Where do bike lanes work best? A Bayesian spatial model of bicycle lanes and bicycle crashes

Group cycling in urban environments: Analyzing visual attention and riding performance for enhanced road safety

China is a major cycling nation with nearly 400 million bicycles, significantly alleviating urban traffic congestion. However, safety concerns are prominent, with approximately 35% of cyclists forming groups with family, friends, or colleagues, exerting a significant impact on the traffic system. This study focuses on group cycling, employing urban cycling experiments, GPS trajectory tracking, and eye-tracking to analyze the visual search, and cycling control of both groups and individuals. Findings reveal that group cyclists tend to focus more on companions, leading to a dispersed gaze pattern compared to individual riders who focus more on the direct path and surroundings. Group riders also exhibit shorter fixation times on traffic signs, potentially indicating decreased attention to traffic regulations. Despite similar lateral position deviation, group cyclists exhibit higher steering entropy, indicating greater variability in their steering choices. Additionally, group riders demonstrate varied passing times, suggesting a collective advantage in navigating complex traffic conditions. This study enhances our understanding of bicycles within traffic dynamics, offering valuable insights for traffic management systems.

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.

Bicycle infrastructure and the incidence rate of crashes with cars: A case-control study with Strava data in Atlanta

Introduction

Bicycling has individual and collective health benefits. Safety concerns are a deterrent to bicycling. Incomplete data on bicycling volumes has limited epidemiologic research investigating safety impacts of bicycle infrastructure, such as protected bike lanes.

Methods

In this case-control study, set in Atlanta, Georgia, USA between 2016-10-01 and 2018-08-31, we estimated the incidence rate of police-reported crashes between bicyclists and motor vehicles (n = 124) on several types of infrastructure (off-street paved trails, protected bike lanes, buffered bike lanes, conventional bike lanes, and sharrows) per distance ridden and per intersection entered. To estimate underlying bicycling (the control series), we used a sample of high-resolution bicycling data from Strava, an app, combined with data from 15 on-the-ground bicycle counters to adjust for possible selection bias in the Strava data. We used model-based standardization to estimate effects of treatment on the treated.

Results

After adjustment for selection bias and confounding, estimated ratio effects on segments (excluding intersections) with protected bike lanes (incidence rate ratio [IRR] = 0.5 [95% confidence interval: 0.0, 2.5]) and buffered bike lanes (IRR = 0 [0,0]) were below 1, but were above 1 on conventional bike lanes (IRR = 2.8 [1.2, 6.0]) and near null on sharrows (IRR = 1.1 [0.2, 2.9]). Per intersection entry, estimated ratio effects were above 1 for entries originating from protected bike lanes (incidence proportion ratio [IPR] = 3.0 [0.0, 10.8]), buffered bike lanes (IPR = 16.2 [0.0, 53.1]), and conventional bike lanes (IPR = 3.2 [1.8, 6.0]), and were near 1 and below 1, respectively, for those originating from sharrows (IPR = 0.9 [0.2, 2.1]) and off-street paved trails (IPR = 0.7 [0.0, 2.9]).

Conclusions

Protected bike lanes and buffered bike lanes had estimated protective effects on segments between intersections but estimated harmful effects at intersections. Conventional bike lanes had estimated harmful effects along segments and at intersections.

The Impact of the COVID-19 Pandemic on Pediatric Bicycle Injury

Bicycling is a common childhood activity that is associated with significant injury risk. This study's aim was to assess pediatric bicycle injury epidemiology and impacts of the COVID-19 pandemic. We conducted a cross-sectional evaluation of patients age < 18 years presenting with bicycle injury to a pediatric trauma center. A pre-pandemic period (1 March 2015-29 February 2020) was compared to the pandemic period (1 March 2020-28 February 2021). A total of 611 injury events for children < 18 years were included (471 pre-pandemic events and 140 pandemic events). The relative frequency of pandemic injuries was greater than pre-pandemic injuries (p < 0.001), resulting in a 48% increase in pandemic period injuries versus the pre-pandemic average (141 pandemic vs. 94.4/year pre-pandemic). Individuals of female sex represented a larger proportion of injuries in the pandemic period compared to the pre-pandemic period (37% pandemic vs. 28% pre-pandemic, p = 0.035). Injuries were more common on weekends versus weekdays (p = 0.01). Time series analysis showed a summer seasonality trend. Localizing injury events to ZIP codes showed regional injury density patterns. During COVID-19, there was an increase in bicycle injury frequency and proportional shift toward more injuries involving individuals of female sex. Otherwise, injury patterns were largely unchanged. These results demonstrate the necessity of safety interventions tailored to community needs.

Odds of self-reported minor cycle crashes with conventional and electric assisted cycles adjusted for cycling frequency in Dutch and Belgian adults a retrospective study

BACKGROUND

Cycling for transportation and recreation is gaining in popularity, especially in older age groups. The rise in electric assisted cycles (EAC) may also have a role to play in this. With an increase in the number of cyclists comes an increase in the prevalence of cycle crashes. However, there is a lack of knowledge on EAC crashes and crash studies including cycle use data. An important question is also whether the high number of serious road injuries among older cyclists, is due to increased risk or more serious consequences in the event of a crash.

STUDY AIM

To compare the odds of reporting a cycle crash on a conventional (CC) against electrically assisted cycle (EAC), while controlling for age, gender, BMI, impairments while cycling, cycling frequency and region of residence.

METHODS

A 12-month retrospective cross-sectional survey-based study, including male and female cyclists aged 40+ years, was conducted in Belgium and the Netherlands. Socio-demographics, physical and mental impairments while cycling (such as lower reaction time), crash details and cycling frequency data were collected. Cyclists were grouped into CC, EAC or both (CC + EAC) based on the type of cycle they used during the study period. Logistic regression models were used to calculate the odds of reporting a cycle crash. Main and interaction effects were studied.

RESULTS

1,919 cyclists were included in the data analysis (63.2 ± 11.1 years; 50% women). 319 (17% of the total sample) cyclists reported a crash in the previous 12 months, of which 36% were EAC crashes. Those reporting a crash were significantly younger compared to those not reporting a crash. The following significant main effects were observed: those cycling on an EAC had a higher odds of reporting a cycle crash compared to those cycling on a CC (OR = 1.41, 95% CI = 1.01-1.97); cyclists in the category average and high on mental impairments while cycling had a higher odds of reporting a cycle crash compared to those in the category low (OR = 1.72, 95% CI = 1.23-2.40 and OR = 3.49, 95% CI = 2.51-4.90, respectively); higher cycling frequency is related to higher odds of reporting a cycle crash (OR = 3.25, 95% CI = 2.25-4.90). A significant interaction effect was observed between age category and gender (OR = 1.93, 95% CI = 1.15-3.26). Post-hoc tests revealed that men in the younger age category (40-64 years) had the highest probability (18.95%) of reporting a cycle crash, whereas men in the oldest age category (65+ years) had the lowest probability (9.99%) of reporting a cycle crash. No significant difference between age categories in women was observed.

CONCLUSION

This study indicates that within a cohort of middle aged and older adults living in regions with high to low cycling modal shares, cycle type, mental impairments while cycling, cycling frequency and region of residence play a significant role in the odds of reporting a (minor) cycle crash. Men in the age category 40-64 years have a significantly higher probability of reporting a cycle crash compared to men of 65+ years. Safety campaigns and instructions should pay particular attention to men in the age category 40-64 years and those with a mental impairment while cycling.

Bike Helmet Usage in the Most Disadvantaged Neighborhoods: A Focused Area for Trauma Prevention

INTRODUCTION

There is a paucity of data to describe how neighborhood socioeconomic disadvantage (NSD) correlates with childhood injuries and outcomes. This study assesses the relationship of NSD to bicycle safety and trauma outcomes among pediatric bicycle versus automobile injuries.

METHODS

Between 2008 and 2018, patients ≤18 y old with bicycle versus automobile injuries from a Level I pediatric trauma center were evaluated. Area Deprivation Index (ADI) was used to measure NSD. Patient demographics, injury, clinical data characteristics, and bike safety were analyzed. Traffic scene data from the Statewide Integrated Traffic Records System were matched to clinical records. Multivariate logistic regression was used to assess demographic characteristics related to helmet usage.

RESULTS

Among 321 patients, 84% were male with a median age of 12 y [interquartile range 9-13], and 44% were of Hispanic ethnicity. Hispanic ethnicity was greater in the most disadvantaged ADI groups (P < 0.001). Mortality occurred in two patients, and most (96%) were discharged home. Of Statewide Integrated Traffic Records System matched traffic records, 81% were at locations without a bike lane. No differences were found in GCS, intensive care unit admission, or length of stay by ADI. Hispanic ethnicity and the highest deprivation group were independently associated with lower odds of wearing a helmet (AOR 0.35, 95% confidence interval 0.1-0.9, P = 0.03; AOR 0.33 95% confidence interval 0.17-0.62; P = 0.001), while patient age and sex were unrelated to helmet usage.

CONCLUSIONS

Outcomes for bike versus auto trauma remains similar across ADI groups. However, bike helmet usage is significantly lower among Hispanic children and those from neighborhoods with greater socioeconomic disadvantage.

The Effect of Nighttime Rental Restrictions on E-Scooter Injuries at a Large Urban Tertiary Care Center

Safety policy for e-scooters in the United States tends to vary by municipality, and the effects of safety interventions have not been well studied. We reviewed medical records at a large, urban tertiary care and trauma center in Atlanta, Georgia with the goal of identifying trends in e-scooter injury and the effects of Atlanta’s nighttime ban on e-scooter rentals on injuries treated in the emergency department (ED). Records from all ED visits occurring between June 2018 through August 2020 were reviewed. To account for ambiguity in medical records, confidence levels of either “certain” or “possible” were assigned using a set of predefined criteria to categorize patient injuries as being associated with an e-scooter. A total of 380 patients categorized as having certain e-scooter related injuries were identified. The average age of these patients was 31 years old, 65% were male, 41% had head injuries, 20% of injuries were associated with the built environment, and approximately 20% were admitted to the hospital. Approximately 19% of patients with injuries associated with e-scooters noted to be clinically intoxicated or have a serum ethanol level exceeding 80 mg/dL. The implementation of a nighttime rental ban on e-scooter rentals reduced the proportion of patients with e-scooter injuries with times of arrival during the hours of the ban from 32% to 22%, however this effect was not significant (p = 0.16). More research is needed to understand how e-scooter use patterns are affected by the nighttime rental ban.

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.

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

Research into the bicycle level-of-service (BLOS) has been extensively conducted over the last three decades. This research has mostly focused on user perceptions of comfort to provide guidance for decision-makers and planners. Segments and nodes were studied first, followed by a network evaluation. Besides these investigations, several variables have also been utilized to depict the users’ perspectives within the BLOS field, along with other cycling research domains that simultaneously scrutinized the users’ preferences. This review investigates the variables and indices employed in the BLOS area in relation to the field of bicycle flow and comfort research. Despite general agreement among existing BLOS variables and the adopted indices, several important research gaps remain to be filled. First, BLOS indices are often categorized based on transport components, while scarce attention has been paid to BLOS studies in trip-end facilities such as bicycle parking facilities. The importance of these facilities has been highlighted instead within research related to comfort. Second, the advantages of separated bike facilities have been proven in many studies; however, scarce research has addressed the challenges associated with them (e.g., the heterogeneity within those facilities due to the presence of electric bikes and electric scooters). This issue is clearly noticeable within the research regarding flow studies. Furthermore, network evaluation (in comparison to segment and node indices) has been studied to a lesser extent, whereas issues such as connectivity can be evaluated mainly through a holistic approach to the system. This study takes one step toward demonstrating the importance of the integration of similar research domains in the BLOS field to eliminate the aforementioned shortcomings.

Accounting for drivers' bicycling frequency and familiarity with bicycle infrastructure treatments when evaluating safety

Municipalities in the United States often encourage bicycling for the health, economic, and environmental benefits by implementing new and innovative bicycle infrastructure treatments. Unfortunately, many treatments are unfamiliar to or misunderstood by drivers, especially when lacking explicit rules (e.g., shared lanes). To date, research has largely investigated bicycle infrastructure from a bicyclist's perspective, but with little research from the driver's perspective. The objective of this research is to utilize a driving simulator to investigate driver behavior towards different bicycle infrastructure treatments when driver behavior is not provoked by an interaction with bicyclists. More specifically, this research intends to investigate the impact of bicycling frequency and treatment familiarity, as well as the combined effect of the two, on driver behavior at each treatment type. The treatments investigated are shared lane markings called "sharrows", standard bike lanes, bike boxes, and merge lanes. The results show that bicycling frequency significantly affects the proportion of drivers making eye glances at treatments. In addition, drivers more familiar with bike boxes stopped significantly further back from bike boxes, and drivers more familiar with merge lanes performed the merge maneuver significantly earlier. Furthermore, driver speed and lane positioning at bike lanes was significantly affected by the combination of bike lane familiarity and bicycling frequency, but not individually. This research is a first step towards understanding driver behavior and expectation of bicyclists; an essential understanding for infrastructure treatments that do not provide physical barriers between bicycles and automobiles, and instead rely on driver behavior for safety.

Crash risk, crash exposure, and the built environment: A conceptual review

This paper reviews the literature on the relationship between the built environment and roadway safety, with a focus on studies that analyse small geographical units, such as census tracts or travel analysis zones. We review different types of built environment measures to analyse if there are consistent relationships between such measures and crash frequency, finding that for many built environment variables there are mixed or contradictory correlations. We turn to the treatment of exposure, because built environment measures are often used, either explicitly or implicitly, as measures of exposure. We find that because exposure is often not adequately controlled for, correlations between built environment features and crash rates could be due to either higher levels of exposure or higher rates of crash risk per unit of exposure. Then, we identify various built environment variables as either more related to exposure, more related to risk, or ambiguous, and recommend further targeted research on those variables whose relationship is currently ambiguous.

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.

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.