Cycling injury risk in London: A case-control study exploring the impact of cycle volumes, motor vehicle volumes, and road characteristics including speed limits

Unpacking the perceived cycling safety of road environment using street view imagery and cycle accident data

Cycling, as a routine mode of travel, offers significant benefits in promoting health, eliminating emissions, and alleviating traffic congestion. Many cities, including London, have introduced various policies and measures to promote 'active travel' in view of its manifold advantages. Nevertheless, the reality is not as desirable as expected. Existing studies suggest that cyclists' perceptions of cycling safety significantly hinder the broader adoption of cycling. Our study investigates the perceived cycling safety and unpacks the association between the cycling safety level and the road environment, taking London as a case study. First, we proposed novel cycling safety level indicators that incorporate both collision and injury risks, based on which a tri-tiered cycling safety level prediction spanning the entirety of London's road network has been generated with good accuracy. Second, we assessed the road environment by harnessing imagery features of street view reflecting the cyclist's perception of space and combined it with road features of cycle accident sites. Finally, associations between road environment features and cycling safety levels have been explained using SHAP values, leading to tailored policy recommendations. Our research has identified several key factors that contribute to a risky environment for cycling. Among these, the "second road effects," which refers to roads intersecting with the road where the accident occurred, is the most critical to cycling safety levels. This would also support and further contribute to the literature on road safety. Other results related to road greenery, speed limits, etc, are also discussed in detail. In summary, our study offers insights into urban design and transport planning, emphasising the perceived cycling safety of road environment.

Cycle fatalities in Delhi and their risk factors

There is a lack of research that investigates the risk factors of cycling in low- and middle-income countries. We present descriptive epidemiology of crashes that involved at least one fatal cyclist, over a three-year period (2016-2018) in Delhi, India. Next, we used an unmatched case-control approach to identify road design risk factors of cycle fatalities. Cases were road segments with at least one cycle fatality, and controls were those with none. We developed logistic regression models with cases and controls as binary outcomes to estimate the odds ratio of site characteristics. There were 167 crashes involving at least one cyclist fatality over the study period. Fatal cyclists were almost all males. They were less likely to be children or young adults and less likely to be residents of high-income localities, compared to the general population. One in ten crashes included more than one occupant on a cycle and 5% of fatal victims were pillion riders. Seventy percent crashes occurred at midblock, and majority were backend collisions. Regression shows that road width, traffic speed, and volume of heavy vehicles have strong positive effects on the fatality risk of cyclists. These results can inform strategies to design interventions for safety of cyclists.

Safety-in-Numbers for route choice of bicycle trips: A choice experiment approach for commuters

Safety-in-Numbers (SiN) implies that the risk of collision per road user is less when there are more road users. Although the available literature has confirmed the existence of SiN as an objective measure of safety, the effect on perceived safety, especially in the context of bicycle riders, has received much less attention. This study investigates the SiN effect on the perceived safety of bicycle riders that influences route choice behavior. A stated preference survey was performed in the South Delhi district of Delhi. The effect of attributes like posted speed limit, the volume of motorized traffic, bicycle infrastructure, and bicycle traffic/ crowding on route choice behavior was investigated. A binary logit model was developed to quantify the effect of these attributes on route choice. The results indicate that, in general, riders prefer routes with more bicycle traffic, hence validating SiN. But the effect does not always hold. For some riders, in the presence of dedicated bicycle infrastructure, when the perceived safety is higher, the presence of more bicycle traffic acts as crowding and demotivates riders to choose that route. The study also reveals that riders prefer routes with a low volume of motorized traffic and dedicated bicycle infrastructure. The outcomes suggest that a policy that encourages infrastructural development to provide lateral separation will encourage more people, hence increasing bicycle mode share as well as the perceived safety of riders.

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.

Assessing bicycle crash risks controlling for detailed exposure: A Copenhagen case study

A better understanding of factors associated with bicycle crashes can inform future efforts to limit crash risks. Many previous studies have analysed crash risk based on crash databases. However, these can only provide conditional information on crash risks. A few recent studies have included aggregate flow measures in their crash risk analyses. This study incorporates detailed bicycle flow to investigate factors related to bicycle crashes. Specifically, the study assesses the relative crash risk given various conditions by applying Palm distributions to control for exposure. The study specifically investigates the relationship between weather and time conditions and the relative risk of bicycle crashes at a disaggregate level. The study uses bicycle crash data from police reports of bicycle crashes from 2017-2020 in the greater Copenhagen area (N = 4877). The relations between the bicycle crash risk and the air temperature and wind speeds are found to be highly non-linear. The relative risk of bicycle crashes is elevated at low and high temperatures (0 °C ¿ x, x ¿ 21 °C). The results also show how decreasing visibility relates to increasing bicycle crash risk. Meanwhile, cycling during the early morning peak (7-8) and afternoon peak hours (15-18) is related to an increased risk of bicycle crashes. While some of the effects are likely spurious, they highlight specific conditions associated with higher relative risk. Finally, the results illustrate the increased risk at weekend night times when cyclists are likely to bike under the influence of alcohol. In conclusion, the analysis confirms that visibility, slippery surfaces, and intoxication are all factors associated with a higher risk of bicycle crashes. Hence, it is relevant to consider how infrastructure planning and preventive measures can modify the bicycle environment to minimise these risks.

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.

Further compelling evidence for safety-in-numbers: It is more than meets the eye

In the extant road safety literature, estimating safety-in-numbers is dominated by conventional cross-sectional methods in which active mode (pedestrian or cyclist) volume together with motorised traffic volume are present in regression models explaining active mode safety directly. There is "direct" evidence for safety-in-numbers when the coefficient associated with active mode volume is negative (safety improves as volume increases) or when it is smaller than one (safety decreases at a lower rate compared to the rate of increase in active mode volume). In this article we extend the concept of safety-in-numbers in the traffic safety field, introducing "indirect" safety-in-numbers, which constitutes a new form of evidence for this phenomenon. We provide empirical evidence to support this, discussing that using an approach based on heterogeneity in mean modelling-a form of random parameters (slopes) models-it is possible to reveal "indirect" safety-in-numbers effects. Therefore, such models can reveal further compelling evidence for safety-in-numbers. Accurate knowledge of safety-in-numbers effects (both direct and indirect) and their underlying mechanisms can help provide robust motives for promoting active travel and will have valuable implications for the design of road safety interventions.

Contraflows and cycling safety: Evidence from 22 years of data involving 508 one-way streets

Contraflow cycling on one-way streets is a low cost intervention that research shows can improve the cycling experience and increase participation. Evidence from several studies suggest that cyclists on contraflows have a lower crash risk. However, implementing contraflow cycling is often controversial, including in the United Kingdom (UK). In this paper we examine whether contraflow cycling on one-way streets alters crash or casualty rates for pedal cyclists. Focusing on inner London boroughs between 1998 and 2019, we identified 508 road segments where contraflow cycling was introduced on one-way streets. We identified road traffic crashes occurring within 10 m of these segments and labelled them as pre-contraflow, contraflow or contraflow removed crashes. We calculated rates using the number of crashes or casualties divided by the time exposed and generated 95 % confidence intervals using bootstrap resampling. We adjusted the rates for changes in cordon cycling volume and injury severity reporting. There were 1498 crashes involving pedal cyclists: 788 pre-contraflow, 703 contraflow and 7 following contraflow removal. There was no change in adjusted overall pedal cyclist crash or casualty rates when contraflow cycling was introduced. Proximity to a junction doubled the crash rate. The crash rate when pedal cyclists were travelling contraflow was the same as those travelling with flow. We have found no evidence that introducing contraflow cycling increases the crash or casualty rate for pedal cyclists. It is possible that such rates may indeed fall when contraflow cycling is introduced if more accurate spatio-temporal cycling volume data was available. We recommend all one-way streets are evaluated for contraflow cycling but encourage judicious junction design and recommend UK legislative change for mandatory-two-way cycling on one-way streets unless exceptional circumstances exist.

Cycling-related trauma admissions to the major trauma centre in the cycling capital of the United Kingdom

PURPOSE

This study aims to characterise cycling related injuries presenting to a major trauma centre located within a region with the highest rates of cycling in the UK.

METHODS

A retrospective analysis of cycling related trauma admissions occurring between January 2012 and June 2020 was performed. Our institution's electronic patient record system was used to collect relevant data for analysis including age, gender, mechanism of injury, Glasgow coma scale (GCS) on arrival, incident date and time, injured body regions, 30-day mortality, helmet use and intubation rate. Comparison was made between groups of patients based on mechanism of injury.

RESULTS

A total of 605 cycling related trauma cases were identified, with 52 being excluded due to incomplete data. The most common mechanism was 'fall from cycle' (53.5%). The 'cyclist v vehicle' group was associated with a significantly higher Injury Severity score (ISS), lower GCS and higher intubation rate. Helmet wearers were significantly older than non-wearers and helmet use was associated with a significantly reduced risk of head injury, lower ISS and intubation rate and a higher GCS.

DISCUSSION

With a likely increase in future cycling uptake, it is crucial that effective interventions are implemented to improve the safety of cyclists. The findings of this study may be used to guide any such intervention. A multi-faceted strategy involving driver and cyclist education, effective road infrastructure changes and helmet promotion campaigns specifically targeting the younger generation could be employed.

Pedestrian injuries in collisions with pedal cycles in the context of increased active travel: Trends in England, 2005-2015

INTRODUCTION

Increasing levels of active travel in the population brings many public health benefits, but may also change the risks of road injury for different road users. We examined changes in rates of pedestrian injuries resulting from collisions with pedal cycles and motor vehicles in England during 2005-2015, a period of increased cycling activity, and described the gender, age distribution and locations of pedestrians injured in collisions with pedal cycles and motor vehicles.

METHODS

Collisions data were obtained from police STATS19 datasets. We used two measures of cycle/motor vehicle use; miles per annum, and estimated average travel time, and assessed evidence for trends towards increase over time using Poisson regression analysis.

RESULTS

There were 3414 pedestrians injured in collisions with one or more pedal cycles in England during 2005-2015, 763 of whom were killed or seriously injured (KSI). This accounted for 1.3% of the total pedestrians KSI from all vehicles. Of those KSI in collisions with cycles, 62% were female; 42% over the age of 60; 26% were on the footway or verge and 24% were on a pedestrian crossing. There was a 6% (IRR 1.056; 95% CI 1.032-1.080, p < 0.001) annual increase in the pedestrian KSI rate per billion vehicle miles cycled in England over the time span. This increase was disproportionate to the increase in cycle use measured by vehicle miles or time spent cycling.

CONCLUSIONS

Increases in cycling were associated with disproportionate increases in pedestrian injuries in collisions with pedal cycles in England, although these collisions remain a very small proportion of all road injury. Increased active travel is essential for meeting a range of public health goals, but needs to be planned for with consideration for potential impact on pedestrians, particularly older citizens.

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.

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.

Cycling-related orthopaedic fractures admitted to the Major Trauma Centre in the cycling capital of the UK

INTRODUCTION

The popularity of cycling in the United Kingdom is increasing, with a further rise likely due to recent government cycling promotion schemes. This study aims to characterise fractures sustained due to cycling-related collisions in patients presenting to a Major Trauma Centre, in the region with the highest cycling rates in the United Kingdom.

METHODS

A retrospective analysis of cycling injuries presenting to our centre between January 2012 and December 2020 was performed using a prospectively collected electronic database. Comparison of fracture characteristics was made according to patient age and mechanism of injury (collision with a motorised vehicle versus collision with a non-motorised object.).

RESULTS

Of the 737 patients who suffered a cycling-related injury, 292 (39.6%) suffered at least 1 fracture to the appendicular skeleton. Overall, fractures were most commonly seen in those over 50 years of age. Upper limb fractures were more common than lower limb fractures. Fractures sustained during motorised injuries were more likely to require surgical intervention than those sustained during non-motorised collisions.

CONCLUSION

This study provides valuable information regarding the nature, epidemiology and treatment of fractures sustained following cycling-related accidents, adding to the paucity of similar literature in the field. Given the likely increase in future cycling uptake, our results are important to clinicians treating patients with cycling-related injuries and policymakers designing safety interventions.

Real-Time Nanoscopic Rider Safety System for Smart and Green Mobility Based upon Varied Infrastructure Parameters

To create a safe bicycle infrastructure system, this article develops an intelligent embedded learning system using a combination of deep neural networks. The learning system is used as a case study in the Northumbria region in England’s northeast. It is made up of three components: (a) input data unit, (b) knowledge processing unit, and (c) output unit. It is demonstrated that various infrastructure characteristics influence bikers’ safe interactions, which is used to estimate the riskiest age and gender rider groups. Two accurate prediction models are built, with a male accuracy of 88 per cent and a female accuracy of 95 per cent. The findings concluded that different infrastructures pose varying levels of risk to users of different ages and genders. Certain aspects of the infrastructure are hazardous to all bikers. However, the cyclist’s characteristics determine the level of risk that any infrastructure feature presents. Following validation, the built learning system is interoperable under various scenarios, including current heterogeneous and future semi-autonomous and autonomous transportation systems. The results contribute towards understanding the risk variation of various infrastructure types. The study’s findings will help to improve safety and lead to the construction of a sustainable integrated cycling transportation system.

Configurations of underreported cyclist-motorised vehicle and single cyclist collisions: Analysis of a self-reported survey

Lower severity cycling collisions, and single cyclist collisions (or single bicycle crashes) are significantly underreported in police statistics, introducing biases into the types of collisions that are available for analysis. Furthermore, many lower severity collisions do not appear in other collision data sources (e.g. hospital and insurance data). This in turn affects priorities for cyclist safety and puts an underemphasis on certain collision types. Due to an absence of data, little is known of the configurations of unreported collisions. In this paper, data from a recent self-reporting survey of cycling collisions in Ireland is used to provide details of cyclist collisions with motorised vehicles and single cyclist collisions, with the inclusion of unreported collision types. Pre-crash scenarios and impact configurations for cyclist collisions with bonnet-type vehicles, and collision factors and fall types for single cyclist collisions are coded. Injury patterns and police underreporting levels are compared, and representative collision scenarios are identified. This study highlights the relative importance of collisions resulting from the cyclist and vehicle travelling in the same direction, specifically, nearside-hook, vehicle lane changing, and overtaking manoeuvres are emphasised. Furthermore, cases involving the cyclist struck from the side by vehicle fronts comprise a smaller share than previous studies. Specifically, side to side impacts, impacts between the front of the cyclist/bicycle and the side of the vehicle, and impacts with open(ing) doors emerge as important impact configurations with the inclusion of self-reported cases. For single cyclist collisions, the importance of loss of traction of the tyres due to slippery road conditions and interactions with tram tracks and kerbs are emphasised. Fall types differ between single cyclist collision scenarios and are related to differences in injury severity. These findings add to existing knowledge for fatal and higher severity collisions, demonstrating that cyclist safety priorities change with inclusion of underreported, and lower severity collisions. The findings are particularly relevant to road infrastructural planners, as well as in the fields of injury biomechanics, and automated vehicle safety (ADAS). Representative scenarios for collisions with bonnet-type vehicles and single cyclist collisions have been identified, allowing for their future inclusion in development of collision and injury prevention strategies. The dataset generated in this study is available from the authors on reasonable request.

Cycling injury risk in Britain: A case-crossover study of infrastructural and route environment correlates

This paper examines infrastructural and route environment correlates of cycling injury risk in Britain. We used a case-crossover design, randomly selecting control sites from modelled cyclist routes, comparing these with sites where cyclists were injured. We then used conditional logistic regression for matched case-control groups modelling to compare characteristics of control and injury sites. Intersections were strongly associated with injury risk. High streets were associated with an elevated injury risk in final adjusted models, as was road type being primary, and a more downhill gradient. Lower speed limits and lower motor traffic connectivity were initially associated with lower injury risk, but these effects were no longer statistically significant in adjusted models. Increased road width was associated with increased injury risk in all models. Increased injury risk was associated in all models with presence of bus lane (somewhat mitigated at stops), guardrail, and fuel station or parking lot. Presence of parked cars in street view data raised injury risk in fully adjusted models, as did congestion (measured by low morning peak speeds), while higher volumes of people cycling along the street reduced it. In fully adjusted models, a statistically significant increase in risk was associated with presence of an on-road painted cycle lane. Most cycle lanes or tracks at control and injury sites were very poor, with narrow lanes, shared footways, and lack of protection at junctions. Given findings from other studies showing protective effects of cycle infrastructure, Britain must create higher quality cycle provision, avoiding narrow on-road painted lanes.

Association of Infrastructure and Route Environment Factors with Cycling Injury Risk at Intersection and Non-Intersection Locations: A Case-Crossover Study of Britain

Objective: This paper examines infrastructural and route environment correlates of cycling injury risk in Britain for commuters riding in the morning peak. Methods: The study uses a case-crossover design which controls for exposure. Control sites from modelled cyclist routes (matched on intersection status) were compared with sites where cyclists were injured. Conditional logistic regression for matched case–control groups was used to compare characteristics of control and injury sites. Results: High streets (defined by clustering of retail premises) raised injury odds by 32%. Main (Class A or primary) roads were riskier than other road types, with injury odds twice that for residential roads. Wider roads, and those with lower gradients increased injury odds. Guard railing raised injury odds by 18%, and petrol stations or car parks by 43%. Bus lanes raised injury odds by 84%. As in other studies, there was a ‘safety in numbers’ effect from more cyclists. Contrary to other analysis, including two recent studies in London, we did not find a protective effect from cycle infrastructure and the presence of painted cycle lanes raised injury odds by 54%. At intersections, both standard and mini roundabouts were associated with injury odds several times higher than other intersections. Presence of traffic signals, with or without an Advanced Stop Line (‘bike box’), had no impact on injury odds. For a cyclist on a main road, intersections with minor roads were riskier than intersections with other main roads. Conclusions: Typical cycling environments in Britain put cyclists at risk, and infrastructure must be improved, particularly on busy main roads, high streets, and bus routes.

Studying bicyclists' perceived level of safety using a bicycle simulator combined with immersive virtual reality

There is a need for methods that provide a better understanding of bicyclists' perceived safety and preferences on currently unavailable and/or unknown bicycle facilities. Different survey methods have been used to study bicyclists' behavior, experiences, and preferences; ranging from verbally described facilities to surveys including images and videos. Virtual Reality (VR) experiments blur the boundaries between stated preference (SP) surveys and revealed preference (RP) surveys and provide a realistic sense of design. This research introduces a novel research method in bicycling research and discusses the results of an experiment using a bicycle simulator combined with immersive VR. In total, 150 participants participated in this experiment and were asked about demographics and perceptions and preferences after bicycling in five different environments with an instrumented bicycle in VR. A 5 × 2 mixed design was used with bicycling environment as within-subject factor and pedestrian / traffic volume as between-subject factor. ANOVA tests revealed how each environment and ambient pedestrian / traffic volume affected perceived level of safety (PLOS) and willingness to bicycle (WTB). Pairwise comparison showed that participants felt safer bicycling on the segregated bicycle path compared to bicycling on the painted bicycle path on the road and roadside. There was no meaningful difference between WTB for less than 10 min and WTB for more than 10 min between bicycling on a painted bicycle path on the sidewalk and painted bicycle path on the road. PLOS and WTB ratings of men and women were not significantly different from each other. The older segment of the sample was more worried about roadside bicycling and bicycle commuters were more confident to ride on the roadside. Despite having several limitations, immersive 360-degree VR was found a powerful presentation tool to evaluate future street designs which can inform transport and urban planning.

At-risk-measure Sampling in Case-Control Studies with Aggregated Data

Transient exposures are difficult to measure in epidemiologic studies, especially when both the status of being at risk for an outcome and the exposure change over time and space, as when measuring built-environment risk on transportation injury. Contemporary "big data" generated by mobile sensors can improve measurement of transient exposures. Exposure information generated by these devices typically only samples the experience of the target cohort, so a case-control framework may be useful. However, for anonymity, the data may not be available by individual, precluding a case-crossover approach. We present a method called at-risk-measure sampling. Its goal is to estimate the denominator of an incidence rate ratio (exposed to unexposed measure of the at-risk experience) given an aggregated summary of the at-risk measure from a cohort. Rather than sampling individuals or locations, the method samples the measure of the at-risk experience. Specifically, the method as presented samples person-distance and person-events summarized by location. It is illustrated with data from a mobile app used to record bicycling. The method extends an established case-control sampling principle: sample the at-risk experience of a cohort study such that the sampled exposure distribution approximates that of the cohort. It is distinct from density sampling in that the sample remains in the form of the at-risk measure, which may be continuous, such as person-time or person-distance. This aspect may be both logistically and statistically efficient if such a sample is already available, for example from big-data sources like aggregated mobile-sensor data.

Data-driven strategies for optimal bicycle network growth

Urban transportation networks, from pavements and bicycle paths to streets and railways, provide the backbone for movement and socioeconomic life in cities. To make urban transport sustainable, cities are increasingly investing to develop their bicycle networks. However, it is yet unclear how to extend them comprehensively and effectively given a limited budget. Here we investigate the structure of bicycle networks in cities around the world, and find that they consist of hundreds of disconnected patches, even in cycling-friendly cities like Copenhagen. To connect these patches, we develop and apply data-driven, algorithmic network growth strategies, showing that small but focused investments allow to significantly increase the connectedness and directness of urban bicycle networks. We introduce two greedy algorithms to add the most critical missing links in the bicycle network focusing on connectedness, and show that they outmatch both a random approach and a baseline minimum investment strategy. Our computational approach outlines novel pathways from car-centric towards sustainable cities by taking advantage of urban data available on a city-wide scale. It is a first step towards a quantitative consolidation of bicycle infrastructure development that can become valuable for urban planners and stakeholders.

Using satellite imagery to estimate heavy vehicle volume for ecological injury analysis in India

A major limitation of road injury research in low- and-middle income countries is the lack of consistent data across the settings, such as traffic counts, to measure traffic risk. This study presents a novel method in which traffic volume of heavy vehicles - trucks and buses - is estimated by identifying these vehicles from satellite imagery of Google Earth. For Rajasthan state in India, a total of ∼44,000 such vehicles were manually identified and geo-located on national highways (NHs), with no distinction made between trucks and buses. To estimate population living in proximity to NHs, defined as those living within 1 km buffer of NH, we geocoded ∼45,000 villages and ∼300 cities using Google Maps Geocoding Application Programming Interface (API). We fitted a spatio-temporal Bayesian regression model with the number of road deaths at the district level as the outcome variable. We found a strong Pearson correlation of 0.84 (p < 0.001) between Google Earth estimates of heavy vehicles and freight vehicle counts reported by a national-level study for different road sections. The regression results show that the volume of heavy vehicles and rural population in proximity to highways are positively associated with fatality risk in the districts. These effects have been estimated after controlling for other modes of travel.

Integrated Impact Assessment of Active Travel: Expanding the Scope of the Health Economic Assessment Tool (HEAT) for Walking and Cycling

The World Health Organization’s Health Economic Assessment Tool (HEAT) for walking and cycling is a user-friendly web-based tool to assess the health impacts of active travel. HEAT, developed over 10 years ago, has been used by researchers, planners and policymakers alike in appraisals of walking and cycling policies at both national and more local scales. HEAT has undergone regular upgrades adopting the latest scientific evidence. This article presents the most recent upgrades of the tool. The health impacts of walking and/or cycling in a specified population are quantified in terms of premature deaths avoided (or caused). In addition to the calculation of benefits derived from physical activity, HEAT was recently expanded to include assessments of the burden associated with air pollution exposure and crash risks while walking or cycling. Further, the impacts on carbon emissions from mode shifts to active travel modes can now be assessed. The monetization of impacts using Value of Statistical Life and Social Costs of Carbon now uses country-specific values. As active travel inherently results in often substantial health benefits as well as not always negligible risks, assessments of active travel behavior or policies are incomplete without considering health implications. The recent developments of HEAT make it easier than ever to obtain ballpark estimates of health impacts and carbon emissions related to walking and cycling.

Safety effects of traffic lane and shoulder widths on two-lane undivided rural roads: A matched case-control study from Norway

This study estimates the effects of lane and shoulder widths on occurrence of head-on and single-vehicle accidents on rural two-lane undivided roads in Norway while considering the differences between winter and non-winter accidents and their severity levels. A matched case-control method was applied to calculate the odds ratios for lane and shoulder width categories, while controlling for the effects of AADT and adjusting for the effects of region, speed limit, segment length, share of long vehicles in AADT and horizontal alignment. The study used a sample of 71,999 roadway segments identified in GIS and 1886 related accidents recorded by the police in five-year period. The results suggest that it is relevant to consider winter and non-winter accidents as well as severe and slight accidents separately when studying the effects of lane and shoulder widths on the occurrence of head-on and single-vehicle accidents. When examining lane and shoulder widths for all related accidents, the lane widths 1.50-2.50 m and shoulder widths 0.50-0.75 m were relatively safer than other categories on Norwegian two-lane rural undivided roads.

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.

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.

How does mode of travel affect risks posed to other road users? An analysis of English road fatality data, incorporating gender and road type

Background

Most analysis of road injuries examines the risk experienced by people using different modes of transport, for instance, pedestrian fatalities per-head or per-km. A small but growing field analyses the impact that the use of different transport modes has on other road users, for instance, injuries to others per-km driven.

Methods

This paper moves the analysis of risk posed to others forward by comparing six different vehicular modes, separating road types (major vs minor roads in urban vs rural settings). The comparison of risk posed by men and women for all these modes is also novel.

Results

Per-vehicle kilometre, buses and lorries pose much the highest risk to others, while cycles pose the lowest. Motorcycles pose a substantially higher per-km risk to others than cars. The fatality risk posed by cars or vans to ORUs per km is higher in rural areas. Risk posed is generally higher on major roads, although not in the case of lorries, suggesting a link to higher speeds. Men pose higher per-km risk to others than women for all modes except buses, as well as being over-represented among users of the most dangerous vehicles.

Conclusions

Future research should examine more settings, adjust for spatial and temporal confounders, or examine how infrastructure or route characteristics affect risk posed to others. Although for most victims the other vehicle involved is a car, results suggest policy-makers should also seek to reduce disproportionate risks posed by the more dangerous vehicles, for instance, by discouraging motorcycling. Finally, given higher risk posed to others by men across five of six modes analysed, policy-makers should consider how to reduce persistent large gender imbalances in jobs involving driving.

Association of injury related hospital admissions with commuting by bicycle in the UK: prospective population based study

OBJECTIVE

To determine whether bicycle commuting is associated with risk of injury.

DESIGN

Prospective population based study.

SETTING

UK Biobank.

PARTICIPANTS

230 390 commuters (52.1% women; mean age 52.4 years) recruited from 22 sites across the UK compared by mode of transport used (walking, cycling, mixed mode versus non-active (car or public transport)) to commute to and from work on a typical day.

MAIN OUTCOME MEASURE

First incident admission to hospital for injury.

RESULTS

5704 (2.5%) participants reported cycling as their main form of commuter transport. Median follow-up was 8.9 years (interquartile range 8.2-9.5 years), and overall 10 241 (4.4%) participants experienced an injury. Injuries occurred in 397 (7.0%) of the commuters who cycled and 7698 (4.3%) of the commuters who used a non-active mode of transport. After adjustment for major confounding sociodemographic, health, and lifestyle factors, cycling to work was associated with a higher risk of injury compared with commuting by a non-active mode (hazard ratio 1.45, 95% confidence interval 1.30 to 1.61). Similar trends were observed for commuters who used mixed mode cycling. Walking to work was not associated with a higher risk of injury. Longer cycling distances during commuting were associated with a higher risk of injury, but commute distance was not associated with injury in non-active commuters. Cycle commuting was also associated with a higher number of injuries when the external cause was a transport related incident (incident rate ratio 3.42, 95% confidence interval 3.00 to 3.90). Commuters who cycled to work had a lower risk of cardiovascular disease, cancer, and death than those who did not. If the associations are causal, an estimated 1000 participants changing their mode of commuting to include cycling for 10 years would result in 26 additional admissions to hospital for a first injury (of which three would require a hospital stay of a week or longer), 15 fewer first cancer diagnoses, four fewer cardiovascular disease events, and three fewer deaths.

CONCLUSION

Compared with non-active commuting to work, commuting by cycling was associated with a higher risk of hospital admission for a first injury and higher risk of transport related incidents specifically. These risks should be viewed in context of the health benefits of active commuting and underscore the need for a safer infrastructure for cycling in the UK.

Safety-in-numbers: An updated meta-analysis of estimates

Safety-in-numbers denotes the tendency for the number of accidents to increase less than in proportion to traffic volume. This paper updates a meta-analysis of estimates of safety-in-numbers published in 2017 (Elvik and Bjørnskau, Safety Science, 92, 274-282). Nearly all studies find safety-in-numbers, but the numerical estimates vary considerably. As virtually all studies are cross-sectional, it is not possible to determine if safety-in-numbers represents a causal relationship. Meta-regression analysis was performed to identify factors which may explain the large heterogeneity of estimates of safety-in-numbers. It was found that safety-in-numbers tends to be stronger for pedestrians than for cyclists, and stronger at the macro-level (e.g. citywide) than at the micro-level (e.g. in junctions). Recent studies find a stronger tendency towards safety-in-numbers than older studies.

A retrospective international study on factors associated with injury, discomfort and pain perception among cyclists

Although cycling has been associated with overuse/fatigue and acute injuries, there is lack of information regarding associated risk factors and prevention factors. The objective of the study was to determine the factors associated with injury, and perceptions of discomfort and pain in cyclists. A total of 739 cyclists completed an online questionnaire between February and October 2016. The questionnaire acquired information on participant demographics, characteristics related to cycling profile and fitness training, bike components and cycling posture, self-reported perceptions of comfort and pain, and injuries sustained in the last 12 months. Logistic regression models estimated odds ratios (OR) and 95% confidence intervals (95%CI) that examined factors associated with reporting overuse/fatigue injury, acute injury, body discomfort, saddle discomfort, and pain while cycling. Odds of reporting an overuse/fatigue injury increased when the cyclists complemented training with running (OR = 1.74; 95%CI = 1.03–2.91) or swimming (OR = 2.17; 95%CI = 1.19–3.88), and with reported pain while cycling (OR = 1.17; 95%CI = 1.05–3.69) and not cycling (OR = 1.76; 95%CI = 1.07–2.90). Odds of reporting an acute injury increased when biking to work (OR = 1.79; 95%CI = 1.07–2.86), and decreased with increased average cycling speed (1-km/h decrease OR = 0.93; 95%CI = 0.88–0.97), and compared to low-end bike, with the use of mid-range (OR = 0.25; 95%CI = 0.09–0.72) and high-end bike (OR = 0.34; 95%CI = 0.13–0.96). Although body discomfort was only associated with saddle discomfort and the presence of pain during cycling, saddle discomfort was also associated with biking to work (OR = 0.46; 95%CI = 0.22–0.88). Finally, pain perception was associated with a number of factors such as ride to work, core training, cycling experience, saddle discomfort, pain while not cycling. Numerous factors are associated with injury, and perceptions of discomfort and pain in cyclists. Such factors should be considered when developing training routines, bicycle maintenance best practices, and injury prevention programs.

Effects of Perceived Traffic Risks, Noise, and Exhaust Smells on Bicyclist Behaviour: An Economic Evaluation

Active mode (walking, bicycling, and their variants) users are exposed to various negative externalities from motor vehicle traffic, including injury risks, noise, and air pollutants. This directly harms the users of these modes and discourages their use, creating a self-reinforcing cycle of less active travel, more motorized travel, and more harmful effects. These impacts are widely recognized but seldom quantified. This study evaluates these impacts and their consequences by measuring the additional distances that bicyclists travel in order to avoid roads with heavy motor vehicle traffic, based on a sample of German-Austrian bicycle organization members (n = 491), and monetizes the incremental costs. The results indicate that survey respondents cycle an average 6.4% longer distances to avoid traffic impacts, including injury risks, air, and noise pollution. Using standard monetization methods, these detours are estimated to impose private costs of at least €0.24/cycle-km, plus increased external costs when travellers shift from non-motorized to motorized modes. Conventional transport planning tends to overlook these impacts, resulting in overinvestment in roadway expansions and underinvestments in other types of transport improvements, including sidewalks, crosswalks, bikelanes, paths, traffic calming, and speed reductions. These insights should have importance for transport planning and economics.

Who is responsible for global road safety? A cross-cultural comparison of Actor Maps

The traditional three 'E's approach to road safety (engineering, education, enforcement) has had, and will continue to have, a significant impact on road traffic casualty rates worldwide. Nevertheless, with rising motorisation in many countries, global fatality numbers have changed little over the past decade. Following calls for the application of sociotechnical systems thinking to the problem, we widen the road safety discussion with an additional four 'E's; economics, emergency response, enablement, and, the umbrella term for the approach taken, ergonomics. The research presents an application of Rasmussen's Risk Management Framework to the road safety systems of five distinct nations; Bangladesh, China, Kenya, the UK, and Vietnam. Following site visits, reviews of literature, and interviews with subject matter experts in each of the countries, a series of Actor Map models of the countries' road safety systems were developed. These are compared and discussed in terms of the wide variety of interconnecting organisations involved, their influences on road safety outcomes, the differences between nations, and the need to look beyond road users when designing road safety interventions.