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Influence of tracking duration on the privacy of individual mobility graphs 跟踪持续时间对个体迁移图私密性的影响
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-07-27 DOI: 10.1080/17489725.2023.2239190
Nina Wiedemann, Henry Martin, Esra Suel, Ye Hong, Yanan Xin
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引用次数: 2
Analytics of historical human migration patterns: use cases of Amsterdam and Copenhagen 历史上人类迁徙模式的分析:阿姆斯特丹和哥本哈根的使用案例
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-07-25 DOI: 10.1080/17489725.2023.2238658
I. Kveladze, Marina Georgati, C. Kessler, H. Hansen
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引用次数: 1
Augmented reality landmarks on windshield and their effects on the acquisition of spatial knowledge in autonomous vehicles 自动驾驶汽车挡风玻璃上的增强现实地标及其对空间知识获取的影响
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-07-24 DOI: 10.1080/17489725.2023.2238661
Rui Li
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引用次数: 0
Exploring the potential of social media to study environmental topics and natural disasters 探索社交媒体研究环境主题和自然灾害的潜力
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-07-20 DOI: 10.1080/17489725.2023.2238663
Kenzo Milleville, S. Van Ackere, Jana Verdoodt, S. Verstockt, P. de Maeyer, N. van de Weghe
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引用次数: 0
Analysis of route choice based on path characteristics using Geolife GPS trajectories 基于Geolife GPS轨迹的路径选择分析
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-06-28 DOI: 10.1080/17489725.2023.2229285
Fateme Teimouri, Kai-Florian Richter, H. Hochmair
ABSTRACT Navigation services are essential for daily navigation, providing turn-by-turn instructions to help wayfinders reach their destinations. These services often differ from the heuristics wayfinders use, resulting in a poor user experience. Researchers have attempted to address this issue by developing algorithms that find less complex routes, by integrating prominent locations along the route to make wayfinding easier and to improve a wayfinder’s knowledge about the environment. These approaches, however, have taken a bottom-up approach, involving a limited number of participants navigating in real or virtual environments which may limit generalisability of results. In this study, we took a top-down approach by analysing a large dataset of GPS-based trips in the real world. Using the Geolife dataset, we analysed individual heuristics for route selection in terms of complexity and prominent locations, and found that wayfinders prefer less complex routes, such as routes that require fewer turns or involve simpler intersections. Additionally, we found that wayfinders choose routes with fewer prominent locations, such as routes that bypass well-known landmarks or busy commercial areas. These findings suggest that simplicity and ease of use are prioritized when selecting a route, while overly complex routes or areas with many points of interest are avoided.
导航服务在日常导航中是必不可少的,它提供逐向的指示,帮助寻路者到达目的地。这些服务通常与寻路器使用的启发式方法不同,从而导致糟糕的用户体验。研究人员试图通过开发算法来解决这个问题,这些算法可以找到不那么复杂的路线,通过整合路线上的突出位置来使寻路更容易,并提高寻路者对环境的了解。然而,这些方法采用了自下而上的方法,涉及在真实或虚拟环境中导航的有限数量的参与者,这可能限制了结果的普遍性。在这项研究中,我们通过分析现实世界中基于gps的旅行的大型数据集,采用了自上而下的方法。使用Geolife数据集,我们根据复杂性和突出位置分析了路线选择的单个启发式方法,发现寻路器更喜欢不太复杂的路线,例如需要较少转弯或涉及更简单路口的路线。此外,我们发现寻路器会选择位置不太突出的路线,例如绕过著名地标或繁忙商业区的路线。这些发现表明,在选择路线时,要优先考虑简单性和易用性,而避免过于复杂的路线或有许多兴趣点的地区。
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引用次数: 1
Road extraction from low-cost GNSS-device dense trajectories 从低成本GNSS设备密集轨迹中提取道路
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-05-27 DOI: 10.1080/17489725.2023.2216670
Bruno de Moura Morceli, A. Poz
ABSTRACT This paper proposes a method for road centerline extraction from dense Global Navigation Satellite System (GNSS) trajectories, collected by using low-cost GNSS-devices, i.e. smartphones. The proposed method basically consists in generating a frequency image by tracking the GNSS trajectories and then by applying the Steger line detector to the generated image to extract the road centerlines. The main motivation of using the Steger algorithm is its capability to detect lines with sub-pixel accuracy. To evaluate the obtained results, reference road centerlines are manually extracted from a georeferenced orthomosaic. The experiments performed demonstrate the high potential of applying the Steger line detector to frequency images, generated by using dense GPS (Global Positioning System) trajectories. The completeness and correctness values for the accomplished experiments were 98% and 99%, respectively. Additionally, the RMSE (Root Mean Square Error) ranged from 0.63 m to 2.39 m, or approximately 1/16 to 1/4 of the expected accuracy (about 10 m) of a point determined by the Single-Point Positioning (SPP) method, which is the GNSS positioning method usually employed by smartphones. KEY POLICY HIGHLIGHTS In this paper we propose to extract roads by using dense GNSS trajectories based on frequency images. GNSS trajectories were collected from low-cost devices (smartphones). Unlike optical images, trajectory frequency images show only roads, thereby preventing problems such as extracting non-road objects. The experiments showed the high potential of using the Steger line detector for road extraction. Profiles drawn cross-sectionally to the roads actually exhibit behaviour similar to the normal distribution. The results obtained were between 16 times and four times better than the expected accuracy of the GNSS positioning method via the SPP positioning method.
摘要本文提出了一种从密集的全球导航卫星系统(GNSS)轨迹中提取道路中心线的方法,该轨迹是使用低成本的GNSS设备(即智能手机)收集的。所提出的方法基本上包括通过跟踪GNSS轨迹来生成频率图像,然后通过将Steger线检测器应用于生成的图像来提取道路中心线。使用Steger算法的主要动机是它能够以亚像素精度检测线条。为了评估所获得的结果,从地理参考正交镶嵌图中手动提取参考道路中心线。所进行的实验证明了将Steger线检测器应用于通过使用密集GPS(全球定位系统)轨迹生成的频率图像的高潜力。完成的实验的完整性和正确性分别为98%和99%。此外,RMSE(均方根误差)范围为0.63 m至2.39 m、 或约为预期精度的1/16至1/4(约10 m) 由智能手机通常采用的GNSS定位方法单点定位(SPP)方法确定的点的位置。关键政策亮点在本文中,我们建议通过使用基于频率图像的密集GNSS轨迹来提取道路。GNSS轨迹是从低成本设备(智能手机)中收集的。与光学图像不同,轨迹频率图像仅显示道路,从而防止了诸如提取非道路对象之类的问题。实验表明,使用Steger线检测器进行道路提取具有很高的潜力。沿道路横截面绘制的剖面实际上表现出与正态分布相似的行为。所获得的结果比通过SPP定位方法的GNSS定位方法的预期精度高出16倍至4倍。
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引用次数: 0
Infrastructure-free indoor navigation based on smartphone sensors in smart buildings 智能建筑中基于智能手机传感器的无基础设施室内导航
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2023-01-22 DOI: 10.1080/17489725.2023.2168078
A. Chehreghan, E. Saadatzadeh, R. Abbaspour
ABSTRACT One of the main elements of location-based services (LBS) is the awareness and knowledge of the user’s location information inside the smart buildings. In this study, a smartphone sensor-based indoor positioning system (IPS) is proposed to track a person’s location in Texting and Pocket carrying modes in a smart building. The gravity, gyroscope, and magnetometer sensors data were combined using a gradient descent algorithm (GDA) to estimate the heading angle. This system was implemented in three straight, complex, and rectangular paths. The mean (M) and standard deviation (SD) of the absolute heading error of each step were obtained as (1.68°, 1.97°) in the Texting mode and (4.39°, 5.22°) in the Pocket mode, respectively. Acceleration and angle-based models were employed to estimate the step length in the Texting and Pocket modes, respectively. The mean relative error (MRE) of the distance in the Texting and Pocket modes were obtained as %4.8 and %4.37, respectively. Experimental results indicated the MRE of the final position along the three paths in the two carrying modes of Texting and Pocket by magnetic and proposed methods reduced from %3.75 to %2.66 and %7.02 to %4.24, respectively.
摘要基于位置的服务(LBS)的主要要素之一是对智能建筑内用户位置信息的感知和了解。在这项研究中,提出了一种基于智能手机传感器的室内定位系统(IPS),用于在智能建筑中以短信和口袋携带模式跟踪人的位置。重力、陀螺仪和磁力计传感器的数据使用梯度下降算法(GDA)进行组合,以估计航向角。该系统在三条直线、复杂和矩形路径中实现。在Texting模式下,每个步骤的绝对航向误差的平均值(M)和标准差(SD)分别为(1.68°,1.97°)和(4.39°,5.22°)。分别采用基于加速度和角度的模型来估计Texting和Pocket模式下的步长。在Texting和Pocket模式下,距离的平均相对误差(MRE)分别为%4.8和%4.37。实验结果表明,在Texting和Pocket两种携带模式下,沿三条路径的最终位置的MRE分别从%3.75降低到%2.66和%7.02降低到%4.24。
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引用次数: 0
Elevation accuracy improvement in mobile devices by implementing artificial neural networks 利用人工神经网络提高移动设备的高程精度
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2022-12-22 DOI: 10.1080/17489725.2022.2157898
Elias Issawy, B. Levy, S. Dalyot
ABSTRACT An important feature of mobile devices relates to positioning, mainly relying on the global navigation satellite system sensor. In optimal conditions, this sensor provides horizontal positioning sufficient for most location-based services. The elevation, on the other hand, still lacks sufficient accuracy and reliability – mostly due to mobile device inadequacies that stem from technological limitations and environmental and physical conditions, which impact the observations quality. We suggest augmenting the elevation measurements of this sensor with measurements from supplementary embedded mobile device sensors, such as barometers and accelerometers, and with data from external mapping and environmental databases, namely topography and weather. We developed an artificial neural network deep-learning model that identifies parameter values for producing the highest predictive accuracy of the elevation value while relying on a comprehensive set of measurements. Our findings indicate very promising results, whereby we enhanced the elevation accuracy of testing data by 428%, while significantly reducing the elevation variance. These results show that using supplementary measurements and data improves elevation values while significantly reducing errors commonly associated with mobile device global navigation satellite system sensors. The proposed method has the capacity to improve outdoor kinematic positioning for location-based services, with a focus on urban and concealed areas.
移动设备的一个重要特征与定位有关,主要依靠卫星全球导航系统的传感器。在最佳条件下,该传感器提供水平定位,足以满足大多数基于位置的服务。另一方面,高程仍然缺乏足够的准确性和可靠性,这主要是由于技术限制以及环境和物理条件导致的移动设备不足,从而影响了观测质量。我们建议通过附加的嵌入式移动设备传感器(如气压计和加速度计)以及外部地图和环境数据库(即地形和天气)的数据来增强该传感器的高程测量。我们开发了一个人工神经网络深度学习模型,该模型可以识别参数值,从而在依赖于一组全面的测量值的情况下产生最高的高程预测精度。我们的研究结果显示了非常有希望的结果,我们将测试数据的高程精度提高了428%,同时显著降低了高程方差。这些结果表明,使用补充测量和数据可以提高高程值,同时显著降低通常与移动设备全球导航卫星系统传感器相关的误差。所提出的方法能够改善基于位置服务的户外运动定位,重点是城市和隐蔽区域。
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引用次数: 0
A survey on data dissemination in internet of vehicles networks 车联网数据传播研究
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2022-11-30 DOI: 10.1080/17489725.2022.2151658
Nadjet Azzaoui, A. Korichi, B. Brik, Hanane Amirat
ABSTRACT Internet of vehicles (IoV) is rapidly growing as key enablers of new applications related to Intelligent Transportation System (ITS), including: autonomous driving, teleoperation, cooperative manoeuvre and perception, etc. The design of such new applications relies mainly on the performance of data dissemination techniques, which enable vehicles to exchange data with their surroundings. In fact, these new applications are coming with new requirements such as ultra-low latency, high bandwidth and communication reliability. This limits also the use of data dissemination techniques designed for traditional vehicular network, especially with the increasing number of connected vehicles on roads. In this paper, we review a taxonomy of data dissemination techniques for IoV based on four new classes: networking-based class, intelligent-based class, traditional-based class, and hybrid class. Furthermore, the paper not only reviews some recent contributions addressing data dissemination in IoV, but also emphasis their enabling technologies, services, architectures, their used simulation tools, and open challenges.
车联网(IoV)作为智能交通系统(ITS)相关新应用的关键推动因素正在迅速发展,包括:自动驾驶、远程操作、协同机动和感知等。这种新应用的设计主要依赖于数据传播技术的性能,使车辆能够与周围环境交换数据。事实上,这些新的应用程序带来了新的要求,如超低延迟、高带宽和通信可靠性。这也限制了为传统车辆网络设计的数据传播技术的使用,特别是随着道路上联网车辆数量的增加。在本文中,我们回顾了基于四种新类别的车联网数据传播技术的分类:基于网络的类、基于智能的类、基于传统的类和混合类。此外,本文不仅回顾了最近关于车联网数据传播的一些贡献,还强调了它们的使能技术、服务、架构、使用的仿真工具和开放的挑战。
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引用次数: 3
Towards mobility reports with user-level privacy 面向具有用户级隐私的移动报告
IF 2.3 Q4 TELECOMMUNICATIONS Pub Date : 2022-09-19 DOI: 10.1080/17489725.2022.2148008
Alexandra Kapp, Saskia Nuñez von Voigt, Helena Mihaljevic, Florian Tschorsch
ABSTRACT The importance of human mobility analyses is growing in both research and practice, especially as applications for urban planning and mobility rely on them. Aggregate statistics and visualizations play an essential role as building blocks of data explorations and summary reports, the latter being increasingly released to third parties such as municipal administrations or in the context of citizen participation. However, such explorations already pose a threat to privacy as they reveal potentially sensitive location information, and thus should not be shared without further privacy measures. There is a substantial gap between state-of-the-art research on privacy methods and their utilization in practice. We thus conceptualize a mobility report with differential privacy guarantees and implement it as open-source software to enable a privacy-preserving exploration of key aspects of mobility data in an easily accessible way. Moreover, we evaluate the benefits of limiting user contributions using three data sets relevant to research and practice. Our results show that even a strong limit on user contribution alters the original geospatial distribution only within a comparatively small range, while significantly reducing the error introduced by adding noise to achieve privacy guarantees.
人类流动性分析在研究和实践中的重要性日益增加,特别是城市规划和流动性的应用依赖于它们。汇总统计和可视化作为数据探索和摘要报告的基石发挥着至关重要的作用,后者越来越多地向市政当局等第三方或在公民参与的背景下发布。然而,这种探索已经对隐私构成了威胁,因为它们会泄露潜在的敏感位置信息,因此在没有进一步的隐私措施的情况下不应该共享。隐私方法的最新研究与实际应用之间存在着很大的差距。因此,我们将具有不同隐私保证的移动性报告概念化,并将其作为开源软件实现,以便以易于访问的方式对移动性数据的关键方面进行隐私保护探索。此外,我们使用与研究和实践相关的三个数据集来评估限制用户贡献的好处。我们的研究结果表明,即使对用户贡献进行严格限制,也只能在相对较小的范围内改变原始地理空间分布,同时显著降低了通过添加噪声来实现隐私保证所带来的误差。
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引用次数: 0
期刊
Journal of Location Based Services
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