Infrastructural and Human Factors Affecting Safety Outcomes of Cyclists

Useche, Sergio A.; Montoro, Luís; Alonso, Francisco; Oviedo-Trespalacios, Óscar

doi:10.3390/su10020299

Cited by 65 publications

(40 citation statements)

References 51 publications

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“…One solution to these problems could be to encourage sustainable transport modes such as cycling. However, for cycling to be widely accepted, good conditions ensuring safety and comfort should be established to minimize stress [1]. Although other means of transport where users are in a protected environment (e.g., vehicles) are subjected to a certain degree of environmental noise, stressful situations experienced by cyclists may be influenced more directly by environmental noise.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Noise, Vibration, Cycle Paths, and Period of Day on Stress Experienced by Cyclists

et al. 2018

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Urban and transport planners need to assess the stressful conditions experienced by cyclists, considering that highly stressful situations can discourage people from cycling as a transport mode. Therefore, this study has two objectives: (1) to present a method for monitoring stress and other environmental factors along cycling routes using smart sensors; and (2) to analyze the influence of noise, vibration, presence of cycle paths, and the period of the day on stress experienced by cyclists. Data were collected in the city of São Carlos, Brazil, using stress and noise sensors, accelerometers, and Global Positioning System (GPS). Primarily, heat maps generated from the data made it possible to identify critical points of stress along the routes. In addition, the results of a logistic regression model were analyzed to identify the influence of the studied variables on stress. Although high levels of noise increased the odds of experiencing stress by 4%, very uncomfortable vibrations increased the odds by 14%, and the presence of cycle paths reduced the odds by 8%, an analysis of p-values and odds ratio confidence intervals shows, with a 95% confidence level, that only the period of the day influenced stress, as confirmed by the data. In this case, the odds of having stress increased by 24% in the afternoon rush hour compared to the morning rush hour.

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Section: Introductionmentioning

confidence: 99%

The Influence of Noise, Vibration, Cycle Paths, and Period of Day on Stress Experienced by Cyclists

et al. 2018

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“…Improvement in the classification power verified for oversampling techniques for both classifier models; however, this is not always regarding the undersampling technique and ROSE. e best results (highlighted in (8) Road Conditions (30) Month (22) Age (17) Oversampling…”

Section: Datasetsmentioning

confidence: 99%

“…Considering the cyclist database for Lisbon, oversampling is the best resampling technique for both classifiers. Besides, this Road Conditions (19) Month (17) Age (14) Month (18) Road Markings (14) Age (14) Road Markings (42) Time (21) Age (19) Age (43) Gender (30) Road Markings (20) explore and compare the results of two supervised classification techniques in order to entify which variables can significantly affect pedestrian and cyclist injury severity when olved in a motor vehicle crash. e three resampling techniques were applied to the datasets, resulting in six different datasets city and the overall perspective.…”

Section: Datasetsmentioning

confidence: 99%

“…Notwithstanding the personal injury, the economic and societal cost of crashes varies substantially based on the severity level of injury. Some of these studies have focused their investigation on identifying which variables can increase the injury severity of a crash involving pedestrians [19][20][21][22][23][24], cyclists [25][26][27][28][29][30] or provide a joint analysis of pedestrian and cyclist risk factors [31][32][33][34][35][36][37][38][39][40]. From these studies, several risk factors have been reported to affect the injury severity of VRUs.…”

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confidence: 99%

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A Rare Event Modelling Approach to Assess Injury Severity Risk of Vulnerable Road Users

Vilaça

Macedo

Coelho

2019

Safety

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Vulnerable road users (VRUs) represent a large portion of fatalities and injuries occurring on European Union roads. It is therefore important to address the safety of VRUs, particularly in urban areas, by identifying which factors may affect the injury severity level that can be used to develop countermeasures. This paper aims to identify the risk factors that affect the severity of a VRU injured when involved in a motor vehicle crash. For that purpose, a comparative evaluation of two machine learning classifiers—decision tree and logistic regression—considering three different resampling techniques (under-, over- and synthetic oversampling) is presented, comparing both imbalanced and balanced datasets. Crash data records were analyzed involving VRUs from three different cities in Portugal and six years (2012–2017). The main conclusion that can be drawn from this study is that oversampling techniques improve the ability of the classifiers to identify risk factors. On the one hand, this analysis revealed that road markings, road conditions and luminosity affect the injury severity of a pedestrian. On the other hand, age group and temporal variables (month, weekday and time period) showed to be relevant to predict the severity of a cyclist injury when involved in a crash.

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“…From the perspective of public health and safety, identifying bicycling behaviors that increase or decrease crash risk is an important objective. A number of recent studies dealing with bicycling behaviors have focused on risky behavior [1][2][3][4][5][6][7][8][9][10][11], and several of these studies reported associations between engaging in risky behaviors and previous crashes or near-misses [1,2,4,5,[7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Safety-oriented Practices of Adult Bicycle Ridersin Brooklyn, New York USA: An Interview Study

Hoglund¹

2020

Preprint

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The primary purpose of this investigation was to identify safety-oriented bicycling practices commonly used by adult riders in an urban setting (Brooklyn, New York), and to explore whether there are any differences between the safety-oriented practices of men and women riders. Methods: 24 adult riders (14 men, 10 women) in Brooklyn were interviewed concerning their perceptions of bicycling hazards and their safety-oriented practices. Interviews were recorded, transcribed, and analyzed through thematic analysis. Fisher’s Exact Test was employed to test for gender differences. Results: Participants identified a variety of hazards, mainly due to motor vehicles but also pedestrians and roadway conditions. The analysis distilled twenty-one bicycling practices to summarize prevalent views of the participants about safe riding practices. Related items were grouped under broader categories, generating seven safety-oriented bicycling strategies. Few differences based on gender were found in the analysis; however, women in this study were more likely than men to say that they felt disrespected by other road users. Conclusion: Seven strategies may be important for safe urban bicycling: minimizing exposure to other road users (especially motor vehicles) while riding, being vigilant and anticipating what others might do, riding in a predictable fashion, making one’s presence known to other road users, making sure it is safe before proceeding, obeying traffic rules, and riding at a safe speed. Future studies could develop these concepts further and test whether they are associated with involvement in traffic crashes.

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Infrastructural and Human Factors Affecting Safety Outcomes of Cyclists

Cited by 65 publications

References 51 publications

The Influence of Noise, Vibration, Cycle Paths, and Period of Day on Stress Experienced by Cyclists

The Influence of Noise, Vibration, Cycle Paths, and Period of Day on Stress Experienced by Cyclists

A Rare Event Modelling Approach to Assess Injury Severity Risk of Vulnerable Road Users

Safety-oriented Practices of Adult Bicycle Ridersin Brooklyn, New York USA: An Interview Study

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