The safety effects of cooperative intelligent transport systems (C-ITS) are mostly unknown and associated with uncertainties, because these systems represent emerging technology. This study proposes a bowtie analysis as a conceptual framework for evaluating the safety effect of cooperative intelligent transport systems. These seek to prevent road traffic accidents or mitigate their consequences. Under the assumption of the potential occurrence of a particular single vehicle accident, three case studies demonstrate the application of the bowtie analysis approach in road traffic safety. The approach utilizes exemplary expert estimates and knowledge from literature on the probability of the occurrence of accident risk factors and of the success of safety measures. Fuzzy set theory is applied to handle uncertainty in expert knowledge. Based on this approach, a useful tool is developed to estimate the effects of safety-related cooperative intelligent transport systems in terms of the expected change in accident occurrence and consequence probability.
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http://dx.doi.org/10.1016/j.aap.2016.11.014 | DOI Listing |
Sensors (Basel)
December 2024
Instituto de Telecomunicações, University of Aveiro, 3810-193 Aveiro, Portugal.
As the demand for high-speed, low-latency communication continues to grow, free-space optical (FSO) communication has gained prominence as a promising solution for supporting the next generation of wireless networks, especially in the context of the 5G and beyond era. It offers high-speed, low-latency data transmission over long distances without the need for a physical infrastructure. However, the deployment of FSO systems faces significant challenges, such as atmospheric turbulence, weather-induced signal degradation, and alignment issues, all of which can impair performance.
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December 2024
School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou 510006, China.
This paper proposes the fixed-time prescribed performance optimal consensus control method for stochastic nonlinear multi-agent systems with sensor faults. The consensus error converges to the prescribed performance bounds in fixed-time by an improved performance function and coordinate transformation. Due to the unknown faults in sensors, the system states cannot be gained correctly; therefore, an adaptive compensation strategy is constructed based on the approximation capabilities of neural networks to solve the negative impact of sensor failures.
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December 2024
CARISSMA Institute of Electric, Connected and Secure Mobility, Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany.
Cooperative intelligent transportation systems continuously send self-referenced data about their current status in the Cooperative Awareness Message (CAM). Each CAM contains the current position of the vehicle based on GPS accuracy, which can have inaccuracies in the meter range. However, a high accuracy of the position data is crucial for many applications, such as electronic toll collection or the reconstruction of traffic accidents.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
Serpentine microstructures offer excellent physical properties, making them highly promising in applications in stretchable electronics and tissue engineering. However, existing fabrication methods, such as electrospinning and lithography, face significant challenges in producing microscale serpentine structures that are cost-effective, efficient, and controllable. These methods often struggle with achieving precise control over fiber morphology and scalability.
View Article and Find Full Text PDFMolecules
December 2024
State Key Laboratory of Continental Shale Oil, Northeast Petroleum University, Daqing 163318, China.
Due to the complex physical properties of low-permeability glutenite reservoirs, the oil recovery rate with conventional development is low. Surfactants are effective additives for enhanced oil recovery (EOR) due to their good ability of wettability alteration and interfacial tension (IFT) reduction, but the reason why imbibition efficiencies vary with different types of surfactants and the mechanism of enhanced imbibition in the glutenite reservoirs is not clear. In this study, the imbibition efficiency and recovery of surfactants including the nonionic, anionic, and cationic surfactants as well as nanofluids were evaluated and compared with produced water (PW) using low-permeability glutenite core samples from the Lower Urho Formation in the Mahu oil field.
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