Regional variations in pedal cyclist injuries in New Zealand: safety in numbers or risk in scarcity?

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.

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.

Evidence for the 'safety in density' effect for cyclists: validation of agent-based modelling results

The safety in numbers (SiN) effect for cyclists is widely observed but remains poorly understood. Although most studies investigating the SiN phenomenon have focused on behavioural adaptation to 'numbers' of cyclists in the road network, previous work in simulated environments has suggested SiN may instead be driven by increases in local cyclist spatial density, which prevents drivers from attempting to move through groups of oncoming cyclists. This study therefore set out to validate the results of prior simulation studies in a real-world environment. Time-gap analysis of cyclists passing through an intersection was conducted using 5 hours of video observation of a single intersection in the city of Melbourne, Australia, where motorists were required to 'yield' to oncoming cyclists. Results demonstrated that potential collisions between motor vehicles and cyclists reduced with increasing cyclists per minute passing through the intersection. These results successfully validate those observed under simulated conditions, supporting evidence of a proposed causal mechanism related to safety in density rather than SiN, per se. Implications of these results for transportation planners, cyclists and transportation safety researchers are discussed, suggesting that increased cyclist safety could be achieved through directing cyclists towards focused, strategic corridors rather than dispersed across a network.

Visualization and analysis of mapping knowledge domain of road safety studies

Mapping knowledge domain (MKD) is an important application of visualization technology in Bibliometrics, which has been extensively applied in psychology, medicine, and information science. In this paper we conduct a systematic analysis of the development trend on road safety studies based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles published between 2000 and 2018 using the MKD software tools VOSviewer and Sci2 Tool. Based on our analysis, we first present the annual numbers of articles, origin countries, main research organizations and groups as well as the source journals on road safety studies. We then report the collaborations among the main research organizations and groups using co-authorship analysis. Furthermore, we adopt the document co-citation analysis, keywords co-occurrence analysis, and burst detection analysis to visually explore the knowledge bases, topic distribution, research fronts and research trends on road safety studies. The proposed approach based on the visualized analysis of MKD can be used to establish a reference information and research basis for the application and development of methods in the domain of road safety studies. In particular, our results show that the knowledge bases (classical documents) of road safety studies in the last two decades have focused on five major areas of "Crash Frequency Data Analysis", "Driver Behavior Questionnaire", "Safety in Numbers for Walkers and Bicyclists", "Road Traffic Injury and Prevention", and "Driving Speed and Road Crashes". Among the research topics, the five dominant clusters are "Causation and Injury Severity Analysis of Road Accidents", "Epidemiologic Study and Prevention of Road Traffic Injury", "Intelligent Transportation System and Active Safety", "Young drivers' driving behavior and psychology", and "Older drivers' psychological and physiological characteristics". Finally, the burst keywords in research trends include Cycling, Intelligent Transportation Systems, and Distraction.

Contextualising Safety in Numbers: a longitudinal investigation into change in cycling safety in Britain, 1991-2001 and 2001-2011

INTRODUCTION

The 'Safety in Numbers' (SiN) phenomenon refers to a decline of injury risk per time or distance exposed as use of a mode increases. It has been demonstrated for cycling using cross-sectional data, but little evidence exists as to whether the effect applies longitudinally -that is, whether changes in cycling levels correlate with changes in per-cyclist injury risks.

METHODS

This paper examines cross-sectional and longitudinal SiN effects in 202 local authorities in Britain, using commuting data from 1991, 2001 and 2011 censuses plus police -recorded data on 'killed and seriously injured' (KSI) road traffic injuries. We modelled a log-linear relationship between number of injuries and number of cycle commuters. Second, we conducted longitudinal analysis to examine whether local authorities where commuter cycling increased became safer (and vice versa).

RESULTS

The paper finds a cross-sectional SiN effect exists in the 1991, 2001 and 2011 censuses. The longitudinal analysis also found a SiN effect, that is, places where cycling increased were more likely to become safer than places where it had declined. Finally, these longitudinal results are placed in the context of changes in pedestrian, cyclist and motorist safety. While between 1991 and 2001 all modes saw declines in KSI risk (37% for pedestrians, 36% for cyclists and 27% for motor vehicle users), between 2001 and 2011 pedestrians and motorists saw even more substantial declines (41% and 49%), while risk for cyclists increased by 4%.

CONCLUSION

The SiN mechanism does seem to operate longitudinally as well as cross-sectionally. However, at a national level between 2001-11 it co-existed with an increase in cyclist injury risk both in absolute terms and in relation to other modes.

Understanding bicycling in cities using system dynamics modelling

BACKGROUND

Increasing urban bicycling has established net benefits for human and environmental health. Questions remain about which policies are needed and in what order, to achieve an increase in cycling while avoiding negative consequences. Novel ways of considering cycling policy are needed, bringing together expertise across policy, community and research to develop a shared understanding of the dynamically complex cycling system. In this paper we use a collaborative learning process to develop a dynamic causal model of urban cycling to develop consensus about the nature and order of policies needed in different cycling contexts to optimise outcomes.

METHODS

We used participatory system dynamics modelling to develop causal loop diagrams (CLDs) of cycling in three contrasting contexts: Auckland, London and Nijmegen. We combined qualitative interviews and workshops to develop the CLDs. We used the three CLDs to compare and contrast influences on cycling at different points on a "cycling trajectory" and drew out policy insights.

RESULTS

The three CLDs consisted of feedback loops dynamically influencing cycling, with significant overlap between the three diagrams. Common reinforcing patterns emerged: growing numbers of people cycling lifts political will to improve the environment; cycling safety in numbers drives further growth; and more cycling can lead to normalisation across the population. By contrast, limits to growth varied as cycling increases. In Auckland and London, real and perceived danger was considered the main limit, with added barriers to normalisation in London. Cycling congestion and "market saturation" were important in the Netherlands.

CONCLUSIONS

A generalisable, dynamic causal theory for urban cycling enables a more ordered set of policy recommendations for different cities on a cycling trajectory. Participation meant the collective knowledge of cycling stakeholders was represented and triangulated with research evidence. Extending this research to further cities, especially in low-middle income countries, would enhance generalizability of the CLDs.

Bicycling injury hospitalisation rates in Canadian jurisdictions: analyses examining associations with helmet legislation and mode share

OBJECTIVES

The purpose of this study was to calculate exposure-based bicycling hospitalisation rates in Canadian jurisdictions with different helmet legislation and bicycling mode shares, and to examine whether the rates were related to these differences.

METHODS

Administrative data on hospital stays for bicycling injuries to 10 body region groups and national survey data on bicycling trips were used to calculate hospitalisation rates. Rates were calculated for 44 sex, age and jurisdiction strata for all injury causes and 22 age and jurisdiction strata for traffic-related injury causes. Inferential analyses examined associations between hospitalisation rates and sex, age group, helmet legislation and bicycling mode share.

RESULTS

In Canada, over the study period 2006-2011, there was an average of 3690 hospitalisations per year and an estimated 593 million annual trips by bicycle among people 12 years of age and older, for a cycling hospitalisation rate of 622 per 100 million trips (95% CI 611 to 633). Hospitalisation rates varied substantially across the jurisdiction, age and sex strata, but only two characteristics explained this variability. For all injury causes, sex was associated with hospitalisation rates; females had rates consistently lower than males. For traffic-related injury causes, higher cycling mode share was consistently associated with lower hospitalisation rates. Helmet legislation was not associated with hospitalisation rates for brain, head, scalp, skull, face or neck injuries.

CONCLUSIONS

These results suggest that transportation and health policymakers who aim to reduce bicycling injury rates in the population should focus on factors related to increased cycling mode share and female cycling choices. Bicycling routes designed to be physically separated from traffic or along quiet streets fit both these criteria and are associated with lower relative risks of injury.

Exposure measurement in bicycle safety analysis: A review of the literature

BACKGROUND

Cycling, as an active mode of transportation, has well-established health benefits. However, the safety of cyclists in traffic remains a major concern. In-depth studies of potential risk factors and safety outcomes are needed to ensure the most appropriate actions are taken to improve safety. However, the lack of reliable exposure data hinders meaningful analysis and interpretation. In this paper, we review the bicycle safety literature reporting different methods for measuring cycling exposure and discuss their findings.

METHODS

A literature search identified studies on bicycle safety that included a description of how cycling exposure was measured, and what exposure units were used (e.g. distance, time, trips). Results were analyzed based on whether retrospective or prospective measurement of exposure was used, and whether safety outcomes controlled for exposure.

RESULTS

We analyzed 20 papers. Retrospective studies were dominated by major bicycle accidents, whereas the prospective studies included minor and major bicycle accidents. Retrospective studies indicated higher incidence rates (IR) of accidents for men compared to women, and an increased risk of injury for cyclists aged 50 years or older. There was a lack of data for cyclists younger than 18 years. The risk of cycling accidents increased when riding in the dark. Wearing visible clothing or a helmet, or having more cycling experience did not reduce the risk of being involved in an accident. Better cyclist-driver awareness and more interaction between car driver and cyclists, and well maintained bicycle-specific infrastructure should improve bicycle safety.

CONCLUSION

The need to include exposure in bicycle safety research is increasingly recognized, but good exposure data are often lacking, which makes results hard to interpret and compare. Studies including exposure often use a retrospective research design, without including data on minor bicycle accidents, making it difficult to compare safety levels between age categories or against different types of infrastructure. Future research should focus more on children and adolescents, as this age group is a vulnerable population and is underrepresented in the existing literature.

Reconsidering the safety in numbers effect for vulnerable road users: an application of agent-based modeling

OBJECTIVE

Increasing levels of active transport provide benefits in relation to chronic disease and emissions reduction but may be associated with an increased risk of road trauma. The safety in numbers (SiN) effect is often regarded as a solution to this issue; however, the mechanisms underlying its influence are largely unknown. We aimed to (1) replicate the SiN effect within a simple, simulated environment and (2) vary bicycle density within the environment to better understand the circumstances under which SiN applies.

METHODS

Using an agent-based modeling approach, we constructed a virtual transport system that increased the number of bicycles from 9% to 35% of total vehicles over a period of 1,000 time units while holding the number of cars in the system constant. We then repeated this experiment under conditions of progressively decreasing bicycle density.

RESULTS

We demonstrated that the SiN effect can be reproduced in a virtual environment, closely approximating the exponential relationships between cycling numbers and the relative risk of collision as shown in observational studies. The association, however, was highly contingent upon bicycle density. The relative risk of collisions between cars and bicycles with increasing bicycle numbers showed an association that is progressively linear at decreasing levels of density.

CONCLUSIONS

Agent-based modeling may provide a useful tool for understanding the mechanisms underpinning the relationships previously observed between volume and risk under the assumptions of SiN. The SiN effect may apply only under circumstances in which bicycle density also increases over time. Additional mechanisms underpinning the SiN effect, independent of behavioral adjustment by drivers, are explored.

The role of conspicuity in preventing bicycle crashes involving a motor vehicle

Background: Bicycle use, despite its proven health and other benefits, is rarely part of everyday travel for many people due to the perceived risk of injury from collision crashes. This article investigated the role of physical vs. attention conspicuity in preventing bicycle crashes involving a motor vehicle in New Zealand. Methods: The Taupo Bicycle Study involved 2590 adult cyclists recruited in 2006 (43.1% response rate) and followed for bicycle crash outcomes through linkage to four national databases. A composite measure of physical conspicuity was created using latent class analysis based on the use of fluorescent colours, lights and reflective materials, and the main colour of top, helmet and bike frame. Attention conspicuity was assessed based on regional differences in travel patterns and the amount of riding in a bunch. Cox regression modelling for repeated events was performed with multivariate adjustments. Results: During a median follow-up period of 6.4 years, 162 participants experienced 187 bicycle–motor vehicle crashes. The crash risk was not predicted by the four latent classes identified and the amount of bunch riding but was higher in Auckland, the region with the lowest level of bicycle use relative to car use. In subgroup analyses, compared to other latent classes, the most physically conspicuous group had a higher risk in Auckland but a lower risk in other regions. Conclusion: Conspicuity aids may not be effective in preventing bicycle–motor vehicle crashes in New Zealand, particularly in Auckland, where attention conspicuity is low.

The societal costs and benefits of commuter bicycling: simulating the effects of specific policies using system dynamics modeling

BACKGROUND

Shifting to active modes of transport in the trip to work can achieve substantial co-benefits for health, social equity, and climate change mitigation. Previous integrated modeling of transport scenarios has assumed active transport mode share and has been unable to incorporate acknowledged system feedbacks.

OBJECTIVES

We compared the effects of policies to increase bicycle commuting in a car-dominated city and explored the role of participatory modeling to support transport planning in the face of complexity.

METHODS

We used system dynamics modeling (SDM) to compare realistic policies, incorporating feedback effects, nonlinear relationships, and time delays between variables. We developed a system dynamics model of commuter bicycling through interviews and workshops with policy, community, and academic stakeholders. We incorporated best available evidence to simulate five policy scenarios over the next 40 years in Auckland, New Zealand. Injury, physical activity, fuel costs, air pollution, and carbon emissions outcomes were simulated.

RESULTS

Using the simulation model, we demonstrated the kinds of policies that would likely be needed to change a historical pattern of decline in cycling into a pattern of growth that would meet policy goals. Our model projections suggest that transforming urban roads over the next 40 years, using best practice physical separation on main roads and bicycle-friendly speed reduction on local streets, would yield benefits 10-25 times greater than costs.

CONCLUSIONS

To our knowledge, this is the first integrated simulation model of future specific bicycling policies. Our projections provide practical evidence that may be used by health and transport policy makers to optimize the benefits of transport bicycling while minimizing negative consequences in a cost-effective manner. The modeling process enhanced understanding by a range of stakeholders of cycling as a complex system. Participatory SDM can be a helpful method for integrating health and environmental outcomes in transport and urban planning.

The role of multilevel factors in geographic differences in bicycle crash risk: a prospective cohort study

BACKGROUND

Regular cycling plays an important role in increasing physical activity levels but raises safety concerns for many people. While cyclists bear a higher risk of injury than most other types of road users, the risk differs geographically. Auckland, New Zealand's largest urban region, has a higher injury risk than the rest of the country. This paper identified underlying factors at individual, neighbourhood and environmental levels and assessed their relative contribution to this risk differential.

METHODS

The Taupo Bicycle Study involved 2590 adult cyclists recruited in 2006 and followed over a median period of 4.6 years through linkage to four national databases. The Auckland participants were compared with others in terms of baseline characteristics, crash outcomes and perceptions about environmental determinants of cycling. Cox regression modelling for repeated events was performed with multivariate adjustments.

RESULTS

Of the 2554 participants whose addresses could be mapped, 919 (36%) resided in Auckland. The Auckland participants were less likely to be Māori but more likely to be socioeconomically advantaged and reside in an urban area. They were less likely to cycle for commuting and off-road but more likely to cycle in the dark and in a bunch, use a road bike and use lights in the dark. They had a higher risk of on-road crashes (hazard ratio: 1.47; 95% CI: 1.22, 1.76), of which 53% (95% CI: 20%, 72%) was explained by baseline differences, particularly related to cycling off-road, in the dark and in a bunch and residing in urban areas. They were more concerned about traffic volume, speed and drivers' behaviour.

CONCLUSIONS

The excess crash risk in Auckland was explained by cycling patterns, urban residence and factors associated with the region's car-dominated transport environment.

Incidence, risk, and protective factors of bicycle crashes: findings from a prospective cohort study in New Zealand

OBJECTIVE

To estimate the incidence and risk of medically or police attended bicycle crashes in a prospective cohort study in New Zealand.

METHOD

The Taupo Bicycle Study involved 2590 adult cyclists recruited from the country's largest cycling event in 2006 and followed over a median period of 4.6 years through linkage to four administrative databases. Incidence rates with Poisson distribution confidence intervals were computed and Cox regression modelling for repeated events was performed.

RESULTS

The 66 on-road crashes and 10 collisions per 1000 person-years corresponded to 240 crashes and 38 collisions per million hours spent road cycling. The risk increased by 6% and 8% respectively for an extra cycling hour each week. There were 50 off-road crashes per 1000 person-years. Residing in urban areas and in Auckland (region with the lowest level of cycling), riding in a bunch, using a road bike and experiencing a previous crash predicted a higher risk. Habitual use of conspicuity aids appeared to lower the risk.

CONCLUSION

The risk is higher in urban areas and where cycling is less common, and increased by bunch riding and previous crashes. These findings alongside the possible protective effect of conspicuity aids suggest promising approaches to improving cycle safety.

Injury incidence rates of cyclists compared to pedestrians, car occupants and powered two-wheeler riders, using a medical registry and mobility data, Rhône County, France

PURPOSE

In France, the bicycle's modal share is stabilizing after a decline; in some of France's major cities, it has even increased since the 1990s. It is hence relevant to improve the knowledge of the injury risk associated with cycling, compared with other means of transport such as car, walking and powered two-wheeler (PTW) riding.

METHODS

The injury incidence rates were estimated by the ratio between accident data and mobility (exposure) data. Two accident data sources were used: police data and hospital-based data (outpatients and inpatients) from the Rhône road trauma Registry. This provides four injury categories: all-injury, hospitalization, serious-injury and fatal-injury. Exposure data were estimated from a regional household travel survey (RTS), using three measures of mobility: number of trips, distance traveled and time spent traveling. The survey was carried out from November 2005 to April 2006, on weekdays, outside school and public holidays; this seasonality was corrected using the 2007-2008 national household travel survey (NTS) that covered an entire year. Only information involving accidents and trips in, and residents of, the Rhône County (1.6 million inhabitants, including the city Lyon) were included in our study. Trends of injury rates were also evaluated in Greater Lyon, using previous travel surveys.

RESULTS

The PTW riders had the highest all-injury, hospitalization, serious-injury and fatal-injury rates, followed by cyclists, and lastly by pedestrians and car occupants. The rates between men and women seemed similar among pedestrians and among car occupants. For car occupants, pedestrians and cyclists, the age group 18-25 years had higher all-injury rate compared with the age group 25-65 years. On the contrary, the age group≥65 years seemed to have higher hospitalization and serious-injury rates, compared with the age group 25-65 years. For cyclists, the injury rates seemed higher in non-dense areas than in dense areas. Between 1996-1997 and 2005-2006 and with regards to time spent traveling, the all-injury, serious-injury and fatal-injury rates seemed to have decreased for car occupants and cyclists.

CONCLUSION

The higher risk for PTW riders is confirmed and quantified; it is very high. Decrease in injury rates seems more marked for cyclists; this may indicate the "safety in numbers" effect. Countermeasures for improving road safety could be implemented, especially for vulnerable road user types. However, they will not be sufficient to fill in the gap between the much higher risk for PTW riders and that of car occupants. Exposure-based injury rates can be a tool for monitoring and evaluating the effectiveness of policies and programs, and for comparisons between countries.

Temporal, seasonal and weather effects on cycle volume: an ecological study

BACKGROUND

Cycling has the potential to provide health, environmental and economic benefits but the level of cycling is very low in New Zealand and many other countries. Adverse weather is often cited as a reason why people do not cycle. This study investigated temporal and seasonal variability in cycle volume and its association with weather in Auckland, New Zealand's largest city.

METHODS

Two datasets were used: automated cycle count data collected on Tamaki Drive in Auckland by using ZELT Inductive Loop Eco-counters and weather data (gust speed, rain, temperature, sunshine duration) available online from the National Climate Database. Analyses were undertaken using data collected over one year (1 January to 31 December 2009). Normalised cycle volumes were used in correlation and regression analyses to accommodate differences by hour of the day and day of the week and holiday.

RESULTS

In 2009, 220,043 bicycles were recorded at the site. There were significant differences in mean hourly cycle volumes by hour of the day, day type and month of the year (p < 0.0001). All weather variables significantly influenced hourly and daily cycle volumes (p < 0.0001). The cycle volume increased by 3.2% (hourly) and 2.6% (daily) for 1°C increase in temperature but decreased by 10.6% (hourly) and 1.5% (daily) for 1 mm increase in rainfall and by 1.4% (hourly) and 0.9% (daily) for 1 km/h increase in gust speed. The volume was 26.2% higher in an hour with sunshine compared with no sunshine, and increased by 2.5% for one hour increase in sunshine each day.

CONCLUSIONS

There are temporal and seasonal variations in cycle volume in Auckland and weather significantly influences hour-to-hour and day-to-day variations in cycle volume. Our findings will help inform future cycling promotion activities in Auckland.