Street Noise Relationship to Bicycling Road User Safety (original) (raw)
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Research Article: Evidence on Why Bike-Friendly Cities Are Safer for All Road Users
Environmental Practice, 2011
Giventhegrowingevidencesuggestingthatcitieswithhigherbicyclingratesfindlowerfatalityrates,we examineroadsafetydatafrom24Californiacities.Thisanalysisincludedaccountingforcrashesacross allseveritylevelsbutalsoforthreedifferentclassesofroadusers:vehicleoccupants,pedestrians,and bicyclists.Additionally,welookedatissuesofstreetandstreetnetworkdesigntoseewhatrolethese characteristicsmightplayinaffectingroadsafetyoutcomes. Overall, high bicycling cities generally show a much lower risk of fatal crashes for all road users when compared to most of the other cities in our database. The fact that this pattern of low fatality risk is constant for all classes of road users strongly suggests that the crashes are taking place at lower speeds.The most notable difference found between the safer and less safe cities was the density of street intersections. While we do not yet have the data to fully disentangle the various contributing factors, our results strongly suggest that safety benefits for all road users can be derived from a combination of the same steps that tend to attract more bicyclists. In other words, improving the streetstobetteraccommodatebicyclesmayinfactleadtoaself-reinforcingcyclethatcanhelpenhance overallsafetyforallroadusers. Journeytoworkdatawascollectedalongwithstreetnetworkmeasures,streetcharacteristics, socioeconomic data, traffic flow information, and over 230,000 individual crash records from elevenyearsof crash data. All of this information was geo-coded in a GIS database with the intentionoffacilitatingamorecomprehensivespatialanalysis.
Cyclists′ Exposure to Road Traffic Noise: A Comparison of Three North American and European Cities
Acoustics
According to the World Health Organization, high levels of exposure to road traffic noise are associated with adverse health effects. Earlier studies suggest that cyclists are exposed to higher noise levels than motorists. Other studies have demonstrated that cyclists’ exposure to noise could vary significantly according to their routes. The aim of this study is to compare cyclists’ exposure to noise and their determinants in three cities. Three participants cycled equipped with noise dosimeters and GPS watches: 1823, 967, and 1362 km in Copenhagen, Paris, and Montreal, respectively. We fitted three generalized additive mixed model with an autoregressive term models to predict the cyclists’ exposure to noise according to the type of route and bicycle infrastructure after controlling for the day of the week, as well as spatial and temporal trends. The overall noise means were 73.4, 70.7, and 68.4 dB(A) in Paris, Montreal, and Copenhagen, respectively. The exposure to road traffic noi...
Transportation Research Record: Journal of the Transportation Research Board, 2017
With the increasing demand for sustainability, the use of cycling as an efficient active mode of transportation is being encouraged. However, the vulnerability of cyclists to severe injuries in crashes can discourage road users from cycling. Therefore, the study of the factors that affect the safety of cyclists is important. This paper describes an investigation of the relationship between cyclist–motorist crashes and various traffic zone characteristics in Vancouver, British Columbia, Canada. The goal was to assess the impacts of socioeconomics, land use, the built environment, and the road facility on cyclist safety through the use of macrolevel collision prediction models. The models were developed by generalized linear regression and full Bayesian techniques. An actual bike exposure indicator (the number of bike kilometers traveled) and the number of vehicle kilometers traveled were used as exposure variables in the models. The safety models showed that cyclist–motorist crashes ...
While the conventional approach to safety planning has emphasized crash analysis with police-reported crash information, transportation professionals increasingly recognize the importance of proactively identifying potential crash risk and considering environmental characteristics. In a proactive approach, individuals' perception of crash risk provides important information in identifying potential crash risk. As built environment characteristics influence the levels of pedestrian and bicycle safety, this study examined how perceived and actual crash risk are related with each other and with respect to built environmental characteristics. Our results showed that residents who live in low density-single residential neighborhoods are more likely to perceive their neighborhood as dangerous relative to residents of compact, mixed-use neighborhoods even though the latter exhibited higher actual crash rates. The results of path analyses confirmed that a simultaneous but opposite relationship exists between perceived and actual crash risks. Our results indicate that higher actual crash risk increases perceived crash risk, while higher perceived crash risk is negatively associated to actual crash rates. Consequently, low density and non-mixed land uses increase individuals perception of crash risk, and increased perception of risk and unfriendly environment for pedestrian and bikers reduces actual crash rates as a result of behavioral changes. From a policy standpoint, more attention and proactive interventions are desirable in suburban areas beyond the areas with high crash rates, as some of these areas have high-perceived risks.
Journal of Transportation Safety & Security, 2019
Encouraging the use of nonmotorized modes of transportation is a goal at the intersection of public health, environment, and transportation, given active transportation's numerous benefits to individuals and communities. However, increased use of nonmotorized modes can also bring increased pedestrian-vehicle and bicycle-vehicle crashes. About 4,000 fatal and serious injury crashes involving a motor vehicle and a pedestrian or bicyclist occurred between 2007 and 2014 in the Texas Department of Transportation Austin District. This study contributed to the field of research by developing four crash frequency and severity models for pedestrians and bicyclists to identify the factors associated with the frequency of crashes and the presence of more severe crashes across the census block groups in the Austin District. The models showed the important role of different variables in crash frequency and severity, including travel demand, commute behaviors, network characteristics, and sociodemographic features. Using the model results, areas of concern with the greatest potential for safety improvements were identified. The study results can help develop safety improvement interventions for vulnerable road users in the Austin District and exemplify how other transportation agencies can estimate pedestrian and bicycle crashes using their existing database and crowdsourced data.
Comparing Unsafe Cyclist Behavior Among Three Urban Test Beds in Austin, TX
2018
In comparison to cars, cyclists are in many ways much more exposed to the potential dangers of the road. The explicit indication of traffic signals and other devices enhance safety by clarifying how the users of the transportation system should act as operators. While past studies have evaluated control devices and their impact on cyclist behavior, experimental set-ups have been typically chosen to ensure that environmental conditions remain the same between tests. Bicycle facility treatments can be thought of as a hierarchy, ranging from no treatment to bicycle signals, raised buffers, and more. Cyclist behavior can vary depending on the type of treatment present. Additionally, the existing road environment in which the treatments are placed will also have an effect on cyclist behavior. The objective of this experiment was to observe cyclist behavior in three different urban environments with three levels of existing treatments, ranging from no treatment to bicycle lanes with raise...
Causal Exploration of Bike Accidents in the Bay Area
Although the proportion of bicycles to cars on the road remains low in the United States, it is on an upward trend. The high cost of gasoline and the re-introduction of bicycles as an attractive way to commute have contributed to an increase in ridership nationwide. However, as the number of bicycles on the road grows, so do the associated challenges. Without a clear understanding of how these two parties interact in a road network it is possible that we may stunt the growth of this sustainable and beneficial form of transportation and endanger riders through car-centered design practices and an unwillingness to accommodate for cyclists and their needs on the road. Five years of bicycle crash data from the city of San Francisco were analyzed. Using multinomial logistic regression, it is possible to relate different factors to the likelihood of an accident occurring, the corresponding severity, and the party at fault. Through this statistical analysis the study hopes to determine some of the statistically significant contributing factors to accidents involving cyclists in the city of San Francisco and make recommendations on how planners and design professionals can keep bicyclist safety considerations in mind. A few significant trends in the data were found, and recommendations are made to try and mitigate the risk of these factors on bicycle related accidents and their severity.
Towards a Sustainable and Safe Future: Mapping Bike Accidents in Urbanized Context
This manuscript presents a study on the spatial relationships between bike accidents, the built environment, land use, and transportation network characteristics in Budapest, Hungary using Geographic Weighted Regression (GWR). The sample period included bike crash data between 2017 and 2022. The findings provide insights into the spatial distribution of bike crashes and their severity, which can be useful for designing targeted interventions to improve bike safety in Budapest and be useful for policymakers and city planners in developing effective strategies to reduce the severity of bike crashes in urban areas. The study reveals that the built environment features, such as traffic signals, road crossings, and bus stops, are positively correlated with the bike crashes index, particularly in the inner areas of the city. However, traffic signals have a negative correlation with the bike crash index in the suburbs, where they may contribute to making roads safer for cyclists. The study...
Transport Reviews, 2015
The growing popularity of electric devices and the increasing number of hybrid and electric cars have recently raised concerns about the use of auditory signals by vulnerable road users. This paper consolidates current knowledge about the two trends in relation to cycling safety. Both a literature review and a crash data analysis were carried out. Based on a proposed conceptual model, knowledge gaps are identified that need to be addressed for a better understanding of the relation between limitations on auditory information while cycling. Results suggest that the concerns regarding the use of electronic devices while cycling and the advent of hybrid and electric vehicles are justified. Listening to music and conversing on the phone negatively influence cyclists' auditory perception, selfreported crash risk and cycling performance. With regard to electric cars, a recurring problem is their quietness at low speeds. Implications of these findings in terms of cycling safety are discussed. Search terms "cycling", "cyclist(s)", "cycling safety" or "pedestrian(s)", "pedestrian safety" were included in all searches and combined with "music", "mobile/cell phone(s)", "distraction" or "media devices".
Transportation, 2012
Pedestrians and bicyclists are the victims of countless car crashes in U.S. cities as well as around the world. Yet, many dimensions of their involvement in crashes remain rather poorly known. In this article, we follow a spatial epidemiologic approach to study the relative risk factors of bicycle and pedestrian crashes at the neighborhood level in the City of Buffalo, NY over a two-year period. The analysis examines physical road characteristics such as roadway and intersection functional classes, urban density and type of development-business or residential, as well as socio-economic and demographic variables to identify discriminating risk factors between the two non-motorized transportation modes. The analysis underscores significant differences tied to neighborhood ethnicity, educational attainment and land use, while physical characteristics of the road infrastructure register as marginally discriminating factors. Income related socio-economic status is not found to play a prominent role.