Mobility Data-Driven Urban Traffic Monitoring
暫譯: 以移動數據驅動的城市交通監測

Liu, Zhidan, Wu, Kaishun

Mobility Data-Driven Urban Traffic Monitoring
  • 出版商: Springer
  • 出版日期: 2021-05-19
  • 售價: $2,990
  • 貴賓價: 9.5 折 $2,841
  • 語言: 英文
  • 頁數: 69
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 981162240X
  • ISBN-13: 9789811622403

    • 海外代購書籍(需單獨結帳)

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商品描述

This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring.

This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory to recover traffic conditions of the whole road network from sparse traffic samplings. Second, the authors have compared the traffic estimation performances between linear and nonlinear traffic correlation models and proposed a dynamical non-linear traffic correlation modelling-based urban traffic monitoring approach. To address the challenge of involved huge computation overheads, the approach adapts the traffic modelling and estimations tasks to Apache Spark, a popular parallel computing framework. Third, in addition to mobility data collected by the public transit systems, the authors present a crowdsensing-based urban traffic monitoring approach. The proposal exploits the lightweight mobility data collected from participatory bus riders to recover traffic statuses through careful data processing and analysis. Last but not the least, the book points out some future research directions, which can further improve the accuracy and efficiency of mobility data-driven urban traffic monitoring at large scale.

This book targets researchers, computer scientists, and engineers, who are interested in the research areas of intelligent transportation systems (ITS), urban computing, big data analytic, and Internet of Things (IoT). Advanced level students studying these topics benefit from this book as well.

商品描述(中文翻譯)

這本書介紹了移動數據和數據驅動的城市交通監測概念。書中還呈現了一個基於移動數據的城市交通監測的典型框架，描述了移動數據收集、數據處理、交通建模的過程，以及應用這些模型進行城市交通監測的一些實際問題。

本書提出了三種新穎的基於移動數據的城市交通監測方法。首先，為了解決移動數據稀疏的挑戰，作者提出了一種基於壓縮感知的城市交通監測方法。這個解決方案在道路網絡規模上挖掘交通相關性，並利用壓縮感知理論從稀疏的交通取樣中恢復整個道路網絡的交通狀況。其次，作者比較了線性和非線性交通相關模型之間的交通估計性能，並提出了一種基於動態非線性交通相關建模的城市交通監測方法。為了解決涉及的巨大計算開銷，該方法將交通建模和估計任務適應於Apache Spark，一個流行的並行計算框架。第三，除了公共交通系統收集的移動數據外，作者還提出了一種基於群眾感知的城市交通監測方法。該提案利用從參與的公車乘客收集的輕量級移動數據，通過仔細的數據處理和分析來恢復交通狀態。最後但同樣重要的是，書中指出了一些未來的研究方向，這些方向可以進一步提高大規模基於移動數據的城市交通監測的準確性和效率。

本書的目標讀者是對智能交通系統（ITS）、城市計算、大數據分析和物聯網（IoT）研究領域感興趣的研究人員、計算機科學家和工程師。學習這些主題的高級學生也能從本書中受益。

作者簡介

Zhidan Liu is currently Assistant Professor in the College of Computer Science and Software Engineering, Shenzhen University, China. He received a Ph.D. degree in Computer Science and Technology from Zhejiang University, China, in 2014. Before joining in Shenzhen University, he was Postdoctoral Research Fellow in the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Dr. Liu's research interests include Internet of Things, urban computing, crowdsourcing, and big data analytics. He has published more than 20 research papers in top-tier international journals and conferences, including IEEE/ACM ToN, IEEE TMC, IEEE TITS, IEEE Network Magazine, IEEE IOTJ, ACM MobiSys, IEEE ICDE, ACM/IEEE IPSN, and ACM MobiHoc. He received the "Best Paper Award" of IEEE ICPADS 2020. Dr. Liu served as Technical Programme Committee Member of IEEE ICDCS, IEEE ICPADS, IEEE ICCCN, IEEE MSN, IEEE MASS, and IEEE HiPC. He is Member of IEEE, ACM, and CCF.

Kaishun Wu is currently Distinguished Professor in the College of Computer Science and Software Engineering, Shenzhen University, China, where he leads the Research Centre of Internet of Things. Professor Wu's research interests include wireless communications and mobile computing. He has co-authored 2 books and published over 100 refereed papers in international leading journals and primer conferences. He is Inventor of 8 US and 100 Chinese pending patents (63 are issued). Professor Wu serves as Associate Editor of IET COMMUNICATIONS, IEEE Access, and Guest Editor of IEEE Network. He is Technical Program Committee Member of IEEE INFOCOM, IEEE ICDCS, IEEE ICC, IEEE Globecom, and so on. He won the best paper awards in IEEE Globecom 2012, IEEE ICPADS 2012, IEEE MASS 2014, IEEE SECON 2018. Professor Wu was selected as Winner of 2012 Hong Kong Young Scientist Award. He was also one of the winners of 2014 Hong Kong ICT Awards: Best Innovation. He received 2014 IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award. He is IET Fellow and IEEE Senior Member.

作者簡介(中文翻譯)

Zhidan Liu 目前是中國深圳大學計算機科學與軟體工程學院的助理教授。他於2014年在中國浙江大學獲得計算機科學與技術的博士學位。在加入深圳大學之前，他曾在新加坡南洋理工大學計算機科學與工程學院擔任博士後研究員。劉博士的研究興趣包括物聯網、城市計算、群眾外包和大數據分析。他在頂尖國際期刊和會議上發表了超過20篇研究論文，包括 IEEE/ACM ToN、IEEE TMC、IEEE TITS、IEEE Network Magazine、IEEE IOTJ、ACM MobiSys、IEEE ICDE、ACM/IEEE IPSN 和 ACM MobiHoc。他獲得了 IEEE ICPADS 2020 的「最佳論文獎」。劉博士曾擔任 IEEE ICDCS、IEEE ICPADS、IEEE ICCCN、IEEE MSN、IEEE MASS 和 IEEE HiPC 的技術程序委員會成員。他是 IEEE、ACM 和 CCF 的會員。

Kaishun Wu 目前是中國深圳大學計算機科學與軟體工程學院的特聘教授，並領導物聯網研究中心。吳教授的研究興趣包括無線通信和移動計算。他共同撰寫了2本書籍，並在國際領先的期刊和主要會議上發表了超過100篇經過審核的論文。他是8項美國和100項中國待審專利的發明人（其中63項已獲得授權）。吳教授擔任 IET COMMUNICATIONS、IEEE Access 的副編輯，以及 IEEE Network 的客座編輯。他是 IEEE INFOCOM、IEEE ICDCS、IEEE ICC、IEEE Globecom 等會議的技術程序委員會成員。他在 IEEE Globecom 2012、IEEE ICPADS 2012、IEEE MASS 2014 和 IEEE SECON 2018 獲得最佳論文獎。吳教授被選為2012年香港青年科學家獎的獲獎者，也是2014年香港資訊及通訊科技獎：最佳創新獎的獲獎者之一。他獲得了2014年 IEEE ComSoc 亞太區傑出青年研究者獎。他是 IET Fellow 和 IEEE 高級會員。

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