610 resultados para car-like vehicle visual servoing


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Vehicle speed is an important attribute for the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to the traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus; in-service bus during peak; and in-service bus during off peak periods with average car are proposed. The models are cross-validated and the interrelationships are significant

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This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

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The performance of visual speech recognition (VSR) systems are significantly influenced by the accuracy of the visual front-end. The current state-of-the-art VSR systems use off-the-shelf face detectors such as Viola- Jones (VJ) which has limited reliability for changes in illumination and head poses. For a VSR system to perform well under these conditions, an accurate visual front end is required. This is an important problem to be solved in many practical implementations of audio visual speech recognition systems, for example in automotive environments for an efficient human-vehicle computer interface. In this paper, we re-examine the current state-of-the-art VSR by comparing off-the-shelf face detectors with the recently developed Fourier Lucas-Kanade (FLK) image alignment technique. A variety of image alignment and visual speech recognition experiments are performed on a clean dataset as well as with a challenging automotive audio-visual speech dataset. Our results indicate that the FLK image alignment technique can significantly outperform off-the shelf face detectors, but requires frequent fine-tuning.

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Road crashes contribute to a significant amount of child mortality and morbidity in Australia. In fact, passenger injuries contribute to the majority of child crash road trauma. A number of factors contribute to child injury and death in motor vehicles, including inappropriate seating position, inappropriate choice of restraint, and incorrect installation and use of child restraints. Prior to March 2010, child restraint legislation in Queensland only required children twelve months and younger to be seated in a properly adjusted and fastened child restraint. This legislation left older infants and young children potentially suboptimally protected. From March 2010, new legislation specified seating position and type of child restraint required, depending on the age of the child. This research was underpinned by the Health Belief Model (HBM), which explores health related behaviour, behaviour change, environmental factors influencing behaviour change (including legislative changes) and is flexible enough to be used in relation to parents' health practices for their children, rather than parent health directly. This thesis investigates the extent to which the changes to child restraint legislation have led parents in regional areas of Queensland to use appropriate restraint practices for their children and determines the extent to which the constructs of the HBM, parental perceptions, barriers and environmental factors contribute to the appropriateness of child seating and restraint use. Study One included three sets of observations taken in two regional cities of Queensland prior to the legislative amendment, during an educative period of six months, and after the enactment of the legislation. Each child's seating position and restraint type were recorded. Results showed that the proportion of children observed occupying the front seat decreased by 15.6 per cent with the announcement the legislation. There was no decrease in front seat use at the enactment of the legislation. The proportion of children observed using dedicated child restraints increased by 8.8 per cent with the announcement of the legislation when there was one child in the vehicle. Further, there was a 10.1 per cent increase in the proportion of children observed using a seat belt that fit with the announcement when there was one child in the vehicle and with the enactment of the legislation regardless of the number of children in the vehicle (21.8 per cent for one child, 39.7 per cent for two children and 40.2 per cent for three or more children). Study Two comprised initial intercept interviews, later followed up by telephone, with parents with children aged eight years and younger at the announcement and telephone interviews at the enactment of the legislation in one regional city in Queensland. Parents reported their child restraint practices, and opinions, knowledge and understanding of the requirements of the new legislation. Parent responses were analysed in terms of the constructs in the HBM. When asked which seating position their child 'usually' used, parents reported child front seat use was nil (0.0 per cent) and did not change with the enactment of the legislative amendment. However, when parents were asked whether they allowed children to use the front seat at some point within the six months prior to the interview, reported child front seat use was 7 (5.4 per cent) children at T2 and 10 (9.6 per cent) at T3. Reported use of age-appropriate child restraints did not increase with the enactment of the legislation (p = 0.77, ns). Parents reported restraint practices were classed as either appropriate or inappropriate. Parents who reported appropriate restraint practices were those whose children were sitting in optimal restraints and seating positions for their age according to the requirements of the legislation. Parents who reported inappropriate restraint practices were those who had one or more children who were suboptimally restrained or seated for their age according to the requirements of the legislation. Neither parents' perceptions about their susceptibility of being in a crash nor the likelihood of severity of child injury if involved in a crash yielded significant differences in the appropriateness of reported parent restraint practices over time with the enactment of the legislation. A trend in the data suggested parents perceived a benefit to using appropriate restraint practices was to avoid fines and demerit points. Over 75 per cent of parents who agreed that child restraints provide better protection for children than an adult seat belt reported appropriately seating and restraining their children (2 (1) = 8.093, p<.05). The self-efficacy measure regarding parents' confidence in installing a child restraint showed a significant association with appropriate parental restraint practices (2 (1) = 7.036, p<.05). Results suggested that some parents may have misinterpreted the announcement of the legislative amendment as the announcement of the enforcement of the legislation instead. Some parents who correctly reported details of the legislation did not report appropriate child restraint practices. This finding shows that parents' knowledge of the legislative amendment does not necessarily have an impact on their behaviour to appropriately seat and restrain children. The results of these studies have important implications for road safety and the prevention of road-related injury and death to children in Queensland. Firstly, parents reported feeling unsure of how to install restraints, which suggests that there may be children travelling in restraints that have not been installed correctly, putting them at risk. Interventions to alert and encourage parents to seek advice when unsure about the correct installation of child restraints could be considered. Secondly, some parents in this study although they were using the most appropriate restraint for their children, reported using a type that was not the most appropriate restraint for the child's age according to the legislation. This suggests that intervention may be effective in helping parents make a more accurate choice of the most appropriate type of restraint to use with children, especially as the child ages and child restraint requirements change. Further research could be conducted to ascertain the most effective methods of informing and motivating parents to use the most appropriate restraints and seating positions for their children, as these results show a concerning disparity between reported restraint practices and those that were observed.

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Electric vehicle battery packs require DC circuit breakers for safety. These must break thousands of Amps DC at hundreds of Volts. The Sunshark solar racing car has a 140V 17Ahr battery box which needs such a breaker. A static design using 200V MOSFETs to interrupt the fault current is presented. The design specification, decisions and proposed solution circuit are given. The current sensing technique,MOSFET overvoltage protection, and DC bus capacitor precharging scheme are specific focuses. Simulation results are presented and discussed.

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In this paper, we present SMART (Sequence Matching Across Route Traversals): a vision- based place recognition system that uses whole image matching techniques and odometry information to improve the precision-recall performance, latency and general applicability of the SeqSLAM algorithm. We evaluate the system’s performance on challenging day and night journeys over several kilometres at widely varying vehicle velocities from 0 to 60 km/h, compare performance to the current state-of- the-art SeqSLAM algorithm, and provide parameter studies that evaluate the effectiveness of each system component. Using 30-metre sequences, SMART achieves place recognition performance of 81% recall at 100% precision, outperforming SeqSLAM, and is robust to significant degradations in odometry.

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The ability to automate forced landings in an emergency such as engine failure is an essential ability to improve the safety of Unmanned Aerial Vehicles operating in General Aviation airspace. By using active vision to detect safe landing zones below the aircraft, the reliability and safety of such systems is vastly improved by gathering up-to-the-minute information about the ground environment. This paper presents the Site Detection System, a methodology utilising a downward facing camera to analyse the ground environment in both 2D and 3D, detect safe landing sites and characterise them according to size, shape, slope and nearby obstacles. A methodology is presented showing the fusion of landing site detection from 2D imagery with a coarse Digital Elevation Map and dense 3D reconstructions using INS-aided Structure-from-Motion to improve accuracy. Results are presented from an experimental flight showing the precision/recall of landing sites in comparison to a hand-classified ground truth, and improved performance with the integration of 3D analysis from visual Structure-from-Motion.

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There are currently more than 400 cities operating bike share programs. Purported benefits of bike share programs include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washing, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometres traveled. The results indicate that the estimated mean reduction in car use due to bike share is at least twice the distance covered by operator support vehicles, with the exception of London, in which the relationship is reversed, largely due to a low car mode substitution rate. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. This paper reveals that by increasing the convenience of bike share relative to car use and by improving perceptions of safety, the capacity of bike share programs to reduce vehicle trips and yield overall net benefits will be enhanced. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.

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This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

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Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

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The social cost of road injury and fatalities is still unacceptable. The driver is often mainly responsible for road crashes, therefore changing the driver behaviour is one of the most important and most challenging priority in road transport. This paper presents three innovative visions that articulate the potential of using Vehicle to Vehicle (V2V) communication for supporting the exchange of social information amongst drivers. We argue that there could be tremendous benefits in socialising cars to influence human driving behaviours for the better and that this aspect is still relevant in the age of looming autonomous cars. Our visions provide theoretical grounding how V2V infrastructure and emerging human–machine interfaces (HMI) could persuade drivers to: (i) adopt better (e.g. greener) driving practices, (ii) reduce drivers aggressiveness towards pro-social driving behaviours, and (iii) reduce risk-taking behaviour in young, particularly male, adults. The visions present simple but powerful concepts that reveal ‘good’ aspects of the driver behaviour to other drivers and make them contagious. The use of self-efficacy, social norms, gamification theories and social cues could then increase the likelihood of a widespread adoption of such ‘good’ driving behaviours.

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This paper investigates whether the net benefits from owning a vehicle, proxied by annual miles driven, explain the price declines observed over a vehicle's life. We first model the household decision on how much to drive each of its vehicles. Then we empirically establish that variation in household annual miles across brands explains observed price declines. Furthermore, the effect of vehicle age on annual miles decisions (and consequently on market value) depends on household characteristics and the composition of the vehicle stock owned.

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There are currently more than 700 cities operating bike share programs. Purported benefits of bike share include flexible mobility, physical activity, reduced congestion, emissions and fuel use. Implicit or explicit in the calculation of program benefits are assumptions regarding the modes of travel replaced by bike share journeys. This paper examines the degree to which car trips are replaced by bike share, through an examination of survey and trip data from bike share programs in Melbourne, Brisbane, Washington, D.C., London, and Minneapolis/St. Paul. A secondary and unique component of this analysis examines motor vehicle support services required for bike share fleet rebalancing and maintenance. These two components are then combined to estimate bike share’s overall contribution to changes in vehicle kilometers traveled. The results indicate an estimated reduction in motor vehicle use due to bike share of approx. 90,000 km per annum in Melbourne and Minneapolis/St. Paul and 243,291 km for Washington, D.C. London’s bike share program however recorded an additional 766,341 km in motor vehicle use. This was largely due to a low car mode substitution rate and substantial truck use for rebalancing of bicycles. As bike share programs mature, evaluation of their effectiveness in reducing car use may become increasingly important. Researchers can adapt the analytical approach proposed in this paper to assist in the evaluation of current and future bike share programs.