Cyclist crash rates and risk factors in a prospective cohort in seven European cities

Unraveling the relation between cycling accidents and built environment typologies: Capturing spatial heterogeneity through a latent class discrete outcome model

Today, cities seek to transition to more sustainable transportation modes. Cycling is critical in this shift, promoting a more beneficial lifestyle for most. However, cyclists are exposed to many hazardous circumstances or environments, resulting in accidents, injuries, and even death. Transport authorities must understand why accidents occur, to reduce the risk of those who cycle. This study applies a new modeling framework to analyze cycling accident severities. We employ a latent class discrete outcome model, where classes are derived from a Gaussian-Bernoulli mixture, applied to data from Berlin, and augmented with volunteered geographic information. We jointly estimate model components, combining machine learning and econometric approaches, allowing for more intricate and flexible representations while maintaining interpretability. Results show the potential of our approach. Risk factors are indexed depending on where accidents occurred and their contribution. We can discover complex relations between specific built environments and accident characteristics and uncover differences in the impact of certain accident factors on one environment typology but not others. Using multiple data sources also proves helpful as an additional layer of knowledge, providing unique value to understand and model cycling accidents. Another critical aspect of our approach is the potential for simulation, where locations can be examined through simulated accident features to understand the inherent risk of various locations. These findings highlight the ability to capture heterogeneity in accidents and their relation to the built environment. Capturing such relations allows for more direct countermeasures to risky situations or policies to be designed, simulated, and targeted.

Risk Factors and Inequities in Transportation Injury and Mortality in the Canadian Census Health and Environment Cohorts (CanCHECs)

BACKGROUND

Road traffic injury contributes substantially to morbidity and mortality. Canada stands out among developed countries in not conducting a national household travel survey, leading to a dearth of national transportation mode data and risk calculations that have appropriate denominators. Since traffic injuries are specific to the mode of travel used, these risk calculations should consider travel mode.

METHODS

Census data on mode of commute is one of the few sources of these data for persons aged 15 and over. This study leveraged a national data linkage cohort, the Canadian Census Health and Environment Cohorts, that connects census sociodemographic and commute mode data with records of deaths and hospitalizations, enabling assessment of road traffic injury associations by indicators of mode of travel (commuter mode). We examined longitudinal (1996-2019) bicyclist, pedestrian, and motor vehicle occupant injury and fatality risk in the Canadian Census Health and Environment Cohorts by commuter mode and sociodemographic characteristics using Cox proportional hazards models within the working adult population.

RESULTS

We estimated positive associations between commute mode and same mode injury and fatality, particularly for bicycle commuters (hazard ratios for bicycling injury was 9.1 and for bicycling fatality was 11). Low-income populations and Indigenous people had increased injury risk across all modes.

CONCLUSIONS

This study shows inequities in transportation injury risk in Canada and underscores the importance of adjusting for mode of travel when examining differences between population groups.

Exploring temporal instability effects on bicyclist injury severities determinants for intersection and non-intersection-related crashes

Cycling is a sustainable and healthy mode of transportation with direct links to reducing traffic congestion, lowering greenhouse gas emissions, and improving air quality. However, from a safety perspective, bicyclists represent a risky road user group with a higher likelihood of sustaining severe injuries when involved in vehicle crashes. With various determinants known to affect bicyclist injury severity and vary across locations, this study investigates the factors affecting bicyclist injury severity and temporal instability, considering the location of crashes. More specifically, the objective of this study is to understand differences in injury severities of intersection and non-intersection-related single-bicycle-vehicle crashes using four year crash data from the state of Florida. Random parameters logit models with heterogeneity in the means and variances are developed to model bicyclist injury severity outcomes (no injury, minor injury, and severe injury) for intersection and non-intersection crashes. Several variables affecting injury severities are considered in model estimation, including weather, roadway, vehicle, driver, and bicyclist characteristics. The temporal stability of the model parameters is assessed for different locations and years using a series of likelihood ratio tests. Results indicate that the determinants of bicyclist injury severities change over time and location, resulting in different injury severities of bicyclists, with non-intersection crashes consistently resulting in more severe bicyclist injuries. Using a simulation-based out-of-sample approach, predictions are made to understand the benefits of replicating driving behaviour and facilities similar to intersections for non-intersection locations, which could benefit in reducing bicyclist injury severity probabilities.

Wider view over bicycle crashes: Complementing and extending bicycle crash statistics in urban areas using surveys

INTRODUCTION

In pursuit of sustainability goals, many cities are introducing measures to increase the usage of bicycles as a means of transportation. City planners aim to ensure that this increase does not lead to an increase in crashes, but must make corresponding infrastructure decisions with limited information. Sufficient data to perform a statistical analysis of location-specific crash frequencies is rarely available. For example, only approximately 10% of all bicycle crashes are reported to the police (Shinar et al., 2018). Therefore, urban planners often rely on expert opinion, which may lead to suboptimal prioritization and realization of infrastructure improvements.

METHOD

This paper demonstrates how surveys on bicycle crashes can be used to aid urban planners in making infrastructure decisions. In addition to confirming the location and characteristics of reported crashes, surveys can uncover characteristics of crashes that are not reported to the police, situations in which a crash almost occurred, and locations perceived by cyclists to be dangerous. Surveys also allow urban planners to investigate non-infrastructure related causes of crashes, such as the frequency with which individual cyclists use other modes of transportation.

PRACTICAL APPLICATIONS

The usefulness of surveys in the determination of urban cycling safety is demonstrated in this paper through analysis of survey results from the city of Zurich in 2018.

[Mobility and Urban Health]

Cities and communities form complex microcosms in which people with very different needs and opportunities live. The structural design and functionality of urban spaces have a significant impact on individual mobility and thus on the health and quality of life of the entire population. In recent decades, politicians and municipalities have accepted negative effects on people (especially vulnerable groups) and ecosystems as a price worth paying for ensuring mobility through car-friendly structures. The interconnection of health and sustainability aspects will be a central process component for the necessary transformation of urban structures in integrated urban and transport planning. Although there are many positive framework conditions and possible solutions in the international and national context, numerous processes need to be optimized and measures implemented on a large scale. In addition, the existing tools in urban and traffic planning must be further expanded to include health aspects more comprehensively. This requires readjustments in science, in municipal practice planning, in education and in interdisciplinary funding programs.

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.

Association of human mobility with road crashes for pandemic-ready safer mobility: A New York City case study

BACKGROUND

The COVID-19 pandemic has reshaped our cities in many ways. The number of motor vehicles on the road has plummeted during lockdowns, and an increasing number of people are turning to walking and biking. From a road safety perspective, the overall question is what effects the human behavior shift brings on the crash occurrence and, more importantly, how to support decision-makers on safer mobility policies?

METHOD

Based on anonymous mobile phone location and crash report data in New York City, this study attempts to provide some new insights by using survival analysis (the hazard function approach) to explore the effects of human mobility changes due to the pandemic on crashes that involve injuries and fatalities (of pedestrian, cyclist or motorist).

RESULTS

(1) the increased percentage of people staying at home improves pedestrian and cyclist safety, which adds evidence for making walking and cycling more appealing; (2) the increased percentage of people staying at home raises the likelihood of injuries for motor vehicle drivers, suggesting that it will be critical to monitor the driving behavior and establish new speed limits during the future pandemic waves and in the post-pandemic era as well; (3) non-work trips (e.g., shopping, recreation, personal business, etc.) are positively associated with crash injuries for motor vehicle drivers as well as pedestrian and cyclist; (4) human mobility factors were found not related to crash fatalities; (5) control NPIs implemented increased the motor vehicle drivers' crash risk.

Active mobility versus motorized transport? User choices and benefits for the society

Measures promoting active mobility - walking or cycling - are often seen as an effective strategy to meet multiple urban objectives. The advantages of such behavioural changes cover multiple dimensions at public and individual level, including positive impacts on health, safety, climate, economy, environment and air quality. However, there is still a considerable potential for increasing the uptake of active mobility in urban areas. This paper explores the determinants of active mobility choice and compares the demographic, socio-economic and cultural factors that influence it. The methodology combines extensive survey data, an EU-wide transport model and detailed indicators of external costs of transport with a Gradient Boosting Machine Learning approach. The model based scenarios quantify the benefit in terms of external costs savings from increasing active mobility shares. Such savings - at EU level, can reach the amount of 15 billion euro per year for a shift of 10% of trips to active mobility modes.

A Spatial Autoregressive Quantile Regression to Examine Quantile Effects of Regional Factors on Crash Rates

Spatial autocorrelation and skewed distribution are the most frequent issues in crash rate modelling analysis. Previous studies commonly focus on the spatial autocorrelation between adjacent regions or the relationships between crash rate and potentially risky factors across different quantiles of crash rate distribution, but rarely both. To overcome the research gap, this study utilizes the spatial autoregressive quantile (SARQ) model to estimate how contributing factors influence the total and fatal-plus-injury crash rates and how modelling relationships change across the distribution of crash rates considering the effects of spatial autocorrelation. Three types of explanatory variables, i.e., demographic, traffic networks and volumes, and land-use patterns, were considered. Using data collected in New York City from 2017 to 2019, the results show that: (1) the SARQ model outperforms the traditional quantile regression model in prediction and fitting performance; (2) the effects of variables vary with the quantiles, mainly classifying three types: increasing, unchanged, and U-shaped; (3) at the high tail of crash rate distribution, the effects commonly have sudden increases/decrease. The findings are expected to provide strategies for reducing the crash rate and improving road traffic safety.

Changes in shared and private e-scooter use in Brisbane, Australia and their safety implications

Shared electric scooter (e-scooter) schemes debuted in US cities in 2017 and have spread to many cities worldwide. Rider inexperience and the inexperience of other road users in interacting with e-scooters may be contributing to injuries. Shared e-scooters came to Brisbane, Australia, in November 2018 and our observational study in February 2019 found a high level of non-compliance with regulations by riders of shared, but not private, e-scooters. This paper examines whether e-scooter safety improved over time by comparing the numbers and behaviors of shared and private e-scooter riders with a follow-up observational study conducted in October 2019. Riders of e-scooters (and bicycles) were counted at six sites in inner-city Brisbane by trained observers over four weekdays. Type of e-scooter (private, Lime, Neuron), helmet use, gender, age group, riding location, time of day and presence of passengers were recorded. The number of shared e-scooters observed dropped from 711 in February to 495 in October but the number of private e-scooters increased from 90 to 269, resulting in a slight reduction in the total number of e-scooters. The correct helmet wearing rate increased non-significantly from 61.4% to 66.8% for shared e-scooters and remained high for riders of private e-scooters (95.5% in February and 94.3% in October). The percentage of e-scooters ridden on the road (which is illegal in central Brisbane) remained roughly the same (shared: 6.6% in February, 4.2% in October; private: 4.5% in February, 4.9% in October). The percentage of children and adolescents (illegally) riding shared e-scooters fell from 10.3% to 6.7%. The prevalence of any of these illegal behaviors among shared e-scooter riders fell significantly for shared e-scooter riders from 49.6% to 39.1% while the prevalence of illegal behaviors by other riders remained lower and did not change. The reduction in illegal behavior among shared e-scooter riders accompanied by the tripling of usage of private e-scooters suggests that e-scooter safety is likely to have improved.

An Analysis of Factors Affecting the Severity of Cycling Crashes Using Binary Regression Model

The increasing use of bicycles rises the interest in investigating the safety aspects of daily commuting. In this investigation, more than 14,000 cyclists’ injuries were analyzed to determine the relationship between severity, road infrastructure characteristics, and surface conditions using binary regression. Minor and major severity categories were distinguished. A binary equation consists of 28 factors is extracted. It has been found that each factor related to roadway characteristics has its negative and positive impacts on cyclist severity such as traffic control, location type, topography, and roadway divisions. Regarding the road surface components, good, paved, and marked roads are associated with a higher probability of major injuries due to the expected greater frequencies of cyclists on roads with good conditions. In conclusion, probabilities of major injuries are higher in urban areas, higher speed limits, signalized intersections, inclined topographies, one-way roads, and during the daytime which require more attention and better considerations.

Estimating walking and bicycling in Canada and their road collision fatality risks: The need for a national household travel survey

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Canadian Community Health Survey captures more bicycling/walking than the census.

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Across data sources, walking more common among women than men.

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Men had higher risk of a fatality than women for bicycling and walking.

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Both data sources have key limitations for measuring bicycling and walking.

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Implementing a national household travel survey should be a priority in Canada.

Canada does not conduct a national household travel survey, resulting in a data gap on walking and bicycling. These data are key to surveillance of physical activity and health, as well as in epidemiological injury risk calculations. This study explored the use of available national data sources, the Canadian census and the Canadian Community Health Survey (CCHS), to tally walking and bicycling and examine trends in fatality risk. Estimates of the percentage and number of Canadians walking or bicycling to work were calculated for 1996–2016 using the census. The CCHS was used to estimate the number and proportion of Canadians walking or bicycling for leisure (2000–2014) and to work or school (2008–2014). We combine these data with National Collision Database data on the number of pedestrian and bicyclist fatalities (1999–2017) and compare trends in fatality risk over time using each dataset. Across all data sources, walking was more common among women, while bicycling was more common among men. Men were at higher fatality risk than women. These results should be interpreted with caution given limitations this study identifies in census and CCHS data, including narrow definitions for bicycling behaviour, lack of detail regarding amount of use, and inconsistency of questions asked over time. A national household travel survey should be a priority for public health purposes in Canada.