932 resultados para Car fleet
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Determining what consequences are likely to serve as effective punishment for any given behaviour is a complex task. This chapter focuses specifically on illegal road user behaviours and the mechanisms used to punish and deter them. Traffic law enforcement has traditionally used the threat and/or receipt of legal sanctions and penalties to deter illegal and risky behaviours. This process represents the use of positive punishment, one of the key behaviour modification mechanisms. Behaviour modification principles describe four types of reinforcers: positive and negative punishments and positive and negative reinforcements. The terms ‘positive’ and ‘negative’ are not used in an evaluative sense here. Rather, they represent the presence (positive) or absence (negative) of stimuli to promote behaviour change. Punishments aim to inhibit behaviour and reinforcements aim to encourage it. This chapter describes a variety of punishments and reinforcements that have been and could be used to modify illegal road user behaviours. In doing so, it draws on several theoretical perspectives that have defined behavioural reinforcement and punishment in different ways. Historically, the main theoretical approach used to deter risky road use has been classical deterrence theory which has focussed on the perceived certainty, severity and swiftness of penalties. Stafford and Warr (1993) extended the traditional deterrence principles to include the positive reinforcement concept of punishment avoidance. Evidence of the association between punishment avoidance experiences and behaviour has been established for a number of risky road user behaviours including drink driving, unlicensed driving, and speeding. We chose a novel way of assessing punishment avoidance by specifying two sub-constructs (detection evasion and punishment evasion). Another theorist, Akers, described the idea of competing reinforcers, termed differential reinforcement, within social learning theory (1977). Differential reinforcement describes a balance of reinforcements and punishments as influential on behaviour. This chapter describes comprehensive way of conceptualising a broad range of reinforcement and punishment concepts, consistent with Akers’ differential reinforcement concept, within a behaviour modification framework that incorporates deterrence principles. The efficacy of three theoretical perspectives to explain self-reported speeding among a sample of 833 Australian car drivers was examined. Results demonstrated that a broad range of variables predicted speeding including personal experiences of evading detection and punishment for speeding, intrinsic sensations, practical benefits expected from speeding, and an absence of punishing effects from being caught. Not surprisingly, being younger was also significantly related to more frequent speeding, although in a regression analysis, gender did not retain a significant influence once all punishment and reinforcement variables were entered. The implications for speed management, as well as road user behaviour modification more generally, are discussed in light of these findings. Overall, the findings reported in this chapter suggest that a more comprehensive approach is required to manage the behaviour of road users which does not rely solely on traditional legal penalties and sanctions.
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Background Drink-driving has been implicated in many road traffic crashes in the world. Consequently, the developed countries have prioritized drink-driving research. Contrary, drink-driving research has not attained any meaningful consideration in many developing countries. It is therefore imperative to intensify drink-driving research so as to provide research driven solutions to the menace. Aims The objective is to establish determinants of drink-driving and its association with traffic crashes in Ghana. Methods A randomized roadside breathalyzer survey was conducted. A multivariable logistic regression was used to establish significant determinants of drink-driving and a bivariate logistic regression to establish the association between drink–driving and road traffic crashes in Ghana. Results In total, 2,736 motorists were randomly stopped for breath testing of whom 8.7% tested positive for alcohol. Among the total participants, 5.5% exceeded the legal BAC limit of 0.08%. Formal education is associated with a reduced likelihood of drink-driving compared with drivers without formal education. The propensity to drink-drive is 1.8 times higher among illiterate drivers compared with drivers with basic education. Young adult drivers also recorded elevated likelihoods for driving under alcohol impairment compared with adult drivers. The odds of drink-driving among truck drivers is OR=1.81, (95% CI=1.16 to 2.82) and two wheeler riders is OR=1.41, (95% CI=0.47 to 4.28) compared with car drivers. Contrary to general perception, commercial car drivers have a significant reduced likelihood of 41%, OR=0.59, (95% CI=0.38 to 0.92) compared with the private car driver. Bivariate analysis conducted showed a significant association between the proportion of drivers exceeding the legal BAC limit and road traffic fatalities, p<0.001. The model predicts a 1% increase in the proportion of drivers exceeding the legal BAC to be associated with a 4% increase in road traffic fatalities, 95% CI= 3% to 5% and vice versa. Discussion and conclusion A positive and significant association between roadside alcohol prevalence and road traffic fatality has been established. Scaling up roadside breath test, determining standard drink and disseminating to the populace and formulating policies targeting the youth such as increasing minimum legal drinking age and reduced legal BAC limit for the youth and novice drivers might improve drink-driving related crashes in Ghana.
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This research investigated the effectiveness of using an eco-driving strategy at urban signalised intersections from both the individual driver and the traffic flow perspective. The project included a field driving experiment and a series of traffic simulation investigations. The study found that the prevailing eco-driving strategy has negative impacts on traffic mobility and environmental performance when the traffic is highly congested. An improved eco-driving strategy has been developed to mitigate these negative impacts.
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Drink driving remains a major cause of serious and fatal car crashes in Australia and internationally. While this problem is more prevalent among male drivers, the rates of female intoxicated drivers have increased steadily over the past decades in many motorised countries. A combination of police enforcement, media awareness campaigns, and community initiatives has played a key role in reducing incidents of illegal drink driving by targeting public drink driving attitudes. However, important cultural differences in regards to the tolerance towards drink driving have been noted. While many countries, including Australia, have a legal Blood Alcohol Concentration (BAC) limit of .05 or higher, some countries have moved towards a zero –or low tolerance approach to drink driving; several European countries, including Sweden, Hungary, Slovakia, and Estonia currently enforce .00 or .02 BAC limits.
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The purpose of this investigation is to present an overview of roadside drug driving enforcement and detections in Queensland, Australia since the introduction of oral fluid screening. Drug driving is a problematic issue for road safety and investigations of the prevalence and impact of drug driving suggest that, in particular, the use of illicit drugs may increase a driver’s involvement in a road crash when compared to a driver who is drug free. In response to the potential increased crash involvement of drug impaired drivers, Australian police agencies have adopted the use of oral fluid analysis to detect the presence of illicit drugs in drivers. This paper describes the results of roadside drug testing for over 80,000 drivers in Queensland, Australia, from December 2007 to June 2012. It provides unique data on the prevalence of methamphetamine, cannabis and ecstasy in the screened population for the period. When prevalence rates are examined over time, drug driving detection rates have almost doubled from around 2.0% at the introduction of roadside testing operations to just under 4.0% in the latter years. The most common drug type detected was methamphetamine (40.8%) followed by cannabis (29.8%) and methamphetamine/cannabis combination (22.5%). By comparison, the rate of ecstasy detection was very low (1.7%). The data revealed a number of regional, age and gender patterns and variations of drug driving across the state. Younger drivers were more likely to test positive for cannabis whilst older drivers were more likely to test positive for methamphetamine. The overall characteristics of drivers who tested positive to the presence of at least one of the target illicit drugs are they are likely to be male, aged 30-39 years, be driving a car on Friday, Saturday or Sunday between 6:00PM and 6:00AM and to test positive for methamphetamine.
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Sharing some closely related themes and a common theoretical orientation based on the governmentality analytic, these are nevertheless two very different contributions to criminological knowledge and theory. The first, The Currency of Justice: Fines and Damages in Consumer Societies (COJ), is a sustained and highly original analysis of that most pervasive yet overlooked feature of modern legal orders; their reliance on monetary sanctions. Crime and Risk (CAR), on the other hand, is a short synoptic overview of the many dimensions and trajectories of risk in contemporary debate and practice, both the practices of crime and the governance of crime. It is one of the first in a new series by Sage, 'Compact Criminology', in which authors survey in little more than a hundred pages some current field of debate. With this small gem, Pat O'Malley has set the bar very high for those who follow. For all its brevity, CAR traverses a massive expanse of research, debates and issues, while also opening up new and challenging questions around the politics of risk and the relationship between criminal risk-taking and the governance of risk and crime. The two books draw together various threads of O'Malley's rich body of work on these issues, and once again demonstrate that he is one of the foremost international scholars of risk inside and outside criminology.
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Twitter and other social media have become increasingly important tools for maintaining the relationships between fans and their idols across a range of activities, from politics and the arts to celebrity and sports culture. Twitter, Inc. itself has initiated several strategic approaches, especially to entertainment and sporting organisations; late in 2012, for example, a Twitter, Inc. delegation toured Australia in order to develop formal relationships with a number of key sporting bodies covering popular sports such as Australian Rules Football, A-League football (soccer), and V8 touring car racing, as well as to strengthen its connections with key Australian broadcasters and news organisations (Jackson & Christensen, 2012). Similarly, there has been a concerted effort between Twitter Germany and the German Bundesliga clubs and football association to coordinate the presence of German football on Twitter ahead of the 2012–2013 season: the Twitter accounts of almost all first-division teams now bear the official Twitter verification mark, and a system of ‘official’ hashtags for tweeting about individual games (combining the abbreviations of the two teams, e.g. #H96FCB) has also been instituted (Twitter auf Deutsch, 2012).
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In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.
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In outdoor environments shadows are common. These typically strong visual features cause considerable change in the appearance of a place, and therefore confound vision-based localisation approaches. In this paper we describe how to convert a colour image of the scene to a greyscale invariant image where pixel values are a function of underlying material property not lighting. We summarise the theory of shadow invariant images and discuss the modelling and calibration issues which are important for non-ideal off-the-shelf colour cameras. We evaluate the technique with a commonly used robotic camera and an autonomous car operating in an outdoor environment, and show that it can outperform the use of ordinary greyscale images for the task of visual localisation.
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Introduction Sleep restriction and missing 1 night’s continuous positive air pressure (CPAP) treatment are scenarios faced by obstructive sleep apnoea (OSA) patients, who must then assess their own fitness to drive. This study aims to assess the impact of this on driving performance. Method 11 CPAP treated participants (50–75 yrs), drove an interactive car simulator under monotonous motorway conditions for 2 hours on 3 afternoons, following;(i)normal night’s sleep (average 8.2 h) with CPAP (ii) sleep restriction (5 h), with CPAP (iii)normal length of sleep, without CPAP. Driving incidents were noted if the car came out of the designated driving lane. EEG was recorded continually and KSS reported every 200 seconds. Results Driving incidents: Incidents were more prevalent following CPAP withdrawal during hour 1, demonstrating a significant condition time interaction [F(6,60) = 3.40, p = 0.006]. KSS: At the start of driving participants felt sleepiest following CPAP withdrawal, by the end of the task KSS levels were similar following CPAP withdrawal and sleep restriction, demonstrating a significant condition, time interaction [F(3.94,39.41) = 3.39, p = 0.018]. EEG: There was a non significant trend for combined alpha and theta activity to be highest throughout the drive following CPAP withdrawal. Discussion CPAP withdrawal impairs driving simulator performance sooner than restricting sleep to 5 h with CPAP. Participants had insight into this increased sleepiness reflected by the higher KSS reported following CPAP withdrawal. In the practical terms of driving any one incident could be fatal. The earlier impairment reported here demonstrates the potential danger of missing CPAP treatment and highlights the benefit of CPAP treatment even when sleep time is short.
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Objectives The UK Department for Transport recommends taking a break from driving every 2 h. This study investigated: (i) if a 2 h drive time on a monotonous road is appropriate for OSA patients treated with CPAP, compared with healthy age matched controls, (ii) the impact of a night’s sleep restriction (with CPAP) and (iii) what happens if these patients miss one nights’ CPAP treatment. Methods About 19 healthy men aged 52–74 y (m = 66.2 y) and 19 OSA participants aged 50–75 y (m = 64.4 y) drove an interactive car simulator under monotonous motorway conditions for 2 h on two afternoons, in a counterbalanced design; (1) following a normal night’s sleep (8 h). (2) following a restricted night’s sleep (5 h), with normal CPAP use (3) following a night without CPAP treatment. (n = 11) Lane drifting incidents, indicative of falling asleep, were recorded for up to 2 h depending on competence to continue driving. Results Normal sleep: Controls drove for an average of 95.9 min (s.d. 37 min) and treated OSA drivers for 89.6 min (s.d. 29 min) without incident. 63.2% of controls and 42.1% of OSA drivers successfully completed the drive without an incident. Sleep restriction: 47.4% of controls and 26.3% OSA drivers finished without incident. Overall: controls drove for an average of 89.5 min (s.d. 39 min) and treated OSA drivers 65 min (s.d. 42 min) without incident. The effect of condition was significant [F(1.36) = 9.237, P < 0.05, eta2 = 0.204]. Stopping CPAP: 18.2% of drivers successfully completed the drive. Overall, participants drove for an average of 50.1 min (s.d. 38 min) without incident. The effect of condition was significant [F(2) = 8.8, P < 0.05, eta2 = 0.468]. Conclusion 52.6% of all drivers were able to complete a 2 hour drive under monotonous conditions after a full night’s sleep. Sleep restriction significantly affected both control and OSA drivers. We find evidence that treated OSA drivers are more impaired by sleep restriction than healthy control, as they were less able to sustain safely the 2 h drive without incidents. OSA drivers should be aware that non-compliance with CPAP can significantly impair driving performance. It may be appropriate to recommend older drivers take a break from driving every 90 min especially when undertaking a monotonous drive, as was the case here.
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Persistent monitoring of the ocean is not optimally accomplished by repeatedly executing a fixed path in a fixed location. The ocean is dynamic, and so should the executed paths to monitor and observe it. An open question merging autonomy and optimal sampling is how and when to alter a path/decision, yet achieve desired science objectives. Additionally, many marine robotic deployments can last multiple weeks to months; making it very difficult for individuals to continuously monitor and retask them as needed. This problem becomes increasingly more complex when multiple platforms are operating simultaneously. There is a need for monitoring and adaptation of the robotic fleet via teams of scientists working in shifts; crowds are ideal for this task. In this paper, we present a novel application of crowd-sourcing to extend the autonomy of persistent-monitoring vehicles to enable nonrepetitious sampling over long periods of time. We present a framework that enables the control of a marine robot by anybody with an internet-enabled device. Voters are provided current vehicle location, gathered science data and predicted ocean features through the associated decision support system. Results are included from a simulated implementation of our system on a Wave Glider operating in Monterey Bay with the science objective to maximize the sum of observed nitrate values collected.
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This paper investigates quality of service and resource productivity implications of transit route passenger loading and travel distance. Weekday Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate correlation between load factor and distance factor. Relationships between boardings and transit work indicate that distance factor generally increases with load factor. Time series analysis is then presented by examining each direction on an hour by hour basis. Inbound correlation is medium to strong across the entire span of service and strong for daytime services up to 19:30, while outbound correlation is strong across the entire span. Passengers tend to be making longer distance, peak direction commuter trips under the least comfortable conditions under stretched peak schedules than off-peak. Therefore productivity gains may be possible by adjusting fleet utilization during off-peak times. Weekday profiles by direction are established for a composite load-distance factor. A threshold corresponding to standing passengers on the Maximum Load Segment reveals that on-board loading and travel distance combined are more severe during the morning inbound peak than evening outbound peak, although the sharpness of the former suggests that encouraging shoulder peak travel during the morning would be more effective than evening peak. Further research suggested includes: consideration of travel duration factor, relating noise within hour to Peak Hour Factor, profiling load-distance factor across a range of case studies, and relating load-distance factor threshold to line length.
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Background In China, as in many developing countries, rapid increases in car ownership and new drivers have been coupled with a large trauma burden. The World Health Organization has identified key risk factors including speeding, drink-driving, helmet and restraint non-use, overloaded vehicles, and fatigued-driving in many rapidly motorising countries, including China. Levels of awareness of these risk factors among road users are not well understood. Although research identifies speeding as the major factor contributing to road crashes in China, there appears to be widespread acceptance of it among the broader community. Purpose To assess self-reported speeding and awareness of crash risk factors among Chinese drivers in Beijing. Methods Car drivers (n=299) were recruited from car washing locations and car parks to complete an anonymous questionnaire. Perceptions of the relative risk of drink-driving, fatigued-driving and speeding, and attitudes towards speeding and self-reported driving speeds were assessed. Results Overall, driving speeds of >10km/hr above posted limits on two road types (60 and 80 km/hour zones) were reported by more than one third of drivers. High-range speeding (i.e., >30 km/hour in a 60 km/hour zone and >40 km/hour in an 80 km/hour zone) was reported by approximately 5% of the sample. Attitudinal measures indicated that approximately three quarters of drivers reported attitudes that were not supportive of speeding. Drink-driving was identified as the most risky behaviour; 18% reported the perception that drink-driving had the same level of danger as speeding and 82% reported it as more dangerous. For fatigued-driving, 1% reported the perception that it was not as dangerous as speeding; 27.4% reported it as the same level and 71.6% perceived it as more dangerous. Conclusion Driving speeds well above posted speed limits were commonly reported by drivers. Speeding was rated as the least dangerous on-road behaviour, compared to drink-driving and fatigued-driving. One third of drivers reported regularly engaging in speeds at least 10km/hr above posted limits, despite speeding being the major reported contributor to crashes. Greater awareness of the risks associated with speeding is needed to help reduce the road trauma burden in China and promote greater speed limit compliance.
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Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.