10 resultados para Pedestrian malls

em Aston University Research Archive


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Self-identity as a careful pedestrian has not been fully considered in previous work on predicting intention to cross the road, or actual crossing behaviour, in non-optimal situations. Evidence suggests that self-identity may be a better predictor than attitudes in situations where decision-making styles have become habitual ways to respond. This study compared contributions of self-identity and attitudes to the prediction of intentions in two situations differing in level of habitual crossing expectation, and to crossing behaviour. Three hundred and sixty-two adults (17–92 years) completed a questionnaire measuring self-identity, attitudes, intentions, experience, social identity variables (e.g. age, gender) and personal limitations (mobility). Two hundred and five participants also completed a road-crossing simulation. Self-identity and attitude were both shown as significant independent predictors of intention in both situations. However, self-identity was less effective as a predictor in the higher risk scenario, where intention to perform the behaviour was lower, and for participants aged >75 years who had lower intention across scenarios. Self-identity strongly predicted intention to cross, which in turn predicted behaviour, but self-identity did not directly predict behaviour. Self-identity was strongly predicted by age. Implications for theories of compensation in older age and for design and targeting of pedestrian safety education are discussed.

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Objective: The purpose of this study was to determine the extent to which mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function, specifically executive functions, including spatial planning, visual attention, and within participant variability, differentially predicted collisions in the near and far sides of the road with increasing age. Methods: Adults aged over 45 years participated in cognitive tests measuring executive function and visual attention (using Useful Field of View; UFoV®), mobility assessments (walking speed, sit-to-stand, self-reported mobility, and postural sway assessed using motion capture cameras), and gave road crossing choices in a two-way filmed real traffic pedestrian simulation. Results: A stepwise regression model of walking speed, start-up delay variability, and processing speed) explained 49.4% of the variance in near-side crossing errors. Walking speed, start-up delay measures (average & variability), and spatial planning explained 54.8% of the variance in far-side unsafe crossing errors. Start-up delay was predicted by walking speed only (explained 30.5%). Conclusion: Walking speed and start-up delay measures were consistent predictors of unsafe crossing behaviours. Cognitive measures, however, differentially predicted near-side errors (processing speed), and far-side errors (spatial planning). These findings offer potential contributions for identifying and rehabilitating at-risk older pedestrians.

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Most object-based approaches to Geographical Information Systems (GIS) have concentrated on the representation of geometric properties of objects in terms of fixed geometry. In our road traffic marking application domain we have a requirement to represent the static locations of the road markings but also enforce the associated regulations, which are typically geometric in nature. For example a give way line of a pedestrian crossing in the UK must be within 1100-3000 mm of the edge of the crossing pattern. In previous studies of the application of spatial rules (often called 'business logic') in GIS emphasis has been placed on the representation of topological constraints and data integrity checks. There is very little GIS literature that describes models for geometric rules, although there are some examples in the Computer Aided Design (CAD) literature. This paper introduces some of the ideas from so called variational CAD models to the GIS application domain, and extends these using a Geography Markup Language (GML) based representation. In our application we have an additional requirement; the geometric rules are often changed and vary from country to country so should be represented in a flexible manner. In this paper we describe an elegant solution to the representation of geometric rules, such as requiring lines to be offset from other objects. The method uses a feature-property model embraced in GML 3.1 and extends the possible relationships in feature collections to permit the application of parameterized geometric constraints to sub features. We show the parametric rule model we have developed and discuss the advantage of using simple parametric expressions in the rule base. We discuss the possibilities and limitations of our approach and relate our data model to GML 3.1. © 2006 Springer-Verlag Berlin Heidelberg.

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The relationship between parent-child interaction and child pedestrian behaviour was investigated by comparing parent-child communication to road-crossing behaviour. Forty-four children and their parents were observed carrying out a communication task (the Map Task), and were covertly filmed crossing roads around a university campus. The Map Task provided measures of task focus and sensitivity to another's current knowledge, which we predicted would be reflected in road-crossing behaviour. We modelled indices of road behaviour with factor scores derived from a principal-component analysis of communication features, and background variables including the age, sex and traffic experience of the child, and parental education. A number of variables were significantly related to road crossing, including the age and sex of the child, the length of the conversation, and specific conversational features such as the checking and clarification of uncertain information by both parent and child. The theoretical and practical implications of the findings are discussed.

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The theory of planned behaviour (TPB) has been used successfully in the past to account for pedestrians' intentions to cross the road in risky situations. However, accident statistics show age and gender differences in the likelihood of adult pedestrian accidents. This study extends earlier work by examining the relative importance of the model components as predictors of intention to cross for four different adult age groups, men, women, drivers and nondrivers. The groups did not differ in the extent to which they differentiated between two situations of varying perceived risk. The model fit was good, but accounted for less of the variance in intention for the youngest group (17-24) than for other age groups. Differences between the age groups in intention to cross seemed to be due to differences in perceived value of crossing rather than differences in perceived risk. Women were less likely to intend to cross than men and perceived more risk, and there were important age, gender and driver status differences in the importance of the TPB variables as predictors of intention. A key implication of these findings is that road safety interventions need to be designed differently for different groups. © 2006 Elsevier Ltd. All rights reserved.

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Adult pedestrian accident data has demonstrated that the risk of being killed or seriously injured varies with age and gender. A range of factors affecting road crossing choices of 218 adults aged 17-90+ were examined in a simulation study using filmed real traffic. With increasing age, women were shown to make more unsafe crossing decisions, to leave small safety margins and to become poorer at estimating their walking speed. However, the age effects on all of these were ameliorated by driving experience. Men differed from women in that age was not a major factor in predicting unsafe crossing decisions. Rather, reduced mobility was the key factor, leading them to make more unsafe crossings and delay longer in leaving the kerb. For men, driving experience did not predict unsafe road crossing decisions. Although male drivers were more likely to look both ways before crossing than male non-drivers, the impact of being a driver had a negative effect in terms of smaller safety margins and delay in leaving the kerb. The implications of the different predictor variables for men and women for unsafe road crossing are discussed and possible reasons for the differences explored.

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The recent history of small shop and independent retailing has been one of decline. The most desirable form of assistance is the provision of information which will increase the efficiency model of marketing mix effeciveness which may be applied in small scale retailing. A further aim is to enhance theoretical development in the marketing field. Recent changes in retailing have affected location, product range, pricing and promotion practices. Although a large number of variables representing aspects of the marketing mix may be identified, it is not possible, on the basis of currently available information, to quantify or rank them according to their effect on sales performance. In designing a suitable study a major issue is that of access to a suitable representative sample of small retailers. The publish nature of the retail activities involved facilitates the use of a novel observation approach to data collection. A cross-sectional survey research design was used focussing on a clustered random sample of greengrocers and gent's fashion outfitters in the West Midlands. Linear multiple regression was the main analytical technique. Powerful regression models were evolved for both types of retailing. For greengrocers the major influences on trade are pedestrian traffic and shelf display space. For gent's outfitters they are centrality-to-other shopping, advertising and shelf display space. The models may be utilised by retailers to determine the relative strength of marketing mix variables. The level of precision is not sufficient to permit cost benefit analysis. Comparison of the findings for the two distinct kinds of business studied suggests an overall model of marketing mix effectiveness might be based on frequency of purchase, homogeneity of the shopping environment, elasticity of demand and bulk characteristics of the good sold by a shop.

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The objectives are to examine rural road accident data in order to develop a method by which high accident rate locations and accident causes can be identified, and also to develop proposals for improvements at such locations and to identify measures which will improve road safety throughout the country. The problem of road safety in Iran is an important issue, because of the tragic and unnecessary loss of life, and the enormous cost of accidents in the country. The resources available to deal with the problems are limited and must be allocated on priority basis. This study represents an initial effort to identify the extent of the problem in order to take remedial measures. A study was made of all the available road accident data collected by agencies related to road safety in Iran, and the major organisations responsible for road safety development were visited. The Vice Minister of Roads and Transportation selected for this study a 280 Km rural road in South West Iran. Mainly because of the lack of suitable maps and plans of the roads, it was not possible to accurately identify the location of accidents. Accident scene data was subsequently collected by the highway police and personally by the author. The data for the study road was then analysed to identify 'high accident rate' locations, and also to determine, as far as was possible, the reasons for the accidents. The study suggests specific improvements for each of the high accident rate locations examined (eg. the building of dual carriageways with central guard rails to reduce the risk of collision with oncoming vehicles, pedestrian facilities to allow pedestrians to cross dangerous roadsl]. In addition recommendations are made to guide and assist the major organisations responsible for road safety in Iran. These recommendations are: (al for improving accident data collection and storage (bl for subsequent analysis for taking remedial measures with a view to accident prevention

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Given evidence of effects of mobile phone use on driving, and also legislation, many careful drivers refrain from answering their phones when driving. However, the distracting influence of a call on driving, even in the context of not answering, has not been examined. Furthermore, given that not answering may be contrary to an individual’s normal habits, this study examined whether distraction caused by the ignored call varies according to normal intention to answer whilst driving. That is, determining whether the effect is more than a simple matter of noise distraction. Participants were 27 young drivers (18-29 years), all regular mobile users. A Theory of Planned Behaviour questionnaire examined predictors of intention to refrain from answering calls whilst driving. Participants provided their mobile phone number and were instructed not to answer their phone if it were to ring during a driving simulation. The simulation scenario had seven hazards (e.g. car pulling out, pedestrian crossing) with three being immediately preceded by a call. Infractions (e.g. pedestrian collisions, vehicle collisions, speed exceedances) were significantly greater when distracted by call tones than with no distraction. Lower intention to ignore calls whilst driving correlated with a larger effect of distraction, as was feeling unable to control whether one answered whilst driving (Perceived Behavioural Control). The study suggests that even an ignored call can cause significantly increased infractions in simulator driving, with pedestrian collisions and speed exceedances being striking examples. Results are discussed in relation to cognitive demands of inhibiting normal behaviour and to drivers being advised to switch phones off whilst driving.

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The aims of this thesis were to investigate the neuropsychological, neurophysiological, and cognitive contributors to mobility changes with increasing age. In a series of studies with adults aged 45-88 years, unsafe pedestrian behaviour and falls were investigated in relation to i) cognitive functions (including response time variability, executive function, and visual attention tests), ii) mobility assessments (including gait and balance and using motion capture cameras), iii) motor initiation and pedestrian road crossing behavior (using a simulated pedestrian road scene), iv) neuronal and functional brain changes (using a computer based crossing task with magnetoencephalography), and v) quality of life questionnaires (including fear of falling and restricted range of travel). Older adults are more likely to be fatally injured at the far-side of the road compared to the near-side of the road, however, the underlying mobility and cognitive processes related to lane-specific (i.e. near-side or far-side) pedestrian crossing errors in older adults is currently unknown. The first study explored cognitive, motor initiation, and mobility predictors of unsafe pedestrian crossing behaviours. The purpose of the first study (Chapter 2) was to determine whether collisions at the near-side and far-side would be differentially predicted by mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function (including spatial planning, visual attention, and within participant variability) with increasing age. The results suggest that near-side unsafe pedestrian crossing errors are related to processing speed, whereas far-side errors are related to spatial planning difficulties. Both near-side and far-side crossing errors were related to walking speed and motor initiation measures (specifically motor initiation variability). The salient mobility predictors of unsafe pedestrian crossings determined in the above study were examined in Chapter 3 in conjunction with the presence of a history of falls. The purpose of this study was to determine the extent to which walking speed (indicated as a salient predictor of unsafe crossings and start-up delay in Chapter 2), and previous falls can be predicted and explained by age-related changes in mobility and cognitive function changes (specifically within participant variability and spatial ability). 53.2% of walking speed variance was found to be predicted by self-rated mobility score, sit-to-stand time, motor initiation, and within participant variability. Although a significant model was not found to predict fall history variance, postural sway and attentional set shifting ability was found to be strongly related to the occurrence of falls within the last year. Next in Chapter 4, unsafe pedestrian crossing behaviour and pedestrian predictors (both mobility and cognitive measures) from Chapter 2 were explored in terms of increasing hemispheric laterality of attentional functions and inter-hemispheric oscillatory beta power changes associated with increasing age. Elevated beta (15-35 Hz) power in the motor cortex prior to movement, and reduced beta power post-movement has been linked to age-related changes in mobility. In addition, increasing recruitment of both hemispheres has been shown to occur and be beneficial to perform similarly to younger adults in cognitive tasks (Cabeza, Anderson, Locantore, & McIntosh, 2002). It has been hypothesised that changes in hemispheric neural beta power may explain the presence of more pedestrian errors at the farside of the road in older adults. The purpose of the study was to determine whether changes in age-related cortical oscillatory beta power and hemispheric laterality are linked to unsafe pedestrian behaviour in older adults. Results indicated that pedestrian errors at the near-side are linked to hemispheric bilateralisation, and neural overcompensation post-movement, 4 whereas far-side unsafe errors are linked to not employing neural compensation methods (hemispheric bilateralisation). Finally, in Chapter 5, fear of falling, life space mobility, and quality of life in old age were examined to determine their relationships with cognition, mobility (including fall history and pedestrian behaviour), and motor initiation. In addition to death and injury, mobility decline (such as pedestrian errors in Chapter 2, and falls in Chapter 3) and cognition can negatively affect quality of life and result in activity avoidance. Further, number of falls in Chapter 3 was not significantly linked to mobility and cognition alone, and may be further explained by a fear of falling. The objective of the above study (Study 2, Chapter 3) was to determine the role of mobility and cognition on fear of falling and life space mobility, and the impact on quality of life measures. Results indicated that missing safe pedestrian crossing gaps (potentially indicating crossing anxiety) and mobility decline were consistent predictors of fear of falling, reduced life space mobility, and quality of life variance. Social community (total number of close family and friends) was also linked to life space mobility and quality of life. Lower cognitive functions (particularly processing speed and reaction time) were found to predict variance in fear of falling and quality of life in old age. Overall, the findings indicated that mobility decline (particularly walking speed or walking difficulty), processing speed, and intra-individual variability in attention (including motor initiation variability) are salient predictors of participant safety (mainly pedestrian crossing errors) and wellbeing with increasing age. More research is required to produce a significant model to explain the number of falls.