248 resultados para car-like vehicle pose control


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Automotive interactive technologies represent an exemplar challenge for user experience (UX) designers, as the concerns for aesthetics, functionality and usability add up to the compelling issues of safety and cognitive demand. This extended abstract presents a methodology for the user-centred creation and evaluation of novel in-car applications, involving real users in realistic use settings. As a case study, we present the methodologies of an ideation workshop in a simulated environment and the evaluation of six design idea prototypes for in-vehicle head up display (HUD) applications using a semi-naturalistic drive. Both methods rely on video recordings of real traffic situations that the users are familiar with and/or experienced themselves. The extended abstract presents experiences and results from the evaluation and reflection on our methods.

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This paper describes a series of trials that were done at an underground mine in New South Wales, Australia. Experimental results are presented from the data obtained during the field trials and suitable sensor suites for an autonomous mining vehicle navigation system are evaluated.

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This paper describes current research at the Australian Centre for Field Robotics (ACFR) in collaboration with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) within the Cooperative Research Centre (CRC) for Mining Technology and Equipment (CMTE) towards achieving autonomous navigation of underground vehicles, like a Load-Haul-Dump (LHD) truck. This work is being sponsored by the mining industry through the Australian Mineral Industries Research Association Limited (AMIRA). Robust and reliable autonomous navigation can only be realised by achieving high level tasks such as path-planning and obstacle avoidance. This requires determining the pose (position and orientation) of the vehicle at all times. A minimal infrastructure localisation algorithm that has been developed for this purpose is outlined and the corresponding results are presented. Further research issues that are under investigation are also outlined briefly.

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This paper presents a novel path planning method for minimizing the energy consumption of an autonomous underwater vehicle subjected to time varying ocean disturbances and forecast model uncertainty. The algorithm determines 4-Dimensional path candidates using Nonlinear Robust Model Predictive Control (NRMPC) and solutions optimised using A*-like algorithms. Vehicle performance limits are incorporated into the algorithm with disturbances represented as spatial and temporally varying ocean currents with a bounded uncertainty in their predictions. The proposed algorithm is demonstrated through simulations using a 4-Dimensional, spatially distributed time-series predictive ocean current model. Results show the combined NRMPC and A* approach is capable of generating energy-efficient paths which are resistant to both dynamic disturbances and ocean model uncertainty.

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Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

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There is an increasing demand for Unmanned Aerial Systems (UAS) to carry suspended loads as this can provide significant benefits to several applications in agriculture, law enforcement and construction. The load impact on the underlying system dynamics should not be neglected as significant feedback forces may be induced on the vehicle during certain flight manoeuvres. The constant variation in operating point induced by the slung load also causes conventional controllers to demand increased control effort. Much research has focused on standard multi-rotor position and attitude control with and without a slung load. However, predictive control schemes, such as Nonlinear Model Predictive Control (NMPC), have not yet been fully explored. To this end, we present a novel controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions. The paper describes a System Dynamics and Control Simulation Toolbox for use with MATLAB/SIMULINK which includes a detailed simulation of the multi-rotor and slung load as well as a predictive controller to manage the nonlinear dynamics whilst accounting for system constraints. It is demonstrated that the controller simultaneously tracks specified waypoints and actively damps large slung load oscillations. A linear-quadratic regulator (LQR) is derived and control performance is compared. Results show the improved performance of the predictive controller for a larger flight envelope, including aggressive manoeuvres and large slung load displacements. The computational cost remains relatively small, amenable to practical implementations.

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Human factors such as distraction, fatigue, alcohol and drug use are generally ignored in car-following (CF) models. Such ignorance overestimates driver capability and leads to most CF models’ inability in realistically explaining human driving behaviors. This paper proposes a novel car-following modeling framework by introducing the difficulty of driving task measured as the dynamic interaction between driving task demand and driver capability. Task difficulty is formulated based on the famous Task Capability Interface (TCI) model, which explains the motivations behind driver’s decision making. The proposed method is applied to enhance two popular CF models: Gipps’ model and IDM, and named as TDGipps and TDIDM respectively. The behavioral soundness of TDGipps and TDIDM are discussed and their stabilities are analyzed. Moreover, the enhanced models are calibrated with the vehicle trajectory data, and validated to explain both regular and human factor influenced CF behavior (which is distraction caused by hand-held mobile phone conversation in this paper). Both the models show better performance than their predecessors, especially in presence of human factors.

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Objectives: To assess the possible association of killer immunoglobulin-like receptor (KIR) genes, specifically KIR3DL1, KIR3DS1 and KIR3DL2, with ankylosing spondylitis (AS). Methods: 14 KIR genes were genotyped in 200 UK patients with AS and 405 healthy controls using multiplex polymerase chain reaction. Sequence-specific oligonucleotide probes were used to subtype 368 cases with AS and 366 controls for 12 KIR3DL2 alleles. Differences in KIR genotypes and KIR3DL2 allele frequencies were assessed using the χp2p test. Results: KIR3DL1 and KIR3DS1 gene frequencies were very similar in cases with AS and controls (odds ratio = 1.5, 95% confidence interval 0.8 to 3.0, and odds ratio = 1.02, 95% confidence interval 0.2 to 5.3, respectively). KIR3DL2 allele frequencies were not significantly different between cases with AS and controls. Conclusions: Neither the KIR gene content of particular KIR haplotypes nor KIR3DL2 polymorphisms contribute to AS.

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A global framework for linear stability analyses of traffic models, based on the dispersion relation root locus method, is presented and is applied taking the example of a broad class of car-following (CF) models. This approach is able to analyse all aspects of the dynamics: long waves and short wave behaviours, phase velocities and stability features. The methodology is applied to investigate the potential benefits of connected vehicles, i.e. V2V communication enabling a vehicle to send and receive information to and from surrounding vehicles. We choose to focus on the design of the coefficients of cooperation which weights the information from downstream vehicles. The coefficients tuning is performed and different ways of implementing an efficient cooperative strategy are discussed. Hence, this paper brings design methods in order to obtain robust stability of traffic models, with application on cooperative CF models

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Aim: To systematically review the literature investigating the incidence of fatal and or nonfatal low-speed vehicle run-over (LSVRO) incidents in children aged 0–15 years. Methods: The following databases were searched using specific search terms, from their date of conception up to June 2011: Cochrane Library, Medline, CINAHL, Embase, AMI, Sociological Abstracts, ERIC, PsycArticles, PsycInfo, Urban Studies and Planning; Australian Criminology Database; Dissertations and Thesis; Academic Research Library; Social Services Abstracts; Family and Society; Scopus; and Web of Science. A total of 128 articles were identified in the databases (33 found by hand searching). The title and abstract of these were read, and 102 were removed because they were not primary research articles relating to LSVRO-type injuries. Twenty-six articles were assessed against the inclusion (reporting population level incidence rates) and exclusion criteria, 19 of which were excluded, leaving a total of five articles for inclusion in the review. Findings: Five studies were identified that met the inclusion criteria. The incidence rate in nonfatal LSVRO events varied in the range of 7.09 to 14.79 per 100,000 and from 0.63 to 3.2 per 100,000 in fatal events. Discussion: Using International Classification of Diseases codes for classifying fatal or nonfatal LSVRO incidents is problematic as there is no specific code for LSVRO. The current body of research is void of a comprehensive secular population data analysis. Only with an improved spectrum of incidence rates will appropriate evaluation of this problem be possible, and this will inform nursing prevention interventions. The effect of LSVRO incidents is clearly understudied. More research is required to address incidence rates in relation to culture, environment, risk factors, car design, and injury characteristics. Conclusions: Thevlack of nursing research or policy around this area of injury, most often to children, indicates a field of inquiry and policy development that needs attention.

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Stability analyses have been widely used to better understand the mechanism of traffic jam formation. In this paper, we consider the impact of cooperative systems (a.k.a. connected vehicles) on traffic dynamics and, more precisely, on flow stability. Cooperative systems are emerging technologies enabling communication between vehicles and/or with the infrastructure. In a distributed communication framework, equipped vehicles are able to send and receive information to/from other equipped vehicles. Here, the effects of cooperative traffic are modeled through a general bilateral multianticipative car-following law that improves cooperative drivers' perception of their surrounding traffic conditions within a given communication range. Linear stability analyses are performed for a broad class of car-following models. They point out different stability conditions in both multianticipative and nonmultianticipative situations. To better understand what happens in unstable conditions, information on the shock wave structure is studied in the weakly nonlinear regime by the mean of the reductive perturbation method. The shock wave equation is obtained for generic car-following models by deriving the Korteweg de Vries equations. We then derive traffic-state-dependent conditions for the sign of the solitary wave (soliton) amplitude. This analytical result is verified through simulations. Simulation results confirm the validity of the speed estimate. The variation of the soliton amplitude as a function of the communication range is provided. The performed linear and weakly nonlinear analyses help justify the potential benefits of vehicle-integrated communication systems and provide new insights supporting the future implementation of cooperative systems.

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Objective To investigate the association of CD14 and Toll-like receptor (TLR4) with ankylosing spondylitis (AS). Methods A promoter variant in CD14 and 2 coding polymorphisms in TLR4 were investigated in UK and Finnish families with AS and in a UK case-control study. A metaanalysis of published TLR4 and CD14 studies was performed. Results In the Finnish study the CD74-260bp T variant showed an association (p = 0.006), and the common 2-marker TLR4 haplotype showed a weak association (global p = 0.03), with AS. No associations were seen in the UK based studies or in the metaanalyses. Conclusion CD14 and TLR4 showed an association with AS in the Finns only.

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This paper presents a motion control system for guidance of an underactuated Unmanned Underwater Vehicle (UUV) on a helical trajectory. The control strategy is developed using Port-Hamiltonian theory and interconnection and damping assignment passivity-based control. Using energy routing, the trajectory of a virtual fully actuated plant is guided onto a vector field. A tracking controller is then used that commands the underactuated plant to follow the velocity of the virtual plant. An integral control is inserted between the two control layers, which adds robustness and disturbance rejection to the design.

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Aggressive driving has been shown to be related to increased crash risk for car driving. However, less is known about aggressive behaviour and motorcycle riding and whether there are differences in on-road aggression as a function of vehicle type. If such differences exist, these could relate to differences in perceptions of relative vulnerability associated with characteristics of the type of vehicle such as level of protection and performance. Specifically, the relative lack of protection offered by motorcycles may cause riders to feel more vulnerable and therefore to be less aggressive when they are riding compared to when they are driving. This study examined differences in self-reported aggression as a function of two vehicle types: passenger cars and motorcycles. Respondents (n = 247) were all motorcyclists who also drove a car. Results were that scores for the composite driving aggression scale were significantly higher than on the composite riding aggression scale. Regression analyses identified different patterns of predictors for driving aggression from those for riding aggression. Safety attitudes followed by thrill seeking tendencies were the strongest predictors for driving aggression, with more positive safety attitudes being protective while greater thrill seeking was associated with greater self-reported aggressive driving behaviour. For riding aggression, thrill seeking was the strongest predictor (positive relationship), followed by self-rated skill, such that higher self rated skill was protective against riding aggression. Participants who scored at the 85th percentile or above for the aggressive driving and aggressive riding indices had significantly higher scores on thrill seeking, greater intentions to engage in future risk taking, and lower safety attitude scores than other participants. In addition participants with the highest aggressive driving scores also had higher levels of self-reported past traffic offences than other participants. Collectively, these findings suggest that people are less likely to act aggressively when riding a motorcycle than when driving a car, and that those who are the most aggressive drivers are different from those who are the most aggressive riders. However, aggressive riders and drivers appear to present a risk to themselves and others on road. Importantly, the underlying influences for aggressive riding or driving that were identified in this study may be amenable to education and training interventions.

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In this paper, the trajectory tracking control of an autonomous underwater vehicle (AUVs) in six-degrees-of-freedom (6-DOFs) is addressed. It is assumed that the system parameters are unknown and the vehicle is underactuated. An adaptive controller is proposed, based on Lyapunov׳s direct method and the back-stepping technique, which interestingly guarantees robustness against parameter uncertainties. The desired trajectory can be any sufficiently smooth bounded curve parameterized by time even if consist of straight line. In contrast with the majority of research in this field, the likelihood of actuators׳ saturation is considered and another adaptive controller is designed to overcome this problem, in which control signals are bounded using saturation functions. The nonlinear adaptive control scheme yields asymptotic convergence of the vehicle to the reference trajectory, in the presence of parametric uncertainties. The stability of the presented control laws is proved in the sense of Lyapunov theory and Barbalat׳s lemma. Efficiency of presented controller using saturation functions is verified through comparing numerical simulations of both controllers.