476 resultados para Parameters estimation


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Bus travel time estimation and prediction are two important modelling approaches which could facilitate transit users in using and transit providers in managing the public transport network. Bus travel time estimation could assist transit operators in understanding and improving the reliability of their systems and attracting more public transport users. On the other hand, bus travel time prediction is an important component of a traveller information system which could reduce the anxiety and stress for the travellers. This paper provides an insight into the characteristic of bus in traffic and the factors that influence bus travel time. A critical overview of the state-of-the-art in bus travel time estimation and prediction is provided and the needs for research in this important area are highlighted. The possibility of using Vehicle Identification Data (VID) for studying the relationship between bus and cars travel time is also explored.

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The existence of the Macroscopic Fundamental Diagram (MFD), which relates network space-mean density and flow, has been shown in urban networks under homogeneous traffic conditions. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. The key requirements for the well-defined MFD is the homogeneity of the area wide traffic condition, which is not universally expected in real world. For the practical application of the MFD concept, several researchers have identified the influencing factors for network homogeneity. However, they did not explicitly take drivers’ behaviour under real time information provision into account, which has a significant impact on the shape of the MFD. This research aims to demonstrate the impact of drivers’ route choice behaviour on network performance by employing the MFD as a measurement. A microscopic simulation is chosen as an experimental platform. By changing the ratio of en-route informed drivers and pre-trip informed drivers as well as by taking different route choice parameters, various scenarios are simulated in order to investigate how drivers’ adaptation to the traffic congestion influences the network performance and the MFD shape. This study confirmed and addressed the impact of information provision on the MFD shape and highlighted the significance of the route choice parameter setting as an influencing factor in the MFD analysis.

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The objective of this research was to investigate the effects of driving conditions and suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. A novel nonlinear model of a multi-axle semi-trailer with longitudinal-connected air suspension was formulated based on fluid mechanics and thermodynamics and was validated through test results. The effects of driving conditions and suspension parameters on dynamic load-sharing and road-friendliness of the semi-trailer were analyzed. Simulation results indicate that the road-friendliness metric-DLC (dynamic load coefficient) is not always in accordance with the load-sharing metric-DLSC (dynamic load-sharing coefficient). The effect of employing larger air lines and connectors on the DLSC optimization ratio gives varying results as road roughness increases and as driving speed increases. When the vehicle load reduces, or the static pressure increases, the DLSC optimization ratio declines monotonically. The results also indicate that if the air line diameter is always assumed to be larger than the connector diameter, the influence of air line diameter on load-sharing is more significant than that of the connector.

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This paper deals with causal effect estimation strategies in highly heterogeneous empirical settings such as entrepreneurship. We argue that the clearer used of modern tools developed to deal with the estimation of causal effects in combination with our analysis of different sources of heterogeneity in entrepreneurship can lead to entrepreneurship with higher internal validity. We specifically lend support from the counterfactual logic and modern research of estimation strategies for causal effect estimation.

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This report is the second deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Freeway Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Freeway Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for Freeway traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for freeway traffic.

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This report is the fourth deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for arterial traffic.

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This report is the eight deliverable of the Real Time and Predictive Traveller Information project and the third deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. Brisbane arterial network is highly equipped with Bluetooth MAC Scanners, which can provide travel time information. Literature is limited with the knowledge on the Bluetooth protocol based data acquisition process and accuracy and reliability of the analysis performed using the data. This report expands the body of knowledge surrounding the use of data from Bluetooth MAC Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.

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The effects of ethanol fumigation on the inter-cycle variability of key in-cylinder pressure parameters in a modern common rail diesel engine have been investigated. Specifically, maximum rate of pressure rise, peak pressure, peak pressure timing and ignition delay were investigated. A new methodology for investigating the start of combustion was also proposed and demonstrated—which is particularly useful with noisy in-cylinder pressure data as it can have a significant effect on the calculation of an accurate net rate of heat release indicator diagram. Inter-cycle variability has been traditionally investigated using the coefficient of variation. However, deeper insight into engine operation is given by presenting the results as kernel density estimates; hence, allowing investigation of otherwise unnoticed phenomena, including: multi-modal and skewed behaviour. This study has found that operation of a common rail diesel engine with high ethanol substitutions (>20% at full load, >30% at three quarter load) results in a significant reduction in ignition delay. Further, this study also concluded that if the engine is operated with absolute air to fuel ratios (mole basis) less than 80, the inter-cycle variability is substantially increased compared to normal operation.

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The effects of small changes in flight-path parameters (primary and secondary flight paths, detector angles), and of displacement of the sample along the beam axis away from its ideal position, are examined for an inelastic time-of-flight (TOF) neutron spectrometer, emphasising the deep-inelastic regime. The aim was to develop a rational basis for deciding what measured shifts in the positions of spectral peaks could be regarded as reliable in the light of the uncertainties in the calibrated flight-path parameters. Uncertainty in the length of the primary or secondary flight path has the least effect on the positions of the peaks of H, D and He, which are dominated by the accuracy of the calibration of the detector angles. This aspect of the calibration of a TOF spectrometer therefore demands close attention to achieve reliable outcomes where the position of the peaks is of significant scientific interest and is discussed in detail. The corresponding sensitivities of the position of peak of the Compton profile, J(y), to flight-path parameters and sample position are also examined, focusing on the comparability across experiments of results for H, D and He. We show that positioning the sample to within a few mm of the ideal position is required to ensure good comparability between experiments if data from detectors at high forward angles are to be reliably interpreted.

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We sought to determine the impact of electrospinning parameters on a trustworthy criterion that could evidently improve the maximum applicability of fibrous scaffolds for tissue regeneration. We used an image analysis technique to elucidate the web permeability index (WPI) by modeling the formation of electrospun scaffolds. Poly(3-hydroxybutyrate) (P3HB) scaffolds were fabricated according to predetermined conditions of levels in a Taguchi orthogonal design. The material parameters were the polymer concentration, conductivity, and volatility of the solution. The processing parameters were the applied voltage and nozzle-to-collector distance. With a law to monitor the WPI values when the polymer concentration or the applied voltage was increased, the pore interconnectivity was decreased. The quality of the jet instability altered the pore numbers, areas, and other structural characteristics, all of which determined the scaffold porosity and aperture interconnectivity. An initial drastic increase was observed in the WPI values because of the chain entanglement phenomenon above a 6 wt % P3HB content. Although the solution mixture significantly (p < 0.05) changed the scaffold architectural characteristics as a function of the solution viscosity and surface tension, it had a minor impact on the WPI values. The solution mixture gained the third place of significance, and the distance was approved as the least important factor.

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Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

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The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

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The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

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Purpose. The purpose of this article was to present methods capable of estimating the size and shape of the human eye lens without resorting to phakometry or magnetic resonance imaging (MRI). Methods. Previously published biometry and phakometry data of 66 emmetropic eyes of 66 subjects (age range [18, 63] years, spherical equivalent range [−0.75, +0.75] D) were used to define multiple linear regressions for the radii of curvature and thickness of the lens, from which the lens refractive index could be derived. MRI biometry was also available for a subset of 30 subjects, from which regressions could be determined for the vertex radii of curvature, conic constants, equatorial diameter, volume, and surface area. All regressions were compared with the phakometry and MRI data; the radii of curvature regressions were also compared with a method proposed by Bennett and Royston et al. Results. The regressions were in good agreement with the original measurements. This was especially the case for the regressions of lens thickness, volume, and surface area, which each had an R2 > 0.6. The regression for the posterior radius of curvature had an R2 < 0.2, making this regression unreliable. For all other regressions we found 0.25 < R2 < 0.6. The Bennett-Royston method also produced a good estimation of the radii of curvature, provided its parameters were adjusted appropriately. Conclusions. The regressions presented in this article offer a valuable alternative in case no measured lens biometry values are available; however care must be taken for possible outliers.

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One of the primary desired capabilities of any future air traffic separation management system is the ability to provide early conflict detection and resolution effectively and efficiently. In this paper, we consider the risk of conflict as a primary measurement to be used for early conflict detection. This paper focuses on developing a novel approach to assess the impact of different measurement uncertainty models on the estimated risk of conflict. The measurement uncertainty model can be used to represent different sensor accuracy and sensor choices. Our study demonstrates the value of modelling measurement uncertainty in the conflict risk estimation problem and presents techniques providing a means of assessing sensor requirements to achieve desired conflict detection performance.