scholarly journals A Cooperative Positioning Method of Connected and Automated Vehicles with Direction-of-Arrival and Relative Distance Fusion

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Faan Wang ◽  
Liwei Xu ◽  
Xianjian Jin ◽  
Guodong Yin ◽  
Ying Liu
Keyword(s):  
Rapid Development ◽  
Direction Of Arrival ◽  
Urban Traffic ◽  
Least Square ◽  
Relative Distance ◽  
Measurement Information ◽  
Cooperative Localization ◽  
Automated Vehicles ◽  
Localization Accuracy ◽  
Position Errors

The rapid development of science and technology has created favorable conditions for Connected and Automated Vehicles (CAVs). Accurate localization is one of the fundamental functions of CAV to realize some advanced operations such as vehicle platooning. However, complicated urban traffic environments, such as the flyover, significantly influence vehicular positioning accuracy. The inability of CAV to accurately perceive self-localization information has become an urgent issue to be addressed. This paper proposed a novel cooperative localization method by introducing the relative Direction-of-Arrival (DOA) and Relative Distance (RD) into CAV to improve the localization accuracy of CAV in the multivehicle environment. First, the three-dimensional positioning error model of the host vehicle concerning adjacent vehicles in azimuth angle and pitch angle and intervehicle distances under the vehicle-to-vehicle communication was established. Second, two least-squares estimation algorithms, linear and nonlinear, are established to decrease the position errors by combining relative DOA and RD measurement information. To verify the proposed algorithm's effect, the PreScan-Simulink joint simulation is carried out. The results show that the host vehicle's localization accuracy by the proposed method can be improved by 25% compared with direct linearization. Besides, by combining relative DOA and relative RD measurement, the locating capability of the least-square-based nonlinear optimization method can be enhanced by 22%.

scholarly journals A Robust, Non-Cooperative Localization Algorithm in the Presence of Outlier Measurements in Ocean Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2708 ◽  
Author(s):  
Xiaojun Mei ◽  
Huafeng Wu ◽  
Jiangfeng Xian ◽  
Bowen Chen ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Large Scale ◽  
Trust Region ◽  
Accurate Solution ◽  
Least Square ◽  
Cooperative Localization ◽  
Localization Problem ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Ocean Sensor Networks

As an important means of multidimensional observation on the sea, ocean sensor networks (OSNs) could meet the needs of comprehensive information observations in large-scale and multifactor marine environments. In what concerns OSNs, accurate location information is the basis of the data sets. However, because of the multipath effect—signal shadowing by waves and unintentional or malicious attacks—outlier measurements occur frequently and inevitably, which directly degrades the localization accuracy. Therefore, increasing localization accuracy in the presence of outlier measurements is a critical issue that needs to be urgently tackled in OSNs. In this case, this paper proposed a robust, non-cooperative localization algorithm (RNLA) using received signal strength indication (RSSI) in the presence of outlier measurements in OSNs. We firstly formulated the localization problem using a log-normal shadowing model integrated with a first order Taylor series. Nevertheless, the problem was infeasible to solve, especially in the presence of outlier measurements. Hence, we then converted the localization problem into the optimization problem using squared range and weighted least square (WLS), albeit in a nonconvex form. For the sake of an accurate solution, the problem was then transformed into a generalized trust region subproblem (GTRS) combined with robust functions. Although GTRS was still a nonconvex framework, the solution could be acquired by a bisection approach. To ensure global convergence, a block prox-linear (BPL) method was incorporated with the bisection approach. In addition, we conducted the Cramer–Rao low bound (CRLB) to evaluate RNLA. Simulations were carried out over variable parameters. Numerical results showed that RNLA outperformed the other algorithms under outlier measurements, notwithstanding that the time for RNLA computation was a little bit more than others in some conditions.

scholarly journals Assessing Determinants of Continuance Intention towards Personal Cloud Services: Extending UTAUT2 with Technology Readiness

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 467
Author(s):  
Shih-Chih Chen ◽  
Shing-Han Li ◽  
Shih-Chi Liu ◽  
David C. Yen ◽  
Athapol Ruangkanjanases
Keyword(s):  
Rapid Development ◽  
Cloud Service ◽  
Individual Characteristics ◽  
Partial Least Square ◽  
Cloud Services ◽  
Least Square ◽  
Information And Communications Technology ◽  
Technology Readiness ◽  
Continuance Intention ◽  
Systems Research

In addition to the rapid development of global information and communications technology (ICT) and the Internet, recent rapid growth in cloud computing technology represents another important trend. Individual continuance intention towards information technology is a critical area in which information systems research can be performed. This study aims to develop an integrated model designed to explain and predict an individual’s continuance intention towards personal cloud services based on the concepts of technology readiness (TR) and the unified theory of acceptance and use of technology 2 (UTAUT2), moderated by gender, age, and experience of personal cloud services. The key results of the partial least square test largely support the proposed model’s validity and the significant impact of effort expectancy, social influence, hedonic motivation, price value, habit, and technology readiness on continuance intention towards personal cloud services. In addition to providing symmetric theoretical support with the proposed model and transforming the individual characteristics of TR into UTAUT2, this study could be used to enhance and analyze users’ adoption of personal cloud services and also increase the symmetry of the model’s explanation and prediction. The findings from this research contribute to providing practical implications and academic resources as well as improving our understanding of personal cloud service applications.

scholarly journals Calibration Method of Array Errors for Wideband MIMO Imaging Radar Based on Multiple Prominent Targets

2021 ◽  
Vol 13 (15) ◽  
pp. 2997
Author(s):  
Zheng Zhao ◽  
Weiming Tian ◽  
Yunkai Deng ◽  
Cheng Hu ◽  
Tao Zeng
Keyword(s):  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Target Position ◽  
Position Estimation ◽  
Least Square ◽  
Antenna Structure ◽  
Imaging Radar ◽  
Position Errors ◽  
Calibration Methods ◽  
Array Errors

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets.

scholarly journals Impact of External Human–Machine Interface Communication Strategies of Automated Vehicles on Pedestrians’ Crossing Decisions and Behaviors in an Urban Environment

2021 ◽  
Vol 13 (15) ◽  
pp. 8396
Author(s):  
Marc Wilbrink ◽  
Merle Lau ◽  
Johannes Illgner ◽  
Anna Schieben ◽  
Michael Oehl
Keyword(s):  
Urban Traffic ◽  
Automated Vehicles ◽  
Negative Effects ◽  
Communication Tools ◽  
Automated Vehicle ◽  
Additional Information ◽  
Road Users ◽  
Vulnerable Road Users ◽  
And Behaviors ◽  
Vehicle Automation

The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.

Video Nodes Based Collaborative Object Localization Framework in Wireless Multimedia Sensor Networks

2011 ◽  
Vol 317-319 ◽  
pp. 1078-1083 ◽  
Author(s):  
Qing Tao Lin ◽  
Xiang Bing Zeng ◽  
Xiao Feng Jiang ◽  
Xin Yu Jin
Keyword(s):  
Cluster Head ◽  
Computation Time ◽  
Least Square Method ◽  
Least Square ◽  
Object Localization ◽  
Wireless Multimedia ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Multimedia Sensor Networks ◽  
Localization Model

This paper establishes a 3-D localization model and based on this model, it proposes a collaborative localization framework. In this framework, node that observes the object sends its attitude information and the relative position of the object's projection in its camera to the cluster head. The cluster head adopts an algorithm proposed in this paper to select some nodes to participate localization. The localization algorithm is based on least square method. Because the localization framework is based on a 3-D model, the size of the object or other prerequisites is not necessary. At the end of this paper, a simulation is taken on the numbers of nodes selected to locate and the localization accuracy. The result implies that selecting 3~4 nodes is proper. The theoretical analysis and the simulation result also imply that a const computation time cost is paid in this framework with a high localization accuracy (in our simulation environment, a 0.01 meter error).

Least Square Cooperative Localization

2015 ◽  
Vol 64 (4) ◽  
pp. 1318-1330 ◽  
Author(s):  
Thang Van Nguyen ◽  
Youngmin Jeong ◽  
Hyundong Shin ◽  
Moe Z. Win
Keyword(s):  
Least Square ◽  
Cooperative Localization

scholarly journals Prevalence of anxiety and depressive symptoms and impact on self-management among adults with chronic conditions in Chicago, Illinois, USA, during the COVID-19 pandemic: a cross-sectional survey

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e052495
Author(s):  
Rebecca M Lovett ◽  
Lauren Opsasnick ◽  
Andrea Russell ◽  
Esther Yoon ◽  
Sophia Weiner-Light ◽  
...  
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Chronic Conditions ◽  
Least Square ◽  
Self Management ◽  
Secondary Outcome ◽  
Measurement Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Patient Reported

ObjectivesTo examine the prevalence of mental health symptoms during the first surge of COVID-19 in the USA, and their associations with COVID-19-related emotional distress, health self-management and healthcare utilisation.DesignCross-sectional analysis of wave 3 (1–22 May 2020) survey data from the ongoing Chicago COVID-19 Comorbidities (C3) study.SettingSeven academic and community health centres in Chicago, Illinois.Participants565 adults aged 23–88 with one or more chronic conditions completing at least one prior C3 study wave.Primary and secondary outcome measuresClinically relevant anxiety and depressive symptoms as measured using Patient-Reported Outcomes Measurement Information System short forms. Self-reported emotional and health-related responses to COVID-19 were measured through a combination of single-item questions and validated measures.ResultsRates of anxiety and depressive symptoms were 14% (81/563) and 15% (84/563), respectively. Anxiety and depressive symptoms were then each separately associated with greater worry about contracting COVID-19 (relative risk (RR) 2.32, 95% CI 1.52 to 3.53; RR 1.67, 95% CI 1.10 to 2.54), greater stress (RR 4.93, 95% CI 3.20 to 7.59; RR 3.01, 95% CI 1.96 to 4.61) and loneliness (RR 3.82, 95% CI 2.21 to 6.60; RR 5.37, 95% CI 3.21 to 8.98), greater avoidance of the doctor (RR 1.62, 95% CI 1.06 to 2.49; RR 1.54, 95% CI 1.00 to 2.36) and difficulty managing health (least square means (LS Means) 6.09, 95% CI 5.25 to 6.92 vs 4.23, 95% CI 3.70 to 4.75; LS Means 5.85, 95% CI 5.04 to 6.65 vs 4.22, 95% CI 3.70 to 4.75) and medications (LS Means 3.71, 95% CI 2.98 to 4.43 vs 2.47, 95% CI 2.02 to 2.92) due to the pandemic.ConclusionsIdentifying and addressing mental health concerns may be an important factor to consider in COVID-19 prevention and management among high-risk medical populations.

Optimization of Urban Traffic Distribution Path Under Quick Response Demand

2018 ◽  
Vol 43 (1) ◽  
pp. 108-112
Author(s):  
F Xiong ◽  
P S Gong ◽  
Z Q Peng ◽  
J F Fan
Keyword(s):  
Motor Vehicle ◽  
Rapid Development ◽  
Three Dimensional ◽  
Fast Response ◽  
Urban Traffic ◽  
Quick Response ◽  
Traffic Planning ◽  
Planning And Design ◽  
Traffic Distribution ◽  
Planning Project

Under the background of the rapid development of e-commerce and information network, the demand for urban distribution is also changing; especially customers' demand for fast delivery of products is increasing. Based on this, the optimization of urban traffic distribution path was studied under the fast response demand. In this paper, the importance and theoretical basis of the design of urban traffic planning under rapid response demand were expounded; then, the urban traffic distribution path planning was designed, and the layout principle of urban traffic roads, the division of road levels and the planning and design of motor vehicle roads were analyzed; through the planning project of the traffic distribution path in a city, analysis of the planning on roadways, three-dimensional traffic paths was achieved.

scholarly journals A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 875 ◽  
Author(s):  
Xiaochao Dang ◽  
Xiong Si ◽  
Zhanjun Hao ◽  
Yaning Huang
Keyword(s):  
Indoor Localization ◽  
Rapid Development ◽  
Location Based Services ◽  
Signal Interference ◽  
Indoor Environments ◽  
Phase Information ◽  
Localization Accuracy ◽  
Localization Method ◽  
Indoor Location ◽  
Conference Room

With the rapid development of wireless network technology, wireless passive indoor localization has become an increasingly important technique that is widely used in indoor location-based services. Channel state information (CSI) can provide more detailed and specific subcarrier information, which has gained the attention of researchers and has become an emphasis in indoor localization technology. However, existing research has generally adopted amplitude information for eigenvalue calculations. There are few research studies that have used phase information from CSI signals for localization purposes. To eliminate the signal interference existing in indoor environments, we present a passive human indoor localization method named FapFi, which fuses CSI amplitude and phase information to fully utilize richer signal characteristics to find location. In the offline stage, we filter out redundant values and outliers in the CSI amplitude information and then process the CSI phase information. A fusion method is utilized to store the processed amplitude and phase information as a fingerprint database. The experimental data from two typical laboratory and conference room environments were gathered and analyzed. The extensive experimental results demonstrate that the proposed algorithm is more efficient than other algorithms in data processing and achieves decimeter-level localization accuracy.

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