in an advanced-interactive driving simulator. Three different cross-sections (all with same width, but with and without a bicycle lane and for different widths of bicycle lane) were tested. Forty participants carried out three driving sessions (one for each road alignment with different cross-section) and were exposed to the condition of bicycle traffic along four geometric elements of the alignment (2 tangents with different lengths, right curve and left curve). The driving simulator experiments were designed in such a way that, along the sections where the driver-cyclist interactions occurred, the oncoming traffic was absent. Overall, 468 speed profiles and 468 lateral position profiles were plotted to obtain the descriptive variables of the driver behavior during the interaction with the cyclist. The influences of cross-sections, geometric elements and bicycle traffic conditions on driver behavior were evaluated by a multivariate variance analysis. The presence of the cyclist determined different levels of influence on driver's trajectory for the three cross-sections. A wider bicycle lane ensured a higher later clearance distance between driver and cyclist, allowing safer overtaking maneuver. The interferences of the cyclist on driver's behavior depended on the geometric elements. On tangents, the lowest lateral clearances were recorded and no speed reduction was observed, compared to the cyclist absence condition. On the left curve, the higher lateral clearance was recorded, due to the concordant tendencies of the driver to move away from the cyclist and to cut the curve. This determined an excessive and risky displacement of the vehicle to the opposing lane, whose criticality was also emphasized by the high speed adopted by the driver. On the right curve, the lateral clearance was higher than that recorded on the tangents, probably due to the necessity of the driver to perform the demanding maneuver of entering in the right curve, which also determined a speed reduction compared to the cyclist absence condition. The obtained results provide suggestions for the most efficient cross-section reorganization of existing two-lane rural roads in order to improve the road safety.

Characteristics of bicycle crashes in an adolescent population in Flanders (Belgium)

INTRODUCTION

In regions where transportation is mainly motorized, air pollution and traffic congestion are rife. Active transportation such as cycling might be a solution but safety is a major concern. An efficient science based safety policy is needed. The aim of this paper is to analyze in depth the bicycle crash causes and characteristics in an adolescent population (14-18 yr).

METHODS

By using questionnaires for self-reported bicycle crashes, bicycle crash data were collected from insurance companies (January 2014-June 2015) and from schools (November 2013-March 2014). Six bicycle crash causes were predefined and possible differences between schools and insurance companies were analyzed.

RESULTS

Eighty-six school and 78 insurance registered crashes were analyzed. "Distraction of the cyclist" and "third party crossing a bicycle path failing to see the cyclist" are the main causes of bicycle crashes (both 29%). Bad (maintained) infrastructure accounted for 21% of the crash causes. Bicycle crashes reported at insurance companies needed significantly more medical attention and led to high absenteeism (57% at least one day of absenteeism). Only 21% of the bicycle crashes reported at insurance companies were also reported in the official police database.

CONCLUSION

The human factor was the main cause accounting for 79% of the crashes. Bicycle crashes involving a car accounted for 42% and single bicycle crashes accounted for 31% of the total number of crashes. From the bicycle crashes registered at insurance companies 21% was also registered in official police statistics. A combination of information, education and changing the bicycle specific environment might reduce the consequences of human errors more efficiently.

Association between intersection characteristics and perceived crash risk among school-aged children

This research examined how environmental attributes near intersections influence the perceived crash risk among school-aged children, which provides information on the potential risks of pedestrian crashes that can guide the development of proactive countermeasures. In a sample of 799 children aged 10-12 years old in Korea, the environmental attributes of intersections perceived as having a high risk of producing crashes near elementary schools were investigated using standard negative binomial and zero-inflated negative binomial models.The results showed that a higher number of student crossings, a wider road width, the presence of crosswalks, student-friendly facilities at the intersection, and four-way intersections were significant and positively associated with perceived crash risk among school-aged children. The findings related to building characteristics indicated that a higher number of entrances at an intersection increased the perceived crash risk while higher visibility at the intersection reduced the perception of risk. Associations with traffic-calming measures were weak,suggesting that the measures used in the study areas were not effective in reducing the perceived crash risk. The results of a police-reported crash model showed that school-aged children have a relatively accurate perception of crash risk and that the perceived crash risk of school-aged children may provide valuable information on the intersection characteristics in need of attention near school sites.

How do drivers overtake cyclists?

In Europe, the number of road crashes is steadily decreasing every year. However, the incidence of bicycle crashes is not declining as fast as that of car crashes. In Sweden, cyclists are the most frequently injured road users. Collisions between bicycles and motorized vehicles are of particular concern because the high speed and large mass of motorized vehicles create a high risk of serious injury to cyclists. In Sweden's urban areas, bicycle lanes keep bicycles separated from motorized vehicles, but on rural roads bicycle lanes are often absent, requiring drivers to interact with cyclists-usually by overtaking them. During this maneuver, drivers regulate speed and lateral position, negotiating with potential oncoming traffic to stay within their comfort zones while approaching and passing cyclists. In this study an instrumented bicycle recorded 145 overtaking maneuvers performed by car and truck drivers on public rural roads in Sweden. The bicycle was equipped with a LIDAR and two cameras to assess how drivers approached and circumvented the bicycle. The collected data allowed us to identify four overtaking phases and quantify the corresponding driver comfort zones. The presence of an oncoming vehicle was the factor that most influenced the maneuver, whereas neither vehicle speed, lane width, shoulder width nor posted speed limit significantly affected the driver comfort zone or the overtaking dynamics.

Evaluating the effectiveness of on-street bicycle lane and assessing risk to bicyclists in Charlotte, North Carolina

The objectives of this manuscript are (1) to evaluate the effectiveness of on-street bicycle lane in reducing crashes involving bicyclists on urban roads, (2) to quantify and compare risk to bicyclists on road segments with and without on-street bicycle lane, (3) to evaluate the effect of on-street bicycle lane on other road network users (all crashes), and, (4) to assess the role of on-network characteristics (speed limit, the number of lanes, the width of on-street bicycle lane, the width of the right-most travel lane, and, the numbers of driveways, unsignalized approaches and signalized intersections per unit distance) on risk to bicyclists. Data for thirty-six segments with on-street bicycle lane and twenty-six segments without on-street bicycle lane in the city of Charlotte, North Carolina were extracted to compute and compare measures such as the number of bicycle crashes per center-lane mile, the number of bicycle crashes per annual million vehicle miles traveled (MVMT), the number of all crashes per center-lane mile, and the number of all crashes per MVMT. The results obtained from analysis indicate that bicyclists are three to four times at higher risk (based on traffic conditions) on segments without on-street bicycle lane than when compared to segments with on-street bicycle lane. An analysis conducted considering all crashes showed that on-street bicycle lanes do not have a statistically significant negative effect on overall safety. An increase in annual MVMT (exposure) and the number of signalized intersections per mile increases the number of bicycle crashes, while an increase in on-street bicycle lane width or right-most travel lane width (if on-street bicycle lane cannot be provided) decreases the number of bicycle crashes. Installing wider on-street bicycle lanes, limiting driveways to less than 50 per mile and unsignalized approaches to less than 10 per mile, increasing spacing between signalized intersections, and, facilitating wider right-most travel lane if on-street bicycle lane cannot be provided reduces occurrence of bicycle crashes and lowers risk to bicyclists on roads.

Assessing the 'system' in safe systems-based road designs: using cognitive work analysis to evaluate intersection designs

While a safe systems approach has long been acknowledged as the underlying philosophy of contemporary road safety strategies, systemic applications are sparse. This article argues that systems-based methods from the discipline of Ergonomics have a key role to play in road transport design and evaluation. To demonstrate, the Cognitive Work Analysis framework was used to evaluate two road designs - a traditional Melbourne intersection and a cut-through design for future intersections based on road safety safe systems principles. The results demonstrate that, although the cut-through intersection appears different in layout from the traditional intersection, system constraints are not markedly different. Furthermore, the analyses demonstrated that redistribution of constraints in the cut-through intersection resulted in emergent behaviour, which was not anticipated and could prove problematic. Further, based on the lack of understanding of emergent behaviour, similar design induced problems are apparent across both intersections. Specifically, incompatibilities between infrastructure, vehicles and different road users were not dealt with by the proposed design changes. The importance of applying systems methods in the design and evaluation of road transport systems is discussed.

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

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

Pedestrian preferences with respect to roundabouts -- a video-based stated preference survey

Research on user behavior and preferences has been a helpful tool in improving road safety and accident prevention in recent years. At the same time, there remain some important areas of road safety and accident prevention for which user preferences, despite their importance, have not been explored. Most road safety research has not explicitly addressed vulnerable user (pedestrians and cyclists) preferences with respect to roundabouts, despite their increasing construction around the world. The present research stems from the fact that studies related to roundabout safety have generally focused on drivers, while overlooking the importance of safety as it relates to vulnerable users, especially pedestrians. Moreover, it handles this particular issue through an approach that has not been used so far in this context; the Stated Preference (SP) survey. As such, there are two main goals (and contributions) of this work. First, to show how SP surveys can be used to investigate the importance of different design and operational features to pedestrian perceptions of safety in roundabouts. This allows us, for example, to quantify how some features of roundabouts (e.g. high traffic volume) can be compensated for by design features such as pedestrian islands. This is useful in helping to design roundabouts that pedestrians prefer and will hopefully use, to help encourage active transport. Second, to demonstrate how traffic simulation software can be successfully used to include difficult-to-communicate attributes in SP surveys.