[1] 李金林. 汉中市道路交通安全精细化管理问题研究[D]. 长安:长安大学, 2016. LI Jinlin. Hanzhong city road traffic meticulous management issues[D]. Chang'an:Chang'an University, 2016. [2] 孟祥海, 覃薇. 基于统计及假设检验的高速公路事故多发点分析[J].中国安全科学学报,2017,27(5): 159-163. MENG Xianghai, QIN Wei. Analysis of black spot for freeway based on both statistics and hypothesis testing [J]. China Safety Science Journal, 2017,27(5): 159-163. [3] 孟祥海. 道路交通安全管理技术与实践案例[M]. 北京:人民交通出版社, 2017: 44-59. [4] 陈金林. 基于网络核密度估计城市路网事故黑点鉴别研究[D]. 南京:东南大学,2015. CHEN Jinlin. Research on identifying hotspots in the urban road network based on the network kernel density estimation method [D]. Nanjing:Southeast University, 2015. [5] 王海. 基于空间分析技术的交通事故多发点鉴别及成因分析[D]. 北京:清华大学,2014. WANG Hai. Based on spatial analysis technology of traffic black point identification and cause analysis [D]. Beijing:Tsinghua University, 2014. [6] 邓蕙菁, 王雪松, 谢琨. 基于交通冲突技术的交叉口事故多发点判别及致因分析[J].武汉理工大学学报:交通科学与工程版,2012,36(2): 370-373. DENG Huijing, WANG Xuesong, XIE Kun. Intersection hotspot identification and crash severity cause analysis based on traffic conflict technology [J]. Journal of Wuhan University of Technology:Transportation Science & Engineering, 2012,36(2): 370-373. [7] KRAAK M. The space-time cube revisited from a geovisualization perespective[C]. Proceedings of the 21st International Cartographic Conference, 2003: 1 988-1 996. [8] GATALSKY P, ANDRIENKO N, ANDRIENKO G. Interactive analysis of event data using space-time cube[C]. Proceedings of the Eighth International Conference on Information Visualisation, 2004: 145-152. [9] CHENG Shifen, ZHANG Beibei, PENG Peng, et al. Spatiotemporal evolution pattern detection for heavy-duty diesel truck emissions using trajectory mining: a case study of Tianjin, China[J]. Journal of Cleaner Production, 2020,244:118654. [10] 朱艳丽, 靖常峰, 伏家云, 等. 时空立方体的抢劫案件时空特征挖掘与分析[J].测绘科学,2019,44(9): 132-138. ZHU Yanli, JING Changfeng, FU Jiayun, et al. Analysis of space-time pattern of robbery crime based on space-time cube [J]. Science of Surveying and Mapping, 2019,44(9): 132-138. [11] TORSTEN H. What about people in regional science?[J]. Ninth European Congress of the Science Assoication, 1970,XXIV: 7-21. [12] 洪安东. 基于时空立方体的交通拥堵点时空模式挖掘与分析[D].成都:西南交通大学, 2017. HONG Andong. Based on the space-time cube of traffic jams point temporal-spatial pattern mining and analysis [D]. Chengdu:Southwest Jiaotong University, 2017. [13] KENDALL M G, GIBBONS J D. Rank correlation methods:fifth edition [M]. London: Griffin, 1990: 25-38. [14] 吴瑞龙, 朱欣焰, 呙维, 等. 城市道路交通事故时空分布模式分析[J]. 测绘与空间地理信息, 2018, 41(7): 103-106. WU Ruilong, ZHU Xinyan, GUO Wei, et al. Spatio-temporal distribution patterns of urban road traffic accidents [J]. Geomatics & Spatial Information Technology, 2018,41(7): 103-106. [15] 岳瀚, 朱欣焰, 呙维, 等. Knox时空交互检验空间阈值确定方法[J]. 武汉大学学报:信息科学报, 2018,43(11): 1 719-1 724. YUE Han, ZHU Xinyan, GUO Wei, et al. A method for determining the critical spatial threshold of spatio-temporal interaction for the Knox test [J]. Geomatics and Information Science of Wuhan University, 2018,43(11): 1 719-1 724. [16] 吴佩洁, 孟祥海, 崔洪海. 面向NSM的高速公路大区段事故风险预测方法[J]. 交通信息与安全, 2018,36(4): 7-14. WU Peijie, MENG Xianghai, CUI Honghai. A crash prediction method for long segments on freeways based on road network traffic safety management [J]. Journal of Transport Information and Safety, 2018,36(4): 7-14. |