Traffic congestion and crash rates can be reduced by introducing variable speed limits (VSLs) and automatic incident detection (AID) systems. Previous findings based on loop detector measurements have revealed that drivers reduce their speeds while approaching traffic congestion when the AID system is active. Notwithstanding these behavioural effects, most microscopic traffic flow models assessing the impact of VSLs do not describe driver response accurately.This study analyses the main factors that influence driver deceleration behaviour while approaching traffic congestion with and without VSLs. The Dutch VSL database was linked to the driver behaviour data collected in the UDRIVE naturalistic driving study. Driver engagement in secondary tasks and glance behaviour were extracted from the video data. Linear mixed-effects models predicting the characteristics of deceleration events were estimated.The results show that the maximum deceleration is high when approaching a slower leader, when driving at high speeds and short distance headways, and close to the beginning of traffic congestion. The minimum time headway is short when driving at high speeds and changing lanes. Certain drivers showed higher decelerations and shorter time headways than others. Controlled for these main factors, smaller maximum decelerations were found when the VSLs were present and visible, and when the gantries were within close proximity. These factors could be incorporated into microscopic traffic simulations to evaluate the impact of AID systems on traffic congestion more realistically. Further research is needed to clarify the link between engagement in secondary tasks, glance behaviour and deceleration behaviour. 相似文献
Intrusion Detection Systems (IDSs) is a system that monitors network traffic for suspicious activity and issues alert when such activity is revealed. Moreover, the existing IDSs-based methods are based on outdated attacks that unable to identify modern attacks or malicious trends. For this reason, in this study we developed a new multi-swarm adaptive grasshopper optimization algorithm to utilize adaptation mechanism in a group of swarms based on fuzzy logic to protect against sophisticated attacks. The proposed (MSAGOA) technique has the capability of global optimization and rapid convergence that are used to attain optimal feature subsets to identify attack types on IDS datasets. In the MSAGOA technique, learning engine as Extreme learning Machine, Naive Bayes, Random Forest and Decision Tree is applied as a fitness function to select the highly discriminating features and to maximize classification performance. Afterward, select the best classifier which works as a fitness function in our approach to measure the performance in terms of accuracy, detection rate, and false alarm rate. The simulations are performed on three IDS datasets such as NSL-KDD, AWID-ATK-R, and NGIDS-DS. The experimental results demonstrated that MSAGOA method has performed better and obtained high detection rate of 99.86%, accuracy of 99.89% in NSL-KDD and high detection rate of 98.73%, accuracy of 99.67% in AWID-ATK-R and detection rate of 89.50%, accuracy of 90.23% in NGIDS-DS. In addition, the performance is compared with several other existing techniques to show the efficacy of the proposed approach. 相似文献
Errors in choice tasks are not only detected fast and reliably, participants often report that they knew that an error occurred already before a response was produced. These early error sensations stand in contrast with evidence suggesting that the earliest neural correlates of error awareness emerge around 300 ms after erroneous responses. The present study aimed to investigate whether anecdotal evidence for early error sensations can be corroborated in a controlled study in which participants provide metacognitive judgments on the subjective timing of error awareness. In Experiment 1, participants had to report whether they became aware of their errors before or after the response. In Experiment 2, we measured confidence in these metacognitive judgments. Our data show that participants report early error sensations with high confidence in the majority of error trials across paradigms and experiments. These results provide first evidence for early error sensations, informing theories of error awareness. 相似文献
Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose a new bio-inspired learning model for a single-class classifier to detect abnormality in video object trajectories. The method uses a simple but dynamic extreme learning machine (ELM) and hierarchical temporal memory (HTM) together referred to as ELM-HTM in an unsupervised way to learn and classify time series patterns. The method has been tested on trajectory sequences in traffic surveillance to find abnormal behaviors such as high-speed, unusual stops, driving in wrong directions, loitering, etc. Experiments have also been performed with 3D air signatures captured using sensors and used for biometric authentication(forged/genuine). The results indicate a significant gain over training time and classification accuracy. The proposed method outperforms in predicting long-time patterns by observing small steps with an average accuracy gain of 15% as compared to the state-of-the-art HTM. The method has applications in detecting abnormal activities in videos by learning the movement patterns as well as in biometric authentication. 相似文献
Background/Objective: This study aims to characterize the differences on the short-term temporal network dynamics of the undirected and weighted whole-brain functional connectivity between healthy aging individuals and people with mild cognitive impairment (MCI). The Network Change Point Detection algorithm was applied to identify the significant change points in the resting-state fMRI register, and we analyzed the fluctuations in the topological properties of the sub-networks between significant change points. Method: Ten MCI patients matched by gender and age in 1:1 ratio to healthy controls screened during patient recruitment. A neuropsychological evaluation was done to both groups as well as functional magnetic images were obtained with a Philips 3.0T. All the images were preprocessed and statistically analyzed through dynamic point estimation tools. Results: No statistically significant differences were found between groups in the number of significant change points in the functional connectivity networks. However, an interaction effect of age and state was detected on the intra-participant variability of the network strength. Conclusions: The progression of states was associated to higher variability in the patient's group. Additionally, higher performance in the prospective and retrospective memory scale was associated with higher median network strength. 相似文献
This study tested the hypothesis that breathlessness in asthma relates linearly to airway obstruction when situational, attentional and emotional influences are held constant via random presentation of different intensities of externally applied airflow obstruction. Adolescents with stable asthma and normal controls (n=25+25) with lung functions of approximately 3.5 l forced expiratory volume in 1 s (FEV1) breathed through a device which obstructed airflow with five stimulus intensities, analogous to a mean reduction in FEV1 of 8–66%. A session consisted of 10 blocks, each with presentation of five stimulus intensities plus the baseline resistance of the apparatus. Breathlessness was continuously reported by moving a lever along a 10-point scale. The mean breathlessness was computed per stimulus intensity. Lung function and anxiety were measured before and after the test.
Participants with asthma, not controls, manifested a paradoxical response: they reported significantly more breathlessness, but undifferentially. One patient against 12 controls reported consistently more breathlessness from baseline to severe obstruction. The hypothesis was only supported for controls. Breathlessness did not correlate with severity of asthma, lung function, duration of asthma, number of exacerbations over the last six months, age, sex or anxiety.
It was concluded that the meaning of airflow obstruction in patients with asthma has changed and underlies their paradoxical responses, even when situational, attentional and emotional factors are controlled. 相似文献