Rerouting drivers from selfish route choices to system-optimal traffic patterns has the potential to improve the performance of existing infrastructure. Previous research has looked into assessing the potential of rer...
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Rerouting drivers from selfish route choices to system-optimal traffic patterns has the potential to improve the performance of existing infrastructure. Previous research has looked into assessing the potential of rerouting through the empirical price of anarchy, a measure of network efficiency. However, studies using real-world measurements have been limited by methodological accuracy and network size. Also, they have lacked understanding of the spatial distribution of benefits from rerouting and the relationship with marginal external cost road charges that can be used for implementation. In this article, we create an accurate data-driven traffic assignment model of England's Strategic Road Network. We use it to calculate the national price of anarchy, which is found to be almost 1 implying gains from rerouting at the national scale are minimal and smaller than in other studies. The results show the distribution of rerouting benefits varies strongly with different network zones and demand profiles. This did not match the distribution of marginal external cost charges. Some zones have noticeable benefits from rerouting although the overall network benefit is small, however, these zones do not coincide with where the largest road charges have to be applied for system-optimal rerouting. These results have implications for rerouting implementation.
Accurate heading control is the premise for underwater vehicles to complete underwater operations. In order to improve the performance of heading control, this paper proposes a heading control strategy based on PID-fu...
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In the Industrial Internet of Things (IIoT), outdoor electronic devices serve crucial roles across sectors, providing vital data for decision-making. However, their exposure to open outdoor environments makes them vul...
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Active sensing plays an essential role in searching and tracking a target without initial target state information. This paper studies the active sensing approach for sensor management problems using multiple unmanned...
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ISBN:
(数字)9781737749769
ISBN:
(纸本)9798350371420
Active sensing plays an essential role in searching and tracking a target without initial target state information. This paper studies the active sensing approach for sensor management problems using multiple unmanned aerial vehicles based on the received signal strength measurements of the target. A Bayesian optimisation-based approach is proposed which adopts the Gaussian process method to model the received signal strength in an area over time and then the expected improvement acquisition function is leveraged to decide where to take new measurements considering the uncertainty of the Gaussian process. A unique contribution of this paper consists of the designed spatial-temporal composite kernel function that accounts for the time-varying nature of the signal strength. Numerical results obtained from different measurement noise levels and varying initial Bayesian optimisation settings demonstrate that the proposed approach can efficiently schedule multiple unmanned aerial vehicles to locate the target within a minimum number of initial data. Particularly, it achieves at most $57 \%$ lower tracking error and $46 \%$ lower lost-track probability as compared to the benchmark approach.
This paper explores the application of centralised and distributed Gaussian process algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is...
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ISBN:
(数字)9781737749769
ISBN:
(纸本)9798350371420
This paper explores the application of centralised and distributed Gaussian process algorithms to real-time target tracking and compares their performance. By embedding the algorithms into the Stone Soup, the focus is on the innovative implementation of Gaussian process methods with learning hyperparameters and implementation with a factorised variance of the Gaussian kernel. The performance of the methods with different kernels was evaluated, not only with the Gaussian kernel. Extensive experiments with various kernel configurations demonstrate their importance in enhancing prediction accuracy and efficiency, especially in real-time tracking. The case studies with manoeuvring targets show significant advancements in tracking capabilities, particularly in wireless sensor networks, using optimised Gaussian process methods. This work advances Stone Soup’s capabilities and lays the groundwork for future investigations into adaptive Gaussian Process applications in tracking and sensor data analysis.
In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth’s system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The p...
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In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth’s system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10 µm, i.e., PM10 are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM10 samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24 h average PM10 mass concentration along with standard deviation was investigated to be 586.83 ± 217.70 µg/m3, which was around 13 times greater than the permissible limit of the world health organization (45 µg/m3) and 4 times the Pakistan national environmental quality standards for ambient PM10 (150 µg/m3). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90 µg/m3, respectively. Water-soluble ions K+ and OC show a substantial association (R = 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of P
Free-form structural forms are widely used to design spatial structures for their irregular spatial morphology. Current free-form form-finding methods cannot adequately meet the material properties, structural require...
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Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing h...
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This paper presents a novel approach for head tracking in augmented reality (AR) flight simulators using an adaptive fusion of Kalman and particle filters. This fusion dynamically balances the strengths of both algori...
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This paper investigates the state-constrained controller design of a hypersonic flight vehicle(HFV) based on an asymmetric barrier Lyapunov function(ABLF). The robust adaptive back-stepping controller with integral te...
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This paper investigates the state-constrained controller design of a hypersonic flight vehicle(HFV) based on an asymmetric barrier Lyapunov function(ABLF). The robust adaptive back-stepping controller with integral terms is applied for the HFV longitudinal dynamics. Considering the asymmetric angle of attack(AOA) constraint caused by the unique structure and scramjet, the controller is modified by constructing an ABLF, where the asymmetric constraint on AOA tracking error is introduced. Combined with the constraint on virtual control, the AOA is restricted to a predefined asymmetric interval. The system stability and the AOA constraint are guaranteed via Lyapunov analysis. Simulation results verify that the AOA can be kept in the given asymmetric interval while the altitude reference signal is tracked.
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