We develop a model for two-layer traffic flow in which a batch of n_{o} packets are dispatched from the source at regular intervals. This scenario is applicable in various communication and transportation systems, such as TCP congestion control mechanisms and congestion management through traffic lights. We demonstrate that implementing stochastic switching between the shortest-path and greedy approaches in the routing strategy of packet transmission results in a significant reduction in the total transmission weight when n_{o} exceeds a certain threshold. This phenomenon mirrors Parrondo's paradox, in which two games or strategies, individually yielding losses, produce a winning outcome or optimal results when combined. In addition, we observe that the influence of layer 1 on overall dynamics surpasses that of layer 2. Furthermore, we find that the impact of the structural characteristics of layers is more significant for switching probability γ<0.5.
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http://dx.doi.org/10.1103/PhysRevE.111.L012201 | DOI Listing |
Sensors (Basel)
February 2025
School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China.
In the domain of autonomous driving systems, vehicle trajectory prediction represents a critical aspect, as it significantly contributes to the safe maneuvering of vehicles within intricate traffic environments. Nevertheless, a preponderance of extant research efforts have been chiefly centered on the spatio-temporal relationships intrinsic to the vehicle itself, thereby exhibiting deficiencies in the dynamic perception of and interaction capabilities with adjacent vehicles. In light of this limitation, we propose a vehicle trajectory prediction algorithm predicated on a hybrid prediction model.
View Article and Find Full Text PDFPhys Rev E
January 2025
Nanyang Technological University, Division of Mathematical Sciences, School of Physical and Mathematical Sciences, 21 Nanyang Link, Singapore S637371.
We develop a model for two-layer traffic flow in which a batch of n_{o} packets are dispatched from the source at regular intervals. This scenario is applicable in various communication and transportation systems, such as TCP congestion control mechanisms and congestion management through traffic lights. We demonstrate that implementing stochastic switching between the shortest-path and greedy approaches in the routing strategy of packet transmission results in a significant reduction in the total transmission weight when n_{o} exceeds a certain threshold.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Western Science City Intelligent and Connected Vehicle Innovation Center (Chongqing) Co., Ltd., Chongqing 400015, China.
With the rise in the intelligence levels of automated vehicles, increasing numbers of modules of automated driving systems are being combined to achieve better performance and adaptability by reducing information loss. In this study, an integrated decision and motion planning system is designed for multi-object highways. A two-layer structure is presented to decouple the influence of the traffic environment and the dynamic control of ego vehicles using the cognitive safety area, the size of which is determined by naturalistic driving behavior.
View Article and Find Full Text PDFSci Rep
December 2024
Xinjiang Petroleum Engineering Co., Ltd, Karamay, 834000, China.
With the exponential growth of mobile devices and data traffic, mobile edge computing has become a promising technology, and the placement of edge servers plays a key role in providing efficient and low-latency services. In this paper, we investigate the issue of edge server placement and user allocation to reduce transmission delay between base stations and servers, and balance the workload of individual servers. To this end, we propose a graph clustering-based edge server placement model by fully considering the constraints such as the distance, coverage area and number of channels of base stations.
View Article and Find Full Text PDFAccid Anal Prev
December 2024
School of Transportation Engineering, Chang'an University, Xi'an 710018, Shanxi, China.
Background: Drowsiness detection is a long-standing concern in preventing drowsiness-related accidents. Inter-individual differences seriously affect drowsiness detection accuracy. However, most existing studies neglected inter-individual differences in measurements' calculation parameters and drowsiness thresholds.
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