计算机科学 ›› 2019, Vol. 46 ›› Issue (4): 14-21.doi: 10.11896/j.issn.1002-137X.2019.04.003
饶永明, 张延孔, 谢文军, 刘璐, 刘新月, 罗月童
RAO Yong-ming, ZHANG Yan-kong, XIE Wen-jun, LIU Lu, LIU Xin-yue, LUO Yue-tong
摘要: 随着城市化进程的推进,城市人口和车辆迅速增长,城市交通事故日益频发,成为社会关注的热点。以合肥市近十年的交通事故记录数据为研究对象,运用可视分析方法分析交通事故记录数据中事故发生的时间和地点信息,探究交通事故的时空模式,构建交通事故可视分析系统,以辅助相关部门改善交通事故频发问题。文中首次提出了道路事故危险度的概念,并以之为判定依据,结合多尺度时间统计折线图和周期性时间统计环形图等可视化方法,构建了一种新的事故多发路段的识别方法。与传统事故多发路段识别方法相比,本方法无需对道路进行分段处理,从而避免了分段优劣对识别结果的影响。在此基础上,将交通事故数据与城市路网数据相结合,运用可视分析技术构建交通事故可视分析系统。本系统可以帮助相关部门了解总体城市交通事故和单条道路的时间模式及事故多发路段,并探究连续时间限定或周期时间限定下的事故多发路段。除时间条件外,本系统还能识别不同天气等其他限定条件下的事故多发路段,从而使得交警部门能根据不同情况下的道路事故危险度来进行决策管理,并合理部署救援警力,降低事故危害。所提系统对缓解和遏制交通事故增长势头、减少和预防道路交通事故具有重要的现实意义,并且也有利于道路交通的科学有效管理。
中图分类号:
[1]COOK K A,THOMAS J J.Illuminating the Path:The Research and Development Agenda for Visual Analytics[M].National Visualization and Analytics Ctr,2005. [2]ZHU Q,FU X.An overview of multimodal spatial and temporal visual analysis methods [J].Journal of Surveying and Mapping,2017,46(10):1672-1677.(in Chinese) 朱庆,付萧.多模态时空大数据可视分析方法综述[J].测绘学报,2017,46(10):1672-1677. [3]REN L,DU Y,MA S,et al.Overview of visual analysis of big data [J].Journal of Software,2014,25(9):1909-1936.(in Chinese) 任磊,杜一,马帅,等.大数据可视分析综述[J].软件学报,2014,25(9):1909-1936. [4]ZHANG J,YANLI E,MA J,et al.Visual Analysis of Public Utility Service Problems in a Metropolis[J].IEEE Transactions on Visualization & Computer Graphics,2014,20(12):1843-1852. [5]CAO N,LIN Y R,SUN X,et al.Whisper:Tracing the Spatiotemporal Process of Information Diffusion in Real Time[J].IEEE Transactions on Visualization & Computer Graphics,2012,18(12):2649-2658. [6]ZHOU Z G,HU D X,LIU Y N,et al.Visual analysis of spatial and temporal multidimensional properties of air quality monitoring data [J].Journal of computer-aided design and graphics,2017,29(8):1477-1487.(in Chinese) 周志光,胡迪欣,刘亚楠,等.面向空气质量监测数据时空多维属性的可视分析方法[J].计算机辅助设计与图形学学报,2017,29(8):1477-1487. [7]WANG Z,YE T,LU M,et al.Visual Exploration of Sparse Traffic Trajectory Data[J].IEEE Transactions on Visualization &Computer Graphics,2014,20(12):1813-1822. [8]GUO H,WANG Z,YU B,et al.TripVista:Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection[C]∥IEEE Pacific Visualization Symposium.IEEE Computer Society,2011:163-170. [9]WANG Z,LU M,YUAN X,et al.Visual Traffic Jam Analysis Based on Trajectory Data[J].IEEE Transactions on Visualization & Computer Graphics,2013,19(12):2159. [10]LU M,WANG Z,LIANG J,et al.OD-Wheel:Visual design to explore OD patterns of a central region[C]∥Visualization Symposium.IEEE,2015:87-91. [11]LU M,WANG Z,YUAN X.TrajRank:Exploring travel behaviour on a route by trajectory ranking[C]∥Proceedings of IEEE Pacific Visualization Symposium (Pacific Vis’15).IEEE,2015:311-318. [12]ZHANG J Q,ZHAO S X,QU R T.Spatial and temporal data visualization based on point and heat [J].Journal of Lanzhou Jiaotong University,2017,36(3):63-69.(in Chinese) 张金秋,赵庶旭,屈睿涛.基于点与热度的交通时空数据可视化[J].兰州交通大学学报,2017,36(3):63-69. [13]PACK M L,WONGSUPHASAWAT K,VANDANIKER M,et al. ICE--visual analytics for transportation incident datasets[C]∥IEEE International Conference on Information Reuse & Integration.IEEE,2009:200-205. [14]PIRINGER H,BUCHETICS M,BENEDIK R.AlVis:Situation awareness in the surveillance of road tunnels[C]∥Visual Analytics Science and Technology.IEEE,2013:153-162. [15]FAN X,HE B,PATRICK B.Context-Aware Big Data Analytics and Visualization for City-Wide Traffic Accidents[C]∥ International & Interdisciplinary Conference on Modeling & Using Context.Cham:Springer,2017. [16]SHAFABAKHSH G A,FAMILI A,BAHADORI M S.GIS- based spatial analysis of urban traffic accidents:Case study in Mashhad,Iran[J].Journal of Traffic and Transportation Engineering (English Edition),2017(3):82-91. [17]CHEN Q,SONG X,YAMADA H,et al.Learning deep representation from big and heterogeneous data for traffic accident inference[C]∥Thirtieth AAAI Conference on Artificial Intelligence.2016:338-344. [18]LU H S,MAO Z J,ZHONG T Y,et al.Study on the linear intelligent screening system based on GIS-T [C]∥International Urban Transportation Academic Conference.2011.(in Chinese) 卢辉恕,毛志坚,钟天宇,等.基于GIS-T的事故多发点段线性智能排查系统研究[C]∥多国城市交通学术会议.2011. |
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