Wearing a bike helmet leads to less cognitive control, revealed by lower frontal midline theta power and risk indifference

A recent study claims that participants wearing a bike helmet behave riskier in a computer-based risk task compared to control participants without a bike helmet. We hypothesized that wearing a bike helmet reduces cognitive control over risky behavior. To test our hypothesis, we recorded participants' EEG brain responses while they played a risk game developed in our laboratory. Previously, we found that, in this risk game, anxious participants showed greater levels of cognitive control as revealed by greater frontal midline theta power, which was associated with less risky decisions. Here, we predicted that cognitive control would be reduced in the helmet group, indicated by reduced frontal midline theta power, and that this group would prefer riskier options in the risk game. In line with our hypothesis, we found that participants in the helmet group showed significantly lower frontal midline theta power than participants in the control group, indicating less cognitive control. We did not replicate the finding of generally riskier behavior in the helmet group. Instead, we found that participants chose the riskier option in about half of trials, no matter how risky the other option was. Our results suggest that wearing a bike helmet reduces cognitive control, as revealed by reduced frontal midline theta power, leading to risk indifference when evaluating potential behaviors

The attitudes and behaviour of adolescent road users : an application of the theory of planned behaviour

The Theory of Planned Behaviour (TPB) was used as a framework to study the attitudes of adolescent road users towards four target behaviours: (1) cycle helmet use, (2) using nearby crossings, (3) crossing from between parked cars, and (4) challenging traffic. Four questionnaires, one for each of the behaviours, were designed based on pilot work. Each questionnaire contained items to measure the TPB variables, self-reported behaviour, and general exposure and demographic characteristics (e.g. age and gender). A total of 2,457 children aged 11-16 completed the questionnaires; 564 respondents completed the 'cycle helmet use' questionnaire; 657 respondents completed the 'using nearby crossings' questionnaire; 619 respondents completed the 'crossing from between parked cars' questionnaire; and 617 completed the 'challenging traffic' questionnaire. Multivariate analyses were conducted for each of the behaviours to explore how adolescents' attitudes, subjective norms, perceived control, behavioural intentions and self-reported behaviour differed as a function of demographic variables. Correlation and multiple regression analyses were then conducted to test the relationships in the TPB and to identify beliefs underpinning adolescents' attitudes that could be targeted in road safety interventions. This report describes all aspects of the study and discusses the theoretical and practical implications

Promoting Bicycle Commuter Safety, Research Report 11-08

We present an overview of the risks associated with cycling to emphasize the need for safety. We focus on the application of frameworks from social psychology to education, one of the 5 Es—engineering, education, enforcement, encouragement, and evaluation. We use the structure of the 5 Es to organize information with particular attention to engineering and education in the literature review. Engineering is essential because the infrastructure is vital to protecting cyclists. Education is emphasized since the central focus of the report is safety

MIXED-USE SAFETY ON RURAL FACILITIES IN THE PACIFIC NORTHWEST: Consideration of Vehicular, Non-Traditional, and Non-Motorized Users

In the United States, one in 12 households do not own a personal automobile and approximately 13% of those who are old enough to drive do not. Trips by these individuals are being made in one of many other possible modes, creating the need to “share space” between many forms of travel. The goal of this project is to: improve safety and minimize the dangers for all transportation mode types while traveling in mixed-use environments on rural facilities through the development and use of engineering and education safety measures. To that end, this report documents three specific efforts by the project team. First, a comprehensive literature review of mixed-use safety issues with consideration of non-motorized and non-traditional forms of transportation. Second, a novel analysis of trauma registry data. Third, development, execution and analysis of the Pacific Northwest Transportation Survey geared toward understanding safety perceptions of mixed-use users. Most notably, findings indicate that ATVs (and similar non-traditional-type vehicles) are used on or near roads 24% of the time and snowmachines are used on or near roads 23% of the time. There are significantly more (twice as many) ATV-related on-road traumas in connected places than isolated places in Alaska and three times more traumas in highway connected places than in secondary road connected places. Comparably, bicycles had 449 on-road traumas between 2004 and 2011 whereas ATVs had 352 on-road traumas. Users of all modes who received formalized training felt safer in mixed-use environments than those who reported having no training at all

Adolescent road user behaviour : a survey of 11-16 year olds

This study was carried out to investigate the safety related behaviour of road users aged 11-16. A self-completion questionnaire was designed to measure the frequency with which children from the target population carry out 43 different road using behaviours and a number of other variables including children's beliefs about the safety of their own road using behaviour. Two thousand four hundred and thirty three children from eleven secondary schools within England completed the questionnaire in lesson time at school. Factor analysis showed that scores on the 43 behaviour items were best represented by a three-factor solution. The three factors were named unsafe road crossing behaviour, dangerous playing in the road, and planned protective behaviour. Analysis of variance and stepwise multiple regression analyses showed that demographic variables and exposure variables had statistically significant effects on how often these behaviours were carried out. More interesting was the finding that respondents had realistic perceptions of their own behaviour as road users. The more respondents believed their road using behaviour to be unsafe and irresponsible, the more often they reported carrying out road using behaviour that was undesirable from a road safety point of view. These results and their implications for road safety interventions and further research are discussed

Neural Motifs: Scene Graph Parsing with Global Context

We investigate the problem of producing structured graph representations of visual scenes. Our work analyzes the role of motifs: regularly appearing substructures in scene graphs. We present new quantitative insights on such repeated structures in the Visual Genome dataset. Our analysis shows that object labels are highly predictive of relation labels but not vice-versa. We also find that there are recurring patterns even in larger subgraphs: more than 50% of graphs contain motifs involving at least two relations. Our analysis motivates a new baseline: given object detections, predict the most frequent relation between object pairs with the given labels, as seen in the training set. This baseline improves on the previous state-of-the-art by an average of 3.6% relative improvement across evaluation settings. We then introduce Stacked Motif Networks, a new architecture designed to capture higher order motifs in scene graphs that further improves over our strong baseline by an average 7.1% relative gain. Our code is available at github.com/rowanz/neural-motifs.Comment: CVPR 2018 camera read

Expanded Parts Model for Semantic Description of Humans in Still Images

We introduce an Expanded Parts Model (EPM) for recognizing human attributes (e.g. young, short hair, wearing suit) and actions (e.g. running, jumping) in still images. An EPM is a collection of part templates which are learnt discriminatively to explain specific scale-space regions in the images (in human centric coordinates). This is in contrast to current models which consist of a relatively few (i.e. a mixture of) 'average' templates. EPM uses only a subset of the parts to score an image and scores the image sparsely in space, i.e. it ignores redundant and random background in an image. To learn our model, we propose an algorithm which automatically mines parts and learns corresponding discriminative templates together with their respective locations from a large number of candidate parts. We validate our method on three recent challenging datasets of human attributes and actions. We obtain convincing qualitative and state-of-the-art quantitative results on the three datasets.Comment: Accepted for publication in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI

Bikesharing and Bicycle Safety

The growth of bikesharing in the United States has had a transformative impact on urban transportation. Major cities have established large bikesharing systems, including Boston, Chicago, Denver, Minneapolis-Saint Paul, New York City, Salt Lake City, the San Francisco Bay Area, Seattle, Washington DC, and others. These systems began operating as early as 2010, and no fatalities have occurred within the US as of this writing. However, three have happened in North America—two in Canada and one in Mexico. Bikesharing has some qualities that appear inherently unsafe for bicyclists. Most prominently, helmet usage is documented to be quite low in most regions. Bikesharing is also used by irregular bicyclists who are less familiar with the local terrain. In this study, researchers take a closer look at bikesharing safety from qualitative and quantitative perspectives. Through a series of four focus groups, they discussed bikesharing usage and safety with bikesharing members and nonmembers in the Bay Area. They further engaged experts nationwide from a variety of fields to evaluate their opinions and perspectives on bikesharing and safety. Finally, researchers conducted an analysis of bicycle and bikesharing activity data, as well as bicycle and bikesharing collisions to evaluate injury rates associated with bikesharing when compared with benchmarks of personal bicycling. The data analysis found that collision and injury rates for bikesharing are lower than previously computed rates for personal bicycling. Experts and focus group participants independently pointed to bikesharing rider behavior and bikesharing bicycle design as possible factors. In particular, bikesharing bicycles are generally designed in ways that promote stability and limited speeds, which mitigate the conditions that contribute to collisions. Data analysis also explored whether there was evidence of a “safety in numbers benefit” that resulted from bikesharing activity. However, no significant impact from bikesharing activity on broader bicycle collisions could be found within the regions in which they operate. Discussion and recommendations are presented in the conclusion