920 resultados para intelligent vehicle air conditioning


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Pedestrians’ use of mp3 players or mobile phones can pose the risk of being hit by motor vehicles. We present an approach for detecting a crash risk level using the computing power and the microphone of mobile devices that can be used to alert the user in advance of an approaching vehicle so as to avoid a crash. A single feature extractor classifier is not usually able to deal with the diversity of risky acoustic scenarios. In this paper, we address the problem of detection of vehicles approaching a pedestrian by a novel, simple, non resource intensive acoustic method. The method uses a set of existing statistical tools to mine signal features. Audio features are adaptively thresholded for relevance and classified with a three component heuristic. The resulting Acoustic Hazard Detection (AHD) system has a very low false positive detection rate. The results of this study could help mobile device manufacturers to embed the presented features into future potable devices and contribute to road safety.

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This paper is directed towards providing an answer to the question, ”Can you control the trajectory of a Lagrangian float?” Being a float that has minimal actuation (only buoyancy control), their horizontal trajectory is dictated through drifting with ocean currents. However, with the appropriate vertical actuation and utilising spatio-temporal variations in water speed and direction, we show here that broad controllabilty results can be met such as waypoint following to keep a float inside of a bay or out of a designated region. This paper extends theory experimen- tally evaluted on horizontally actuated Autonomous Underwater Vehicles (AUVs) for trajectory control utilising ocean forecast models and presents an initial investi- gation into the controllability of these minimally actuated drifting AUVs. Simulated results for offshore coastal and within highly dynamic tidal bays illustrate two tech- niques with the promise for an affirmative answer to the posed question above.

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Commuting in various transport modes represents an activity likely to incur significant exposure to traffic emissions. This study investigated the determinants and characteristics of exposure to ultrafine (< 100 nm) particles (UFPs) in four transport modes in Sydney, with a specific focus on exposure in automobiles, which remain the transport mode of choice for approximately 70% of Sydney commuters. UFP concentrations were measured using a portable condensation particle counter (CPC) inside five automobiles commuting on above ground and tunnel roadways, and in buses, ferries and trains. Determinant factors investigated included wind speed, cabin ventilation (automobiles only) and traffic volume. The results showed that concentrations varied significantly as a consequence of transport mode, vehicle type and ventilation characteristics. The effects of wind speed were minimal relative to those of traffic volume (especially heavy diesel vehicles) and cabin ventilation, with the latter proving to be a strong determinant of UFP ingress into automobiles. The effect of ~70 minutes of commuting on total daily exposure was estimated using a range of UFP concentrations reported for several microenvironments. A hypothetical Sydney resident commuting by automobile and spending 8.5 minutes of their day in the M5 East tunnel could incur anywhere from a lower limit of 3-11% to an upper limit of 37-69% of daily UFP exposure during a return commute, depending on the concentrations they encountered in other microenvironments, the type of vehicle they used and the ventilation setting selected. However, commute-time exposures at either extreme of the values presented are unlikely to occur in practice. The range of exposures estimated for other transport modes were comparable to those of automobiles, and in the case of buses, higher than automobiles.

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Travel in passenger cars is a ubiquitous aspect of the daily activities of many people. During the 2009 influenza A (H1N1) pandemic a case of probable transmission during car travel was reported in Australia, to which spread via the airborne route may have contributed. However, there are no data to indicate the likely risks of such events, and how they may vary and be mitigated. To address this knowledge gap, we estimated the risk of airborne influenza transmission in two cars (1989 model and 2005 model) by employing ventilation measurements and a variation of the Wells-Riley model. Results suggested that infection risk can be reduced by not recirculating air; however, estimated risk ranged from 59 to 99.9% for a 90 min trip when air was recirculated in the newer vehicle. These results have implications for interrupting in-car transmission of other illnesses spread by the airborne route.

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In this paper, we examine the use of a Kalman filter to aid in the mission planning process for autonomous gliders. Given a set of waypoints defining the planned mission and a prediction of the ocean currents from a regional ocean model, we present an approach to determine the best, constant, time interval at which the glider should surface to maintain a prescribed tracking error, and minimizing time on the ocean surface. We assume basic parameters for the execution of a given mission, and provide the results of the Kalman filter mission planning approach. These results are compared with previous executions of the given mission scenario.

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• What is risk compensation, and why is relevant to motor vehicle crashes? • Recent simulator work that revealed risk compensation • Current and future work on risk compensation

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Seat pressure is known as a major factor of seat comfort in vehicles. In passenger vehicles, there is lacking research into the seat comfort of rear seat occupants. As accurate seat pressure measurement requires significant effort, simulation of seat pressure is evolving as a preferred method. However, analytic methods are based on complex finite element modeling and therefore are time consuming and involve high investment. Based on accurate anthropometric measurements of 64 male subjects and outboard rear seat pressure measurements in three different passenger vehicles, this study investigates if a set of parameters derived from seat pressure mapping are sensitive enough to differentiate between different seats and whether they correlate with anthropometry in linear models. In addition to the pressure map analysis, H-Points were measured with a coordinate measurement system based on palpated body landmarks and the range of H-Point locations in the three seats is provided. It was found that for the cushion, cushion contact area and cushion front area/force could be modeled by subject anthropometry,while only seatback contact area could be modeled based on anthropometry for all three vehicles. Major differences were found between the vehicles for other parameters.

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In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

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In order to gain a competitive edge in the market, automotive manufacturers and automotive seat suppliers have identified seat ergonomics for further development to improve overall vehicle comfort. Adjustable lumbar support devices have been offered since long as comfort systems in either a 2-way or 4-way adjustable configuration, although their effect on lumbar strain is not well documented. The effect of a lumbar support on posture and muscular strain, and therefore the relationship between discomfort and comfort device parameter settings, requires clarification. The aim of this paper is to study the effect of a 4-way lumbar support on lower trunk and pelvis muscle activity, pelvic tilt and spine curvature during a car seating activity. 10 healthy subjects (5 m/f; age 19-39) performed a seating activity in a passenger vehicle with seven different static lumbar support positions. The lumbar support was tested in 3 different height positions in relation to the seatback surface centreline (high, centre, low), each having 2 depths positions (lumbar prominence). An extra depth position was added for the centre position. Posture data were collected using a VICON MX motion capture system and NORAXON DTS goniometers and inclinometer. A rigid-body model of an adjustable car seat with four-way adjustable lumbar support was constructed in UGS Siemens NX and connected to a musculoskeletal model of a seated-human, modelled in AnyBody. Wireless electromyography (EMG) was used to calibrate the musculoskeletal model and assess the relationship between (a) muscular strain and lumbar prominence (normal to seatback surface) respective to the lumbar height (alongside seatback surface), (b) hip joint moment and lumbar prominence (normal to seatback surface) respective to lumbar height (alongside seatback surface) and (c) pelvic tilt and lumbar prominence (normal to seatback surface) respective to the lumbar height (alongside seatback surface). This study was based on the assumption that the musculoskeletal human model was seated at the correct R-Point (SgRP), determined via the occupant packaging toolkit in the JACK digital human model. The effect of the interaction between the driver/car-seat has been investigated for factors resulting from the presence and adjustment of a 4-way lumbar support. The results obtained show that various seat adjustments, and driver’s lumbar supports can have complex influence on the muscle activation, joint forces and moments, all of which can affect the comfort perception of the driver. This study enables the automotive industry to optimise passenger vehicle seat development and design. It further more supports the evaluation of static postural and dynamic seat comfort in normal everyday driving tasks and can be applied for future car design to reduce investment and improve comfort.

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Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

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This paper discusses and summarises a recent systematic study on the implication of global warming on air conditioned office buildings in Australia. Four areas are covered, including analysis of historical weather data, generation of future weather data for the impact study of global warming, projection of building performance under various global warming scenarios, and evaluation of various adaptation strategies under 2070 high global warming conditions. Overall, it is found that depending on the assumed future climate scenarios and the location considered, the increase of total building energy use for the sample Australian office building may range from 0.4 to 15.1%. When the increase of annual average outdoor temperature exceeds 2 °C, the risk of overheating will increase significantly. However, the potential overheating problem could be completely eliminated if internal load density is significantly reduced.