UrbComp '13最新文献

Spatiotemporal periodical pattern mining in traffic data 交通数据的时空周期模式挖掘

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505837

Tanvi Jindal, P. Giridhar, L. Tang, Jun Li, Jiawei Han

{"title":"Spatiotemporal periodical pattern mining in traffic data","authors":"Tanvi Jindal, P. Giridhar, L. Tang, Jun Li, Jiawei Han","doi":"10.1145/2505821.2505837","DOIUrl":"https://doi.org/10.1145/2505821.2505837","url":null,"abstract":"The widespread use of road sensors has generated huge amount of traffic data, which can be mined and put to various different uses. Finding frequent trajectories from the road network of a big city helps in summarizing the way the traffic behaves in the city. It can be very useful in city planning and traffic routing mechanisms, and may be used to suggest the best routes given the region, road, time of day, day of week, season, weather, and events etc. Other than the frequent patterns, even the events that are not so frequent, such as those observed when there is heavy snowfall, other extreme weather conditions, long traffic jams, accidents, etc. might actually follow a periodic occurrence, and hence might be useful to mine. This problem of mining the frequent patterns from road traffic data has been addressed in previous works using the context knowledge of the road network of the city. In this paper, we have developed a method to mine spatiotemporal periodic patterns in the traffic data and use these periodic behaviors to summarize the huge road network. The first step is to find periodic patterns from the speed data of individual road sensor stations, and use their periods to represent the station's periodic behavior using probability distribution matrices. Then, we use density-based clustering to cluster the sensors on the road network based on the similarities between their periodic behavior as well as their geographical distance, thus combining similar nodes to form a road network with larger but fewer nodes.","PeriodicalId":157169,"journal":{"name":"UrbComp '13","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124911777","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: 38

Whose "city of tomorrow" is it?: on urban computing, utopianism, and ethics 这是谁的“明天之城”?:关于城市计算、乌托邦主义和伦理

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505838

Justin Cranshaw

引用次数: 6

Daily travel behavior: lessons from a week-long survey for the extraction of human mobility motifs related information 日常出行行为:从为期一周的调查中提取人类出行动机相关信息的经验教训

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505829

C. Schneider, C. Rudloff, D. Bauer, Marta C. González

{"title":"Daily travel behavior: lessons from a week-long survey for the extraction of human mobility motifs related information","authors":"C. Schneider, C. Rudloff, D. Bauer, Marta C. González","doi":"10.1145/2505821.2505829","DOIUrl":"https://doi.org/10.1145/2505821.2505829","url":null,"abstract":"Multi-agent models for simulating the mobility behavior of the urban population are gaining momentum due to increasing computing power. Such models pose high demands in terms of input data in order to be reliably able to match real world behavior. To run the models a synthetic population mirroring typical mobility demand needs to be generated based on real world observations. Traditionally this is done using travel diary surveys, which are costly (and hence have relatively low sample size) and focus mainly on trip choice rather than on activities for an entire day. Thus in this setting the generation of synthetic populations either relies on resampling identical activity chains or on imposing independence of various trips occurring during the day. Both assumptions are not realistic.\u0000 Using Call Detail Records (CDRs) it has been found that individual daily movement uses only a small number of movement patterns. These patterns, termed motifs, appear stably in many different cities, as has been shown for both CDR data as well as travel diaries.\u0000 In this paper the relation between these motifs and other mobility related quantities like the distribution of travel distances and times as well as mode choice is investigated. Additionally transition probabilities both for motifs (relevant for multi-day simulations) and mode transitions are discussed.\u0000 The main finding is that while some of the characteristics seem to be unrelated to motifs, others such as mode choice exhibit strong correlations which could improve the provision of synthetic populations for multi-agent models.\u0000 Thus the results in this paper are seen as one step further towards the creation of realistic (with respect to mobility behavior) synthetic populations for multi-agent models in order to analyze the performance of multi-modal transportation systems or disease spreading in urban areas.","PeriodicalId":157169,"journal":{"name":"UrbComp '13","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124786322","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: 36

Exploring human movements in Singapore: a comparative analysis based on mobile phone and taxicab usages 探索新加坡的人类运动:基于手机和出租车使用的比较分析

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505826

Chaogui Kang, Stanislav Sobolevsky, Yu Liu, C. Ratti

{"title":"Exploring human movements in Singapore: a comparative analysis based on mobile phone and taxicab usages","authors":"Chaogui Kang, Stanislav Sobolevsky, Yu Liu, C. Ratti","doi":"10.1145/2505821.2505826","DOIUrl":"https://doi.org/10.1145/2505821.2505826","url":null,"abstract":"Existing studies extensively utilized taxicab trips and individuals' movements captured by mobile phone usages (referred as \"mobile phone movements\" hereafter) to understand human mobility patterns in an area. However, all these studies analyze taxicab trips and mobile phone movements separately.\u0000 In this paper, we: (1) integrate mobile phone and taxicab usages together to explore human movements in Singapore and reveal that mobile phone movements as a general proxy to all kinds of human mobility has substantially different characteristics compared to taxicab trips, which are one of the frequently used means of transportation; (2) investigate the ratio of taxicab trips and mobile phone movements between two arbitrary locations, which not only characterizes taxicab demands between these locations but also sheds light on underlying land use patterns.\u0000 In details, we quantify the distinct characteristics of mobile phone movements and taxicab trips, and particularly confirm that the number of taxicab trips decays with distance more slowly compared to mobile phone movements. From a spatial network perspective, taxicab trips largely reflect interactions between further-separating locations than mobile phone movements, resulting in emergence of larger spatial communities (delineated based on people mobility) in Singapore.\u0000 The contribution of this research is two-fold: (1) we clarified the divergences between observed human mobility patterns based on taxicab and mobile phone data; (2) we implemented an integrated approach of taxicab and mobile phone usages for gaining more informative insights in population dynamics, transportation and urban configuration.","PeriodicalId":157169,"journal":{"name":"UrbComp '13","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133044757","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: 121

Exploring venue-based city-to-city similarity measures 探索基于场馆的城市间相似性度量

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505832

Daniel Preotiuc-Pietro, Justin Cranshaw, T. Yano

引用次数: 31

On the importance of temporal dynamics in modeling urban activity 关于时间动态在模拟城市活动中的重要性

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505825

Ke Zhang, Qiuye Jin, K. Pelechrinis, Theodoros Lappas

{"title":"On the importance of temporal dynamics in modeling urban activity","authors":"Ke Zhang, Qiuye Jin, K. Pelechrinis, Theodoros Lappas","doi":"10.1145/2505821.2505825","DOIUrl":"https://doi.org/10.1145/2505821.2505825","url":null,"abstract":"The vast amount of available spatio-temporal data of human activities and mobility has given raise to the rapidly emerging field of urban computing/informatics. Central to the latter is understanding the dynamics of the activities that take place in an urban area (e.g., a city). This can significantly enhance functionalities such as resource and service allocation within a city. Existing literature has paid a lot of attention on spatial dynamics, with the temporal ones often being neglected and left out. However, this can lead to non-negligible implications. For instance, while two areas can appear to exhibit similar activity when the latter is aggregated in time, they can be significantly different when introducing the temporal dimension. Furthermore, even when considering a specific area X alone, the transitions of the activity that takes place within X are important themselves. Using data from the most prevalent location-based social network (LBSN for short), Foursquare, we analyze the temporal dynamics of activities in New York City and San Francisco. Our results clearly show that considering the temporal dimension provides us with a different and more detailed description of urban dynamics. We envision this study to lead to more careful and detailed consideration of the temporal dynamics when analyzing urban activities.","PeriodicalId":157169,"journal":{"name":"UrbComp '13","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133697415","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: 33

Analyzing the composition of cities using spatial clustering 利用空间聚类分析城市构成

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505827

Zechun Cao, Sujing Wang, G. Forestier, A. Puissant, C. Eick

{"title":"Analyzing the composition of cities using spatial clustering","authors":"Zechun Cao, Sujing Wang, G. Forestier, A. Puissant, C. Eick","doi":"10.1145/2505821.2505827","DOIUrl":"https://doi.org/10.1145/2505821.2505827","url":null,"abstract":"Cities all around the world are in constant evolution due to numerous factors, such as fast urbanization and new ways of communication and transportation. Since understanding the composition of cities is the key to intelligent urbanization, there is a growing need to develop urban computing and analysis tools to guide the orderly development of cities, as well as to enhance their smooth and beneficiary evolution. This paper presents a spatial clustering approach to discover interesting regions and regions which serve different functions in cities. Spatial clustering groups the objects in a spatial dataset and identifies contiguous regions in the space of the spatial attributes. We formally define the task of finding uniform regions in spatial data as a maximization problem of a plug-in measure of uniformity and introduce a prototype-based clustering algorithm named CLEVER to find such regions. Moreover, polygon models which capture the scope of a spatial cluster and histogram-style distribution signatures are used to annotate the content of a spatial cluster in the proposed methodology; they play a key role in summarizing the composition of a spatial dataset. Furthermore, algorithms for identifying popular distribution signatures and approaches for identifying regions which express a particular distribution signature will be presented. The proposed methodology is demonstrated and evaluated in a challenging real-world case study centering on analyzing the composition of the city of Strasbourg in France.","PeriodicalId":157169,"journal":{"name":"UrbComp '13","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124323323","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: 23

Real-time air quality monitoring through mobile sensing in metropolitan areas 利用移动传感技术实时监测大都市地区空气质量

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505834

Srinivas Devarakonda, Parveen Sevusu, Hongzhang Liu, Ruilin Liu, L. Iftode, Badri Nath

引用次数: 354

Prediction of user location using the radiation model and social check-ins 使用辐射模型和社交签到来预测用户位置

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505833

Alexey Tarasov, Felix Kling, A. Pozdnoukhov

引用次数: 20

Modeling urban traffic dynamics in coexistence with urban data streams 与城市数据流共存的城市交通动态建模

UrbComp '13 Pub Date : 2013-08-11 DOI: 10.1145/2505821.2505822

V. Moosavi, L. Hovestadt

{"title":"Modeling urban traffic dynamics in coexistence with urban data streams","authors":"V. Moosavi, L. Hovestadt","doi":"10.1145/2505821.2505822","DOIUrl":"https://doi.org/10.1145/2505821.2505822","url":null,"abstract":"Classic paradigm of scientific modeling is mainly based on a set of previously, accepted or assumed theories about the target phenomena and a validation procedure by limited observations. Therefore, normally data has a supporting role in the modeling process. On the other hand, recent advances in computing technology have brought us a data deluge that may change the classic paradigm of scientific modeling. Information flows and data streams have reached a level of maturity that they can play the main role in modeling of the real systems, without relying on lots of assumptions and rules in the first step. This turn may cause an inversion in the concept of modeling as a rational process.\u0000 The proposed theoretical idea in this work is that traditional theory-driven models have a theoretical limit in modeling complex systems, known as curse of dimensionality and further, to highlight the fact that massive urban data streams can open up a new data-driven modeling approach, which goes beyond simple data driven analytics or eye catching info-graphics toward operational models of complex phenomena.\u0000 In this work we describe a conceptual framework for modeling city wide traffic dynamics that proposes a way to encapsulate the complexity based on abstraction power of Markov chains in a coexistence with continuous data streams. Therefore, finally as an experimental set up, we applied the proposed model to a real data set, consisting of GPS traces of taxi cabs in Beijing and the results have been explained.","PeriodicalId":157169,"journal":{"name":"UrbComp '13","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120937677","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: 24