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Prediction of Traffic Volume of Motor Vehicles Based on Mobile Phone Signaling Technology
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作者 Jin Shang Hailong Su +2 位作者 Kai Hu Xin Guo Defa Sun 《Computers, Materials & Continua》 SCIE EI 2023年第4期799-814,共16页
Urban traffic volume detection is an essential part of trafficplanning in terms of urban planning in China. To improve the statisticsefficiency of road traffic volume, this thesis proposes a method for predictingmotor... Urban traffic volume detection is an essential part of trafficplanning in terms of urban planning in China. To improve the statisticsefficiency of road traffic volume, this thesis proposes a method for predictingmotor vehicle traffic volume on urban roads in small and medium-sizedcities during the traffic peak hour by using mobile signal technology. Themethod is verified through simulation experiments, and the limitations andthe improvement methods are discussed. This research can be divided intothree parts: Firstly, the traffic patterns of small and medium-sized cities areobtained through a questionnaire survey. A total of 19745 residents weresurveyed in Luohe, a medium-sized city in China and five travel modes oflocal people were obtained. Secondly, after the characteristics of residents’rest and working time are investigated, a method is proposed in this studyfor the distribution of urban residential and working places based on mobilephone signaling technology. Finally, methods for predicting traffic volume ofthese travel modes are proposed after the characteristics of these travel modesand methods for the distribution of urban residential and working placesare analyzed. Based on the actual traffic volume data observed at offlineintersections, the project team takes Luohe city as the research object and itverifies the accuracy of the prediction method by comparing the predictiondata. The prediction simulation results of traffic volume show that the averageerror rate of traffic volume is unstable. The error rate ranges from 10% to 30%.In this thesis, simulation experiments and field investigations are adopted toanalyze why these errors occur. 展开更多
关键词 Traffic planning prediction of traffic volume mobile phone signaling technology small and medium-sized cities traffic peak hour
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Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System 被引量:2
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作者 Predrag Rapajic 《International Journal of Automation and computing》 EI 2008年第4期325-333,共9页
It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present... It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture. 展开更多
关键词 Medical and patient monitoring sensing technologies and signal processing vital sign ULTRA-WIDEBAND distributed cog-nitive radar respiration rate estimation.
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