[1] 高强, 张凤荔, 王瑞锦, 等. 轨迹大数据: 数据处理关键技术研究综述[J]. 软件学报, 2017, 28(4): 959-993. [GAO Q, ZHANG F L, WANG R J, et al. Trajectory big data: A review of key technologies in data processing[J]. Journal of Software, 2017, 28(4): 959-993.]
[2] 赵竹珺, 吉根林. 时空轨迹分类研究进展[J]. 地球信息科学学报, 2017, 19(3): 289-297. [ZHAO Z J, JI G L. Research progress of spatial-temporal trajectory classification[J]. Journal of Geo-information Science, 2017, 19(3): 289-297.]
[3] HAO J, ZHU J, ZHONG R. The rise of big data on urban studies and planning practices in China: Review and open research issues[J]. Journal of Urban Management, 2015(4): 92-124.
[4] ZHOU Z, DOU W, JIA G, et al. A method for real-time trajectory monitoring to improve taxi service using GPS big data[J]. Information & Management, 2016(53): 964-977.
[5] ZHENG W, HUANG X, LI Y. Understanding the tourist mobility using GPS: Where is the nextplace?[J]. Tourism Management, 2017(59): 267-280.
[6] 郑宇. 城市计算概述[J]. 武汉大学学报(信息科学版), 2015, 40(1): 1-13. [ZHENG Y. Overview of urban computing[J]. Geomatics and Information Science of Wuhan University, 2015, 40(1): 1-13.]
[7] 牟乃夏, 张恒才, 陈洁, 等. 轨迹数据挖掘城市应用研究综述[J]. 地球信息科学, 2015, 17(10): 1136-1142. [MOU N X, ZHANG H C, CHEN J, et al. A survey of urban application research on track data mining[J]. Journal of Geo-information Science, 2015, 17(10): 1136-1142.]
[8] CASTRO P S, ZHANG D, LI S. Urban traffic modelling and prediction using large scale taxi GPS traces[M]. Pervasive Computing, Springer Berlin Heidelberg, 2012.
[9] ZHAN X, HASAN S, UKKUSUR S V, et al. Urban link travel time estimation using large- scale taxi data with partial information[J]. Transportation Research Part C: Emerging Technologies, 2013, 33(2013): 37-49.
[10] 齐观德, 潘遥, 李石坚, 等. 基于出租车轨迹数据挖掘的 乘 客 候 车 时 间 预 测 [J], 软 件 学 报, Journal of Software, 2013, 24(Sup2): 14-23. [QI D G, PAN Y, LI S J, et al. Predicting passengers’waiting time by mining taxi traces[J]. Journal of Software, 2013, 24(Sup2): 14-23.]
[11] FUSCO G, COLOMBARONI C, ISAENKO N. Shortterm speed predictions exploiting big data on large urban road networks[J]. Transportation Research Part C, 2016 , 2016(73): 183-201.
[12] CUI J, LIU F, HU J, et al. Identifying mismatch between urban travel demand and transport network services using GPS data: A case study in the fast growing Chinese city of Harbin[J]. Neurocomputing, 2016, 2016 (181): 4-18.
[13] 杨伟, 艾廷华. 基于车辆轨迹大数据的道路网更新方法研究[J]. 计算机研究与发展,2016, 53(12): 2681-2693. [YANG W, AI T H. A method for road network updating based on vehicle trajectory big data[J]. Journal of Computer Research and Development, 2016, 53(12): 2681-2693.]
[14] 胡一竑, 吴勤旻, 朱道立. 城市道路网络的拓扑性质和脆弱性分析[J]. 复杂系统与复杂性科学, 2009, 6(3): 69-76. [HU Y H, WU Q M, ZHU D L. Topological properties and vulnerability analysis of spatial urban street networks[J]. Journal of Computer Research and Development, 2009, 6(3): 69-76.]
[15] NIK HASHIM NIK MUSTAPHA, NIK NUR WAHIDAH NIK HASHIM. Outflow of traffic from the national capital Kuala Lumpur to the north, south and east coast highways using flow, speed and density relationships[J]. Journal of Traffic and Transportation Engineering, 2016, 6(3): 540-548.
[16] 张琨, 李配配, 朱保平, 等. 基于 PageRank的有向加权复杂网络节点重要性评估方法[J]. 南京航空航天大学学 报, 2013, 45(3): 429- 434. [ZHANG K, LI P P, ZHU B P, et al. Evaluation method for node importance in directed-weighted complex networks based on pagerank[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2013, 45(3): 429-434.]
[17] MOKBEL M F, et al. MNTG: An extensible web-based traffic generator[M]. In: Nascimento M A, et al. (eds), Advances in Spatial and Temporal Databases, SSTD 2013. Lecture Notes in Computer Science, vol 8098. Springer, Berlin, Heidelberg, 2013.
[18] 马云飞. 基于出租车轨迹点的居民出行热点区域与时空特征研究: 以昆山市为例[D].南京:南京师范大学,2014. [MA Y F. Research on residents behavior of attractive areas and spatial-temporal feature based on taxi trajectory data:A case of kunshan city[D]. Nanjing Normal University, 2014.]
[19] 中华人民共和国公共安全行业标准. 城市道路交通管理评价指标体系[S]. 中华人民共和国公共安全行业标准, 2002. [People's Republic of China Public Safety Industry Standard. Evaluation index system of urban road traffic management[S]. People's Republic of China Public Safety Industry Standard, 2002.] |