Traffic conflicts on bicycle paths: A systematic observation of behaviour from video

Horst, A.R.A. van der; Goede, M. de; Hair-Buijssen, Stefanie de; Methorst, Rob

doi:10.1016/j.aap.2013.04.005

Cited by 86 publications

(39 citation statements)

References 2 publications

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“…We believe this methodology, and the simpler approach of asking participants where they feel most in danger (Chataway et al, 2014), has great potential for improving understanding of the social and geographical factors associated with both perceived risk and risk inadequately indexed by STATS19. 8 Additionally, Van der Horst (2014) has found behavioural observation through video capture was a successful technique for data collection on cyclist risk, as it allowed repeated review and judgment of different aspects of the situation. Stevenson (2014) also uses cameras attached to participants' bikes, allowing for naturalistic data from an objective point of view.…”

Section: When Are Bicycle Crashes Most Likely?mentioning

confidence: 99%

Who, where, when: the demographic and geographic distribution of bicycle crashes in West Yorkshire

Lovelace

Roberts

Kellar

2016

Transportation Research Part F: Traffic Psychology and Behaviou

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Factors associated with cycle safety, including international differences in injury and mortality rates, protective equipment and bicycle training, have been subject to increasing academic interest. Environmental variables associated with cycle safety have also been scrutinised, but few studies have focussed on geographical factors at the local level. This paper addresses this research gap by analysing a geo-referenced dataset of road traffic incidents, taken from the UK's STATS19 dataset (2005 -2012). We investigate incidents involving cyclists within West Yorkshire. This is an interesting case study area as it has an historically low cycling rate but very ambitions cycling plans following investment from the Department of Transport. West Yorkshire is found to be an unusually risky area for cyclists, with an estimated 53 deaths and 1372 serious injuries per billion kilometres cycled, based on census commuting statistics. This is roughly double the national average. This riskiness varies spatially and temporally, broadly in line with expectations from the previous literature. An unexpected result was that cycling seems to be disproportionately risky for young people in West Yorkshire compared with young people nationally. The case study raises the issue of potential negative health impacts of promoting cycling amongst vulnerable groups in dangerous areas. We conclude by highlighting opportunities for increasing cycling uptake via measures designed primarily to improve safety. The analysis underlying this research is reproducible, based on code stored at github.com/Robinlovelace/bikeR.

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Section: When Are Bicycle Crashes Most Likely?mentioning

confidence: 99%

Who, where, when: the demographic and geographic distribution of bicycle crashes in West Yorkshire

Lovelace

Roberts

Kellar

2016

Transportation Research Part F: Traffic Psychology and Behaviou

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“…Most serious fractures result from collisions with motor vehicles. Maxillofacial injuries are three times more likely in motor vehicle involved crashes than bike only crashes and probably this is why the risk of facial fracture decreases with impact speed, although cannot be separated from other gradual changes, including overall cyclist experience, bicycling patterns and attitudes to risk, making it very difficult to correctly adjust for all relevant variables 12,15,16 . Moreover, a motor vehicle being involved does not tell us what the actual cause of the injury was: did the brakes fail and the cyclist collide with a car or did a car turn into a cyclist at a junction due to not seeing them.…”

Section: Discussionmentioning

confidence: 99%

Bicycling-related accidents and factors contributing to injury

Peréz

Wideberg

PEREZ-SOMARRIBA³

2016

Libro De Actas CIT2016. XII Congreso De Ingeniería Del Transporte

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Abstract:Objective: This study was conducted to find the epidemiological characteristics of bicycling-related maxillofacial fractures in a defined population, and identify factors contributing to injury. Methodology: A prospective study was carried out involving patients presenting with maxillofacial fractures sustained in bicycling-related accidents. Results: Between 908 of all cycling accidents attending for medical treatment, 122 patients (13% of all cycling accidents) were admitted with facial fractures between 2007 and 2014. Male and female ratio was 2.6:1, and the mean age was 29.4 years (standard deviation: 12.8, range: 12-79 years). Causes of injury included collisions (63%) and accidental falls (37%). The fracture patterns seen were mandibular (49%), zygomatic (32%), orbital (13%), nasal (7%), maxillary (2%), and frontal (2%). Condylar fractures were the most common of the mandibular fractures (63%). The most frequently observed concomitant lesions were orthopedic injuries. Conclusions: Bicycling-related maxillofacial injuries are common and therefore important to identify in order to design a sustainable transport system and for units that provide assistance to traffic accident victims. Missed diagnosis or delayed treatment can lead to facial deformities and functional problems. Wearing protective helmets and the improvement of the helmets design is one aspect that would be of interest for the prevention of injuries.

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“…In addition to that, ABMs are particularly well suited to integrating local context and behavioural information of individual road users [41]. The next step ahead in predicting accidents with ABM is thus to systematically analyse context-specific risk factors that are associated with an encounter, such as encounter angle, road type, traffic mode, weather, time of the day, or certain road user characteristics [2], and integrate these into ABM models.…”

Section: Discussionmentioning

confidence: 99%

“…We would therefore expect the relation between flows and encounters to be of the general form of aˆn + bˆn 2 , where the coefficients a and b are related to the complexity of the network.…”

Section: Flows and Encounters In An Abstract Networkmentioning

confidence: 99%

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Bicycle-Bicycle Accidents Emerge from Encounters: An Agent-Based Approach

Wallentin

Loidl

2016

Safety

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Traditional accident risk prediction models need adequate data on explanatory variables, most importantly data on traffic flows. However, in the case of accidents between bicycles the availability of such data is often limited. Therefore, alternative bottom-up simulation modelling approaches are expected to complement traditional equation-based models. In this paper we present an agent-based approach to explore bicycle-bicycle accidents. Specifically, we hypothesise that (1) bicycle-bicycle accidents are based on the population of encounters between cyclists rather than on bicycle flows and (2) that encounters have a non-linear relationship with flows. Bicycle flows and encounters are simulated by means of an agent-based model that is implemented for the road network of the city of Salzburg. Simulation results are tested against a 10-year dataset of police records on bicycle-bicycle accidents. The results affirm both hypotheses: First, cyclist encounters exhibit a linear relationship to accidents and thus suggest being the true population of bicycle-bicycle accidents. Second, flows show a relationship in the form of a second-order polynomial function with encounters as well as accidents.

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Traffic conflicts on bicycle paths: A systematic observation of behaviour from video

Cited by 86 publications

References 2 publications

Who, where, when: the demographic and geographic distribution of bicycle crashes in West Yorkshire

Who, where, when: the demographic and geographic distribution of bicycle crashes in West Yorkshire

Bicycling-related accidents and factors contributing to injury

Bicycle-Bicycle Accidents Emerge from Encounters: An Agent-Based Approach

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