Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems最新文献_第4页

Autonomous car and ride sharing: flexible road trains: (vision paper) 自动驾驶汽车和拼车:灵活的公路列车:(愿景文件)

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996947

Niels A. H. Agatz, A. Bazzan, Ronny J. Kutadinata, D. Mattfeld, Monika Sester, S. Winter, O. Wolfson

引用次数: 7

k-Optimal meeting points based on preferred paths 基于优选路径的k-最优会合点

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996994

E. Ahmadi, M. Nascimento

引用次数: 9

Interpreting traffic dynamics using ubiquitous urban data 利用无处不在的城市数据解释交通动态

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996962

Fei Wu, Hongjian Wang, Z. Li

{"title":"Interpreting traffic dynamics using ubiquitous urban data","authors":"Fei Wu, Hongjian Wang, Z. Li","doi":"10.1145/2996913.2996962","DOIUrl":"https://doi.org/10.1145/2996913.2996962","url":null,"abstract":"Given a large collection of urban datasets, how can we find their hidden correlations? For example, New York City (NYC) provides open access to taxi data from year 2012 to 2015 with about half million taxi trips generated per day. In the meantime, we have a rich set of urban data in NYC including points-of-interest (POIs), geo-tagged tweets, weather, vehicle collisions, etc. Is it possible that these ubiquitous datasets can be used to explain the city traffic? Understanding the hidden correlation between external data and traffic data would allow us to answer many important questions in urban computing such as: If we observe a high traffic volume at Madison Square Garden (MSG) in NYC, is it because of the regular peak hour or a big event being held at MSG? If a disaster weather such as a hurricane or a snow storm hits the city, how would the traffic be affected? Most of existing studies on traffic dynamics focus only on traffic data itself and do not seek for external datasets to explain traffic. In this paper, we present our results in attempts to understand taxi traffic dynamics in NYC from multiple external data sources. We use four real-world ubiquitous urban datasets, including POIs, weather, geo-tagged tweets, and collision records. To address the heterogeneity of ubiquitous urban data, we present carefully-designed feature representations for these datasets. Our analysis suggests that POIs can well describe the regular traffic patterns. In addition, geo-tagged tweets can be used to explain irregular traffic caused by big events, and weather may account for abnormal traffic drops.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84588730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 64

Efficient in-memory indexing of network-constrained trajectories 网络约束轨迹的高效内存索引

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996972

Benjamin B. Krogh, Christian S. Jensen, K. Torp

引用次数: 22

Enhancing scene parsing by transferring structures via efficient low-rank graph matching 通过高效的低秩图匹配传递结构来增强场景解析

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996956

Tianshu Yu, Ruisheng Wang

{"title":"Enhancing scene parsing by transferring structures via efficient low-rank graph matching","authors":"Tianshu Yu, Ruisheng Wang","doi":"10.1145/2996913.2996956","DOIUrl":"https://doi.org/10.1145/2996913.2996956","url":null,"abstract":"Scene parsing has attracted significant attention for its practical and theoretical value in computer vision. A typical scene parsing algorithm seeks to densely label pixels or 3-dimensional points from a scene. Traditionally, this procedure relies on a pre-trained classifier to identify the label information, and a smoothing step via Markov Random Field to enhance the consistency. LabelTranfer is a category of scene parsing algorithms to enhance traditional scene parsing framework, by finding dense correspondence and transferring labels across scenes. In this paper, we present a novel scene parsing algorithm which matches maximal similar structures between scenes via efficient low-rank graph matching. The inputs of the algorithm are images, and well- aligned point clouds if available. The images and the point clouds are processed in separate pipelines. The pipeline of images is to learn a reliable classifier and to match local structures via graph matching. The pipeline of point clouds is to conduct preliminary segmentation and to generate feasible label sets. The two pipelines are merged at inference step, in which we elaborate effective and efficient potential functions. We propose a new graph matching model incorporating low-rank and Frobenius regularization, which not only guarantees an accurate solution, but also provides high optimization efficiency via an eigen-decomposition strategy. Several challenging experiments are conducted, showing competitive performance of the proposed method compared to state-of-the-art LabelTransfer algorithm. Further, with point clouds, the performance can be significantly enhanced.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77102413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A vision for micro and macro location aware services 对微观和宏观位置感知服务的展望

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996977

Abdeltawab M. Hendawi, Mohamed E. Khalefa, Harry Liu, Mohamed H. Ali, J. Stankovic

{"title":"A vision for micro and macro location aware services","authors":"Abdeltawab M. Hendawi, Mohamed E. Khalefa, Harry Liu, Mohamed H. Ali, J. Stankovic","doi":"10.1145/2996913.2996977","DOIUrl":"https://doi.org/10.1145/2996913.2996977","url":null,"abstract":"A few decades ago, the Internet was created. Since then, searching for information and services has increased exponentially. With the introduction of GPS-enabled devices, a special type of search appeared offering location-aware services. These services customize search results based on users' location. This includes, but not limited to, (1) service finding, e.g., \"find the nearest pizza restaurant\", (2) routing, e.g., \"obtain the shortest path from a user's home to the airport\", (3) transportation, e.g., \"what are the bus links to get a user from downtown to the mall\", and (4) monitoring, e.g., \"alert a parent if their child school-bus deviates from its regular route\". Though new hardware and software technologies such as smart watches, voice search, and big-data platforms have been introduced and widely used, each single type of the above services has benefited very little from these technologies. On the local level of each service (the micro level), a full-fledged view is still missing. On the global level of all service types (the macro level), all Location-aware services are still acting as isolated islands and a global optimized service is not available. This paper presents our vision of how to provide an integrated macro location-aware service that acts harmoniously, and how each micro service can be further improved by better incorporation of novel technologies. We also overview the key challenges associated with these suggested improvements. Then, we highlight the potential value-added by the application of our vision.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87770610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Real-time urban population monitoring using pervasive sensor network 基于普适传感器网络的城市人口实时监测

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996937

Gautam Thakur, P. Kuruganti, M. Bobrek, S. Killough, J. Nutaro, Cheng Liu, W. Lu

{"title":"Real-time urban population monitoring using pervasive sensor network","authors":"Gautam Thakur, P. Kuruganti, M. Bobrek, S. Killough, J. Nutaro, Cheng Liu, W. Lu","doi":"10.1145/2996913.2996937","DOIUrl":"https://doi.org/10.1145/2996913.2996937","url":null,"abstract":"It is estimated that 50% of the global population lives in urban areas occupying just 0.4% of the Earth's surface. Understanding urban activity constitutes monitoring population density and its changes over time, in urban environments. Currently, there are limited mechanisms to non-intrusively monitor population density in real-time. The pervasive use of cellular phones in urban areas is one such mechanism that provides a unique opportunity to study population density by monitoring the mobility patterns in near real-time. Cellular carriers such as AT&T harvest such data through their cell towers; however, this data is proprietary and the carriers restrict access, due to privacy concerns. In this work, we propose a system that passively senses the population density and infers mobility patterns in an urban area by monitoring power spectral density in cellular frequency bands using periodic beacons from each cellphone without knowing who and where they are located. A wireless sensor network platform is being developed to perform spectral monitoring along with environmental measurements. Algorithms are developed to generate real-time fine-resolution population estimates.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86912023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A SMART approach to quality assessment of site-based spatio-temporal data 基于站点的时空数据质量评估的SMART方法

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996932

D. Galarus, R. Angryk

引用次数: 8

A Markov chain based pruning method for predictive range queries 基于马尔可夫链的预测范围查询剪枝方法

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996922

Xiaofeng Xu, Li Xiong, V. Sunderam, Yonghui Xiao

引用次数: 4

MultiCalib: national-scale traffic model calibration in real time with multi-source incomplete data MultiCalib:多源不完整数据的全国范围交通模型实时标定

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems Pub Date : 2016-10-31 DOI: 10.1145/2996913.2996918

Desheng Zhang, Fan Zhang, T. He

{"title":"MultiCalib: national-scale traffic model calibration in real time with multi-source incomplete data","authors":"Desheng Zhang, Fan Zhang, T. He","doi":"10.1145/2996913.2996918","DOIUrl":"https://doi.org/10.1145/2996913.2996918","url":null,"abstract":"Real-time traffic modeling at national scale is essential to many applications, but its calibration is extremely challenging due to its large spatial and fine temporal coverage. The existing work mostly is focused on urban-scale calibration with complete field data from single data sources (e.g., loop sensors or taxis), which cannot be generalized to national scale, because complete single-source field data at national scale are almost impossible to obtain. To address this challenge, in this paper, we design MultiCalib, a model calibration framework to optimize traffic models based on multiple incomplete data sources at national scale in real time. Instead of naively combining multi-source data, we theoretically formulate a multi-source model calibration problem based on real-world contexts and multi-view learning. More importantly, we implement and evaluate MultiCalib with two heterogeneous nationwide vehicle networks with 340,000 vehicles to infer traffic conditions on 36 expressways and 119 highways, along with 4 cities across China. The results show that MultiCalib outperforms state-of-the- art calibration by 25% on average with same input data.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83036057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10