11 resultados para Driver-Vehicle-Road Performance.

em CentAUR: Central Archive University of Reading - UK


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We extend the theory of the multinational enterprise (MNE) by exploring the concept of subsidiary-specific advantages (SSAs) as a driver for subsidiary performance. We investigate the relationship of host country-specific advantages (host CSAs) in the form of market attractiveness, SSAs and subsidiary sales as they affect subsidiary performance. From an original primary dataset of 101 British multinational (MNE) subsidiaries in six South East Asian countries, our analysis reveals three significant findings. First, host market attractiveness has a statistically positive impact on the performance of subsidiaries. Second, the three traditional SSAs of general management, marketing capabilities and invested capital enhance subsidiary performance. Third, we examine geographic direction and types of customers for subsidiary sales by following international accounting standards. We find that these subsidiaries generate on average 95 percent of total sales from the Asia Pacific region and 91 percent of total sales from external customers. Our findings have important research and managerial implications.

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Motor vehicle accidents are one of the principal causes of adolescent disability or mortality and male drivers are more likely to be involved in road accidents than female drivers. In part such associations between driver age and sex have been linked to differences in risky behaviour (e.g. speed, violations) and individual characteristics (e.g. sensation seeking, deviant behaviour). The aim of this research is to determine whether associations between risky road user behaviour and individual characteristics are a function of driver behaviour or whether they are intrinsic and measurable in individuals too young to drive. Five hundred and sixty-seven pre-driver students aged 11-16 from three secondary schools completed questionnaires measuring enthusiasm for speed, sensation seeking, deviant behaviour and attitudes towards driver violations. Boys reported more risky attitudes than girls for all measures. Associations between sensation seeking, deviant behaviour and attitudes towards risky road use were present from early adolescence and were strongest around age 14, before individuals learn to drive. Risky attitudes towards road use are associated with individual characteristics and are observed in adolescents long before they learn to drive. Safe attitudes towards road use and driver behaviour should be promoted from childhood in order to be effective. (C) 2007 Elsevier Ltd. All rights reserved.

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Planning is one of the key problems for autonomous vehicles operating in road scenarios. Present planning algorithms operate with the assumption that traffic is organised in predefined speed lanes, which makes it impossible to allow autonomous vehicles in countries with unorganised traffic. Unorganised traffic is though capable of higher traffic bandwidths when constituting vehicles vary in their speed capabilities and sizes. Diverse vehicles in an unorganised exhibit unique driving behaviours which are analysed in this paper by a simulation study. The aim of the work reported here is to create a planning algorithm for mixed traffic consisting of both autonomous and non-autonomous vehicles without any inter-vehicle communication. The awareness (e.g. vision) of every vehicle is restricted to nearby vehicles only and a straight infinite road is assumed for decision making regarding navigation in the presence of multiple vehicles. Exhibited behaviours include obstacle avoidance, overtaking, giving way for vehicles to overtake from behind, vehicle following, adjusting the lateral lane position and so on. A conflict of plans is a major issue which will almost certainly arise in the absence of inter-vehicle communication. Hence each vehicle needs to continuously track other vehicles and rectify plans whenever a collision seems likely. Further it is observed here that driver aggression plays a vital role in overall traffic dynamics, hence this has also been factored in accordingly. This work is hence a step forward towards achieving autonomous vehicles in unorganised traffic, while similar effort would be required for planning problems such as intersections, mergers, diversions and other modules like localisation.

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Almost all modern cars can be controlled remotely using a personal communicator (keyfob). However, the degree of interaction between currently available personal communicators and cars is very limited. The communication link is unidirectional and the communication range is limited to a few dozen meters. However, there are many interesting applications that could be supported if a keyfob would be able to support energy efficient bidirectional longer range communication. In this paper we investigate off-the-shelf transceivers in terms of their usability for bidirectional longer range communication. Our evaluation results show that existing transceivers can generally support the required communication ranges but that links tend to be very unreliable. This high unreliability must be handled in an energy efficient way by the keyfob to car communication protocol in order to make off-the-shelf transceivers a viable solution.

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This paper reports the current state of work to simplify our previous model-based methods for visual tracking of vehicles for use in a real-time system intended to provide continuous monitoring and classification of traffic from a fixed camera on a busy multi-lane motorway. The main constraints of the system design were: (i) all low level processing to be carried out by low-cost auxiliary hardware, (ii) all 3-D reasoning to be carried out automatically off-line, at set-up time. The system developed uses three main stages: (i) pose and model hypothesis using 1-D templates, (ii) hypothesis tracking, and (iii) hypothesis verification, using 2-D templates. Stages (i) & (iii) have radically different computing performance and computational costs, and need to be carefully balanced for efficiency. Together, they provide an effective way to locate, track and classify vehicles.

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The rapid growth of non-listed real estate funds over the last several years has contributed towards establishing this sector as a major investment vehicle for gaining exposure to commercial real estate. Academic research has not kept up with this development, however, as there are still only a few published studies on non-listed real estate funds. This paper aims to identify the factors driving the total return over a seven-year period. Influential factors tested in our analysis include the weighted underlying direct property returns in each country and sector as well as fund size, investment style gearing and the distribution yield. Furthermore, we analyze the interaction of non-listed real estate funds with the performance of the overall economy and that of competing asset classes and found that lagged GDP growth and stock market returns as well as contemporaneous government bond rates are significant and positive predictors of annual fund performance.

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An unlisted property fund is a private investment vehicle which aims to provide direct property total returns and may also employ financial leverage which will accentuate performance. They have become a far more prevalent institutional property investment conduit since the early 2000’s. Investors have been primarily attracted to them due to the ease of executing a property exposure, both domestically and internationally, and for their diversification benefits given the capital intensive nature of constructing a well diversified commercial property investment portfolio. However, despite their greater prominence there has been little academic research conducted on the performance and risks of unlisted property fund investments. This can be attributed to a paucity of available data and limited time series where it exists. In this study we have made use of a unique dataset of institutional UK unlisted non-listed property funds over the period 2003Q4 to 2011Q4, using a panel modelling framework in order to determine the key factors which impact on fund performance. The sample provided a rich set of unlisted property fund factors including market exposures, direct property characteristics and the level of financial leverage employed. The findings from the panel regression analysis show that a small number of variables are able to account for the performance of unlisted property funds. These variables should be considered by investors when assessing the risk and return of these vehicles. The impact of financial leverage upon the performance of these vehicles through the recent global financial crisis and subsequent UK commercial property market downturn was also studied. The findings indicate a significant asymmetric effect of employing debt finance within unlisted property funds.

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The problem of planning multiple vehicles deals with the design of an effective algorithm that can cause multiple autonomous vehicles on the road to communicate and generate a collaborative optimal travel plan. Our modelling of the problem considers vehicles to vary greatly in terms of both size and speed, which makes it suboptimal to have a faster vehicle follow a slower vehicle or for vehicles to drive with predefined speed lanes. It is essential to have a fast planning algorithm whilst still being probabilistically complete. The Rapidly Exploring Random Trees (RRT) algorithm developed and reported on here uses a problem specific coordination axis, a local optimization algorithm, priority based coordination, and a module for deciding travel speeds. Vehicles are assumed to remain in their current relative position laterally on the road unless otherwise instructed. Experimental results presented here show regular driving behaviours, namely vehicle following, overtaking, and complex obstacle avoidance. The ability to showcase complex behaviours in the absence of speed lanes is characteristic of the solution developed.

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Chaotic traffic, prevalent in many countries, is marked by a large number of vehicles driving with different speeds without following any predefined speed lanes. Such traffic rules out using any planning algorithm for these vehicles which is based upon the maintenance of speed lanes and lane changes. The absence of speed lanes may imply more bandwidth and easier overtaking in cases where vehicles vary considerably in both their size and speed. Inspired by the performance of artificial potential fields in the planning of mobile robots, we propose here lateral potentials as measures to enable vehicles to decide about their lateral positions on the road. Each vehicle is subjected to a potential from obstacles and vehicles in front, road boundaries, obstacles and vehicles to the side and higher speed vehicles to the rear. All these potentials are lateral and only govern steering the vehicle. A speed control mechanism is also used for longitudinal control of vehicle. The proposed system is shown to perform well for obstacle avoidance, vehicle following and overtaking behaviors.

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There were 338 road fatalities on Irish roads in 2007. Research in 2007 by the Road Safety Authority in Ireland states that young male drivers (17 – 25 years) are seven times more likely to be killed on Irish roads than other road users. The car driver fatality rate was found to be approximately 10 times higher for young male drivers than for female drivers in 2000. Young male drivers in particular demonstrate a high proclivity for risky driving behaviours. These risky behaviours include drink driving, speeding, rug-driving and engaging in aggressive driving. Speed is the single largest contributing factor to road deaths in Ireland. Approximately 40% of fatal accidents are caused by excessive or inappropriate speed. This study focuses on how dangerous driving behaviours may be addressed through social marketing. This study analyses the appropriate level of fear that needs to be induced in order to change young male driving behaviour.

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Background: Daily consumption of Concord grape juice (CGJ) over three to four months has been shown to improve memory function in adults with mild cognitive impairment, and reduce blood pressure in hypertensive adults. These benefits are likely due to the high concentration of polyphenols in CGJ. Increased stress can impair cognitive function and elevate blood pressure. Thus we examined the potential beneficial effect of CGJ in individuals experiencing somewhat stressful demanding lifestyles. Objective: To examine the effects of twelve weeks’ daily consumption of CGJ on cognitive function, driving performance, and blood pressure in healthy, middle-aged working mothers. Design: Twenty five healthy mothers of pre-teen children, aged 40-50 years, who were employed for > 30 hours/week consumed 12oz (355ml) CGJ (containing 777mg total polyphenols) or an energy, taste and appearance matched placebo daily for twelve weeks according to a randomised, crossover design with a four week washout. Verbal and spatial memory, executive function, attention, blood pressure and mood were assessed at baseline, six weeks and twelve weeks. Immediately following the cognitive battery, a subsample of seventeen females completed a driving performance assessment in the University of Leeds Driving Simulator. The twenty five minute driving task required participants to match the speed and direction of a lead vehicle. Results: Significant improvements in immediate spatial memory and driving performance were observed following CGJ relative to placebo. There was evidence of an enduring effect of CGJ such that participants who received CGJ in arm 1 maintained better performance in the placebo arm. Conclusions: Cognitive benefits associated with chronic consumption of flavonoid-rich grape juice are not exclusive to adults with mild cognitive impairment. Moreover, these cognitive benefits are apparent in complex everyday tasks such as driving. Effects may persist beyond cessation of flavonoid consumption and future studies should carefully consider the length of washout within crossover designs.