The Effect of Sharrows, Painted Bicycle Lanes and Physically Protected Paths on the Severity of Bicycle Injuries Caused by Motor Vehicles

Cycling safely: Examining the factors associated with bicycle accidents in Seoul, South Korea

This study investigates the factors contributing to bicycle accidents, focusing on four types of bicycle lanes and other exposure and built environment characteristics of census blocks. Using Seoul as a case study, three years of bicycle accident spot data from 2018 to 2020 was collected, resulting in 1,330 bicycle accident spots and a total of 2,072 accidents. The geographically weighted Poisson regression (GWPR) model was used as a methodological approach to investigate the spatially varying relationships between the accident frequency and explanatory variables across the space, as opposed to the Poisson regression model. The results indicated that the GWPR model outperforms the global Poisson regression model in capturing unobserved spatial heterogeneity. For example, the value of deviance that determines the goodness of fit for a model was 0.244 for the Poisson regression model and 0.500 for the far better-fitting GWPR model. Further findings revealed that the factors affecting bicycle accidents have varying impacts depending on the location and distribution of accidents. For example, despite the presence of bicycle lanes, some census blocks, particularly in the northeast part of the city, still pose a risk for bicycle accidents. These findings can provide valuable insights for urban planners and policymakers in developing bicycle safety measures and regulations.

Analyzing the Prevalence of and Factors Associated with Road Traffic Crashes (RTCs) among Motorcyclists in Bangladesh

Methods

A cross-sectional survey was conducted using a structured questionnaire involving 402 motorcyclists from four major southeastern towns, comprising 350 (86.07%) males and 52 (12.93%) females. The chi-square test was applied in bivariate analysis, and binary multivariable logistic regression was performed to determine the risk factors of road traffic crashes.

Results

This study's findings revealed that the overall reported prevalence of road traffic crashes involving motorcycle drivers over one year was 68.66%. Multivariable logistic regression analysis revealed several factors that significantly impacted road traffic crashes. These factors included driving without a valid driving license, the young age (<20) of motorcyclists, driving in rainy weather, exceeding the speed limit, per-week working hours, smoking status, motorcycle ownership, the brand of motorcycle, and not wearing a helmet while driving.

Conclusion

The study findings highlight the need for improving motorcycle safety by implementing measures such as imposing per-week work hour limits for riders, enforcing traffic regulations, and promoting helmet use among motorcycle drivers. The results of this study draw attention to the Bangladesh Road Transport Authority (BRTA) and motorcycle drivers in the country to decrease motorcycle crashes and the severity of injuries by implementing efficient guidelines and strategies for driving motorcycles. The findings of this study can assist policymakers and concerned authorities in taking the essential steps to lessen road traffic crashes among motorcyclists in Bangladesh.

Effectiveness of road safety interventions: An evidence and gap map

Background

Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low- and middle-income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high-income countries have successfully reduced RTI by using a public health approach and implementing evidence-based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high-income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.

Objectives

The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.

Search Methods

The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.

Selection Criteria

The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post-crash pre-hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non-fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.

Data Collection and Analysis

The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case-control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.

Main Results

The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post-crash pre-hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non-fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety-six percent of the studies were reported from high-income countries (HIC), 4.5% from upper-middle-income countries, and only 1.4% from lower-middle and low-income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.

Authors' Conclusions

The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence-synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

Conventional or parking-protected bike lanes? A Full-Bayesian before-and-after assessment

OBJECTIVE

Biking infrastructure plays a crucial role in ensuring cyclists' safety and encouraging more people to bike. Recently, many North American municipalities started to adopt a new bike lane design, namely the parking-protected bike lane (PPBL), in which the bike lane is placed between the sidewalk and the parking lane. This study aims to assess the safety impacts associated with converting conventional bike lanes (CBLs) to PPBLs.

METHODS

To that end, collision and traffic data were collected at 19 street sections from three corridors in Vancouver and Ottawa before and after the conversion. Poisson-Lognormal Linear Intervention model was developed to undertake a Full Bayesian before-and-after analysis to evaluate the change in the frequency of bike-vehicle collisions and other collaterally affected collisions (i.e., total and rear-end collisions) after implementing PPBLs.

RESULTS

Reductions of 31.2%, 16.5%, and 4.4% were observed for total, rear-end, and bike collisions, respectively, after implementing the PPBLs, but the results varied significantly depending on the corridor characteristics.

CONCLUSION

Overall, PPBLs demonstrated positive impacts on cyclist safety in some corridors, but their performance is highly sensitive to bike path opening density, intersection density, and intersection treatments.

Protected and unprotected cycle lanes' effects on cyclists' behaviour

Previous research has suggested that in countries with low cycling rates, a barrier to cycling is the perception that cycling is unsafe. Unfortunately, this perception is accurate in many places, and protected cycle lanes have been advocated as a possible solution. Although some research shows that people tend to feel safer in them, there have been conflicting results regarding protected cycle lanes' safety benefits. Understanding the reasons protected cycle lanes may actually reduce safety is key to promoting active transport modes. One possible reason crash rates may increase is that cyclists may cycle faster in them due to either a decreased mental workload or from reduced perceptions of risk. In the present research, two studies were conducted to examine cyclists' speeds and perceptions of difficulty and safety in both protected and unprotected cycle lanes, as well as streets with no cycle lanes. The first study was an online questionnaire using short video clips from a cyclist's perspective, and the second study was an on-road experiment with a post-ride questionnaire. The studies found that cyclists felt safer with protected cycle lanes, were more willing to allow their children to bike on them and showed less concern towards hazards. There was no evidence of decreased attentional demand while using the protected cycle lanes, but there was some evidence of higher maximum cycling speeds.

Infrastructure and Injury Prevention in Cycling

The focus of this article centers on bicycle injury prevention and related infrastructure. The article discusses the current epidemiology of cycling injuries, and known prevention strategies, specifically individual recommended practices related to helmet use in both adult and pediatric populations. The article also discusses different ways in which the environment plays a role in protecting cyclists from injuries, and what environmental changes have been adopted to reduce the likelihood for cycling injuries.

Evaluating cyclist biometrics to develop urban transportation safety metrics

The transportation safety paradigm for urban transportation - particularly safety for those walking and cycling - relies on counting crashes to parameterize safety. These objective measures of safety are spatially static and reflective of past events: they can be enriched by including the human response to risk at diverse infrastructure designs. This perceived risk has been well captured qualitatively in the transportation safety literature; in the following study, we seek to develop a quantitative methodology that captures perceived risk as a continuous measure of human biometrics. Building on diverse safety-critical fields, we hypothesize that the perception of safety can be measured proactively with traveler biometrics, including eye and head movements, such that high readings of biometric indicators correlate with less safe areas. We collect biometric data from cyclists traversing an urban corridor with a protected, yet not continuously, cycle lane. By isolating and correlating peaks in cyclist biometric measures with infrastructure design, we develop a set of continuous variables - lateral head movements, gaze velocity, and off-mean gaze distance, both independently and as a vector - that allow for the evaluation of urban infrastructure based on perceived risk. The results reflect that higher biometric readings correspond to less safe (i.e., unprotected) areas, indicating that perceived risk can be measured proactively with biometric data.

Analysis of the severity of vehicle-bicycle crashes with data mining techniques

INTRODUCTION

Although cycling is increasingly being promoted for transportation, the safety concern of bicyclists is one of the major impediments to their adoption. A thorough investigation on the contributing factors to fatalities and injuries involving bicyclist.

METHOD

This paper designs an integrated data mining framework to determine the significant factors that contribute to the severity of vehicle-bicycle crashes based on the crash dataset of Victorian, Australia (2013-2018). The framework integrates imbalanced data resampling, learning-based feature extraction with gradient boosting algorithm and marginal effect analysis. The top 10 significant predictors of the severity of vehicle-bicycle crashes are extracted, which gives an area under ROC curve (AUC) value of 0.8236 and computing time as 37.8 s.

RESULTS

The findings provide insights for understanding and developing countermeasures or policy initiatives to reduce severe vehicle-bicycle crashes.

Not all protected bike lanes are the same: Infrastructure and risk of cyclist collisions and falls leading to emergency department visits in three U.S. cities

OBJECTIVE

Protected bike lanes separated from the roadway by physical barriers are relatively new in the United States. This study examined the risk of collisions or falls leading to emergency department visits associated with bicycle facilities (e.g., protected bike lanes, conventional bike lanes demarcated by painted lines, sharrows) and other roadway characteristics in three U.S. cities.

METHODS

We prospectively recruited 604 patients from emergency departments in Washington, DC; New York City; and Portland, Oregon during 2015-2017 who fell or crashed while cycling. We used a case-crossover design and conditional logistic regression to compare each fall or crash site with a randomly selected control location along the route leading to the incident. We validated the presence of site characteristics described by participants using Google Street View and city GIS inventories of bicycle facilities and other roadway features.

RESULTS

Compared with cycling on lanes of major roads without bicycle facilities, the risk of crashing or falling was lower on conventional bike lanes (adjusted OR = 0.53; 95 % CI = 0.33, 0.86) and local roads with (adjusted OR = 0.31; 95 % CI = 0.13, 0.75) or without bicycle facilities or traffic calming (adjusted OR = 0.39; 95 % CI = 0.23, 0.65). Protected bike lanes with heavy separation (tall, continuous barriers or grade and horizontal separation) were associated with lower risk (adjusted OR = 0.10; 95 % CI = 0.01, 0.95), but those with lighter separation (e.g., parked cars, posts, low curb) had similar risk to major roads when one way (adjusted OR = 1.19; 95 % CI = 0.46, 3.10) and higher risk when they were two way (adjusted OR = 11.38; 95 % CI = 1.40, 92.57); this risk increase was primarily driven by one lane in Washington. Risk increased in the presence of streetcar or train tracks relative to their absence (adjusted OR = 26.65; 95 % CI = 3.23, 220.17), on downhill relative to flat grades (adjusted OR = 1.92; 95 % CI = 1.38, 2.66), and when temporary features like construction or parked cars blocked the cyclist's path relative to when they did not (adjusted OR = 2.23; 95 % CI = 1.46, 3.39).

CONCLUSIONS

Certain bicycle facilities are safer for cyclists than riding on major roads. Protected bike lanes vary in how well they shield riders from crashes and falls. Heavier separation, less frequent intersections with roads and driveways, and less complexity appear to contribute to reduced risk in protected bike lanes. Future research should systematically examine the characteristics that reduce risk in protected lanes to guide design. Planners should minimize conflict points when choosing where to place protected bike lanes and should implement countermeasures to increase visibility at these locations when they are unavoidable.

Can Automated Vehicles Improve Cyclist Safety in Urban Areas?

Automated vehicles (AVs) are expected to assist in decreasing road traffic fatalities, particularly among passenger cars. However, until now limited research has been conducted on how they will impact the safety of vulnerable road users (VRUs) (i.e., cyclists and pedestrians). Therefore, there is a clear need to start taking into account the interactions between AVs and VRUs as an integrated element of the transport network, especially in urban areas where they are dominant. The objective of this study is to verify whether the anticipated implementation of AVs can actually improve cyclists’ safety. For this purpose, the microscopic traffic flow simulation software PTV Vissim combined with the surrogate safety assessment model (SSAM) were utilized. The road network used for this analysis was generated based on a real study case in a medium-sized city in Belgium, where narrow streets in the city center are shared on many occasions between vehicles and cyclists. The findings of the analysis show a notable reduction in the total number of conflicts between cars, but also between cars and cyclists, compared to the current situation, assuming a 100% market penetration scenario for AVs. Moreover, the severity level of conflicts also decreased as a result of the lack of human-driven vehicles in the traffic streams.

Integrating Spatial and Temporal Approaches for Explaining Bicycle Crashes in High-Risk Areas in Antwerp (Belgium)

The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle–motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle–motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads.

A Rare Event Modelling Approach to Assess Injury Severity Risk of Vulnerable Road Users

Vulnerable road users (VRUs) represent a large portion of fatalities and injuries occurring on European Union roads. It is therefore important to address the safety of VRUs, particularly in urban areas, by identifying which factors may affect the injury severity level that can be used to develop countermeasures. This paper aims to identify the risk factors that affect the severity of a VRU injured when involved in a motor vehicle crash. For that purpose, a comparative evaluation of two machine learning classifiers—decision tree and logistic regression—considering three different resampling techniques (under-, over- and synthetic oversampling) is presented, comparing both imbalanced and balanced datasets. Crash data records were analyzed involving VRUs from three different cities in Portugal and six years (2012–2017). The main conclusion that can be drawn from this study is that oversampling techniques improve the ability of the classifiers to identify risk factors. On the one hand, this analysis revealed that road markings, road conditions and luminosity affect the injury severity of a pedestrian. On the other hand, age group and temporal variables (month, weekday and time period) showed to be relevant to predict the severity of a cyclist injury when involved in a crash.

On-road bicycle lane types, roadway characteristics, and risks for bicycle crashes

Bicycle lanes reduce real and perceived risks for bicycle vs. motor vehicle crashes, reducing the burden of traffic injuries and contributing to greater cycling participation. Previous research indicates that the effectiveness of bicycle lanes differs according to roadway characteristics, and that bicycle lane types are differentially associated with reduced crash risks. The aim of this study is to combine these perspectives and identify the types of on-road bicycle lanes that are associated with the greatest reductions in bicycle crashes given the presence of specific roadway characteristics. We compiled a cross sectional spatial dataset consisting of 32,444 intersection polygons and 57,285 street segment polygons representing the roadway network for inner Melbourne, Australia. The dependent measure was a dichotomous indicator for any bicycle crash (2014-2017). Independent measures were bicycle lanes (exclusive bicycle lanes, shared bicycle and parking lanes, marked wide kerbside lanes, and kerbside bicycle lanes) and other roadway characteristics (speed limit, bus routes, tram routes, bridges, one-way flow, traffic lane width). In Bayesian conditional autoregressive logit models, bicycle lanes of all types were associated with decreased crash odds where speeds were greater, bus routes and tram stops were present, and traffic lanes were narrower. Only exclusive bicycle lanes were associated with reduced crash odds (compared to the expected odds given the presence of the bicycle lane and the roadway conditions) in all these setting. The extent to which on-road bicycle lanes reduce crash risks depends on the bicycle lane type, the roadway conditions, and the combination of these two factors. Bicycle lanes that provide greater separation between cyclists and vehicular traffic are most consistently protective.

Identifying high-risk built environments for severe bicycling injuries

INTRODUCTION

This study is aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated; and if so, what built environment factors most significantly relate to severe bicyclist injuries? Second, are the identified associations varied substantially among cities with different levels of bicycling and different built environments?

METHODS

The generalized ordered logit model is employed to examine the relationship between built environment features and bicyclist injury severity.

RESULTS

Bicyclist injury severity is coded into four types, including no injury (NI), possible injury (PI), evident injury (EI), and severe injury and fatality (SIF). The findings include: (a) higher percentages of residential land and green space, and office or mixed use land are correlated with lower probabilities of EI and SIF; (b) land use mixture is negatively correlated with EI and SIF; (c) steep slopes are positively associated with bicyclist injury severity; (d) in areas with more transit routes, bicyclist injury is less likely to be severe; (e) a higher speed limit is more likely to correlate with SIF; and (f) wearing a helmet is negatively associated with SIF, but positively related to PI and EI. Practical applications: To improve bicycle safety, urban planners and policymakers should encourage mixed land use, promote dense street networks, place new bike lanes in residential neighborhoods and green spaces, and office districts, while avoiding steep slopes. To promote bicycling, a process of evaluating the risk of bicyclists involving severe injuries in the local environment should be implemented before encouraging bicycle activities.

Bicycle helmets - To wear or not to wear? A meta-analyses of the effects of bicycle helmets on injuries

A meta-analysis has been conducted of the effects of bicycle helmets on serious head injury and other injuries among crash involved cyclists. 179 effect estimates from 55 studies from 1989-2017 are included in the meta-analysis. The use of bicycle helmets was found to reduce head injury by 48%, serious head injury by 60%, traumatic brain injury by 53%, face injury by 23%, and the total number of killed or seriously injured cyclists by 34%. Bicycle helmets were not found to have any statistically significant effect on cervical spine injury. There is no indication that the results from bicycle helmet studies are affected by a lack of control for confounding variables, time trend bias or publication bias. The results do not indicate that bicycle helmet effects are different between adult cyclists and children. Bicycle helmet effects may be somewhat larger when bicycle helmet wearing is mandatory than otherwise; however, helmet wearing rates were not found to be related to bicycle helmet effectiveness. It is also likely that bicycle helmets have larger effects among drunk cyclists than among sober cyclists, and larger effects in single bicycle crashes than in collisions with motor vehicles. In summary, the results suggest that wearing a helmet while cycling is highly recommendable, especially in situations with an increased risk of single bicycle crashes, such as on slippery or icy roads.

Bicycle Facilities That Address Safety, Crime, and Economic Development: Perceptions from Morelia, Mexico

México is a developing nation and, in the city of Morelia, the concept of the bicyclist as a road user appeared only recently in the Municipal Traffic Regulations. Perhaps the right bicycle infrastructure could address safety, crime, and economic development. To identify the best infrastructure, six groups in Morelia ranked and commented on pictures of bicycle environments that exist in bicycle-friendly nations. Perceptions about bike paths, but only those with impossible-to-be-driven-over solid barriers, were associated with safety from crashes, lowering crime, and contributing to economic development. Shared use paths were associated with lowering the probability of car/bike crashes but lacked the potential to deter crime and foster the local economy. Joint bus and bike lanes were associated with lower safety because of the unwillingness by Mexican bus drivers to be courteous to bicyclists. Gender differences about crash risk biking in the road with the cars (6 best/0 worst scenario) were statistically significant (1.4 for male versus 0.69 for female; p < 0.001). For crashes, crime, and economic development, perceptions about bicycle infrastructure were different in this developing nation perhaps because policy, institutional context, and policing (ticketing for unlawful parking) are not the same as in a developed nation. Countries such as Mexico should consider building cycle tracks with solid barriers to address safety, crime, and economic development.