GeoVisual analytics for understanding the distribution of speeding patterns on arterial roads: assessing the traffic safety of vulnerable road users

References

• Agerholm, N., D. Knudsen, and K. Variyeswaran. 2017. “Speed-calming Measures and Their Effect on Driving Speed – Test of a New Technique Measuring Speeds Based on GNSS Data.” Review Of. Transportation Research Part F: Traffic Psychology and Behaviour 46: 263–270. doi:10.1016/j.trf.2016.06.022.
   Web of Science ®Google Scholar
• Ahmadi, M., A. Valinejadi, A. Goodarzi, A. Safari, M. Hemmat, H. A. Majdabadi, and A. Mohammadi. 2017. “Geographic Information System (GIS) Capabilities in Traffic Accident Information Management: A Qualitative Approach.” Review Of. Electronic Physician 9 (6): 4533–4540. doi:10.19082/4533.
   PubMedGoogle Scholar
• Akin, D., V. P. Sisiopiku, and A. Skabardonis. 2011. “Impacts of Weather on Traffic Flow Characteristics of Urban Freeways in Istanbul.” Review Of. Procedia - Social and Behavioral Sciences 16: 89–99. doi:10.1016/j.sbspro.2011.04.432.
   Google Scholar
• Andrienko, G., and N. Andrienko 2008. “Spatio-temporal Aggregation for Visual Analysis of Movements”. Paper presented at the IEEE Symposium on Visual Analytics Science and Technology, Columbus, OH, USA, 19–24 Oct.
   Google Scholar
• Andrienko, G., N. Andrienko, P. Bak, D. Keim, S. Kisilevich, and S. Wrobel. 2011a. “A Conceptual Framework and Taxonomy of Techniques for Analyzing Movement.” Review Of. Journal of Visual Languages & Computing 22 (3): 213–232. doi:10.1016/j.jvlc.2011.02.003.
   Web of Science ®Google Scholar
• Andrienko, G., N. Andrienko, P. Bak, D. Keim, and S. Wrobel. 2013. Visual Analytics of Movement. Springer International: Springer-Verlag Berlin Heidelberg.
   Google Scholar
• Andrienko, G., N. Andrienko, C. Hurter, S. Rinzivillo, and S. Wrobel 2011b. “From Movement Tracks through Events to Places: Extracting and Characterizing Significant Places from Mobility Data”. Paper presented at the IEEE Conference on Visual Analytics Science and Technology (VAST), Providence, RI, USA, 23–28 Oct.
   Google Scholar
• Andrienko, G., N. Andrienko, P. Jankowski, D. Keim, M. J. Kraak, A. MacEachren, and S. Wrobel. 2007. “Geovisual Analytics for Spatial Decision Support: Setting the Research Agenda.” Review of International Journal of Geographical Information Science 21 (8): 839–857. doi:10.1080/13658810701349011.
   Web of Science ®Google Scholar
• Andrienko, G., N. Andrienko, and S. Wrobel. 2007. “Visual Analytics Tools for Analysis of Movement Data.” Review Of. SIGKDD Explor Newsl. 9 (2): 38–46. doi:10.1145/1345448.1345455.
   Google Scholar
• Andrienko, N., G. Andrienko, and P. Gatalsky. 2003. “Exploratory Spatio - Temporal Visualization: An Analytical Review.” Review of Journal of Visual Languages and Computing 14 (6): 503–541. doi:10.1016/S1045-926X(03)00046-6.
   Web of Science ®Google Scholar
• Attaset, V., R. J. Schneider, L. S. Arnold, and D. R. Ragland 2010. “Effects of Weather Variables on Pedestrian Volumes in Alameda County, California.” In Safe Transportation Research & Education Center. UC Berkeley.
   Google Scholar
• Bertin, J. (1983). “Semiology of Graphics: Diagrams, Networks, Maps”. Madison (first published in French in 1967, translated to English by Berg WJ in 1983): The University of Wisconsin Press.
   Google Scholar
• Buja, A., D. Cook, and D. F. Swayne. 1996. “Interactive High-Dimensional Data Visualization.” Review Of. Computational and Graphical Statistics 5 (1): 78–99. doi:10.1080/10618600.1996.10474696.
   Google Scholar
• Cheng, T., G. Tanaksaranond, C. Brunsdon, and J. Haworth. 2013. “Exploratory Visualisation of Congestion Evolutions on Urban Transport Networks.” Review Of. Transportation Research Part C: Emerging Technologies 36: 296–306. doi:10.1016/j.trc.2013.09.001.
   Web of Science ®Google Scholar
• Cruz, P. M., P. Machado, and J. Bicker 2010. “Visualizing Lisbon’s Traffic.” http://www.visualcomplexity.com
   Google Scholar
• Dorling, D. 1992. “Stretching Space and Splicing Time: From Cartographic Animation to Interactive Visualization.” Review Of. Cartography and Geographic Information Science 19: 215–227. doi:10.1559/152304092783721259.
   Web of Science ®Google Scholar
• Dorling, D. 1996. Area Cartograms: Their Use and Creation. 59, Concepts and Techniques in Modern Geography. UK: University of East Anglia.
   Google Scholar
• Eksler, V., M. Popolizio, and R. Allsop. 2009. “How Far from Zero?” In Benchmarking of Road Safety Performance in the Nordic Countries. Brussels: European Transport Safety Council. https://www.academia.edu/24745378/How_far_from_Zero_Benchmarking_of_road_safety_performance_in_the_Nordic_countriesT
   Google Scholar
• Elvik, R. 2009. The Handbook of Road Safety Measures. second ed. Oslo, Norway: Emerald.
   Google Scholar
• Elvik, R., A. Hoye, T. Vaa, and M. Sorensen. 2009. The Handbook of Road Safety Measures. 2nd ed. UK: Emerald Group Publishing Limited.
   Google Scholar
• European Commission 2017. “Traffic Safety Basic Facts 2017 - Pedestrians.” Traffic Safety, edited by Commission E. Belgium: European Road Safety Observatory.
   Google Scholar
• Guo, H., Z. Wang, B. Yu, H. Zhao, and X. Yuan 2011. “TripVista: Triple Perspective Visual Trajectory Analytics and Its Application on Microscopic Traffic Data at a Road Intersection”. Paper presented at the 2011 IEEE Pacific Visualization Symposium, Hong Kong, China, 1-4 March 2011.
   Google Scholar
• International Traffic Safety Data and Analysis Group (IRTAD) 2014. “Pedestrian Safety, Urban Space and Health.” In International Transport Forume. OECD.
   Google Scholar
• Keim, D. 2002. “Information Visualization and Visual Data Mining.” Review Of. Transactions on Visualization and Computer Graphics IEEE 8 (1): 1–8. doi:10.1109/2945.981847.
   Web of Science ®Google Scholar
• Keim, D., M. C. Hao, U. Dayal, and M. Hsu. 2002. “Pixel Bar Charts: A Visualization Technique for Very Large Multi-Attribute Data Sets.” Review Of. Information Visualization 1 (1): 20–34. doi:10.1057/palgrave.ivs.9500003.
   Google Scholar
• Keim, D., F. Mansmann, J. Schneidewind, J. Thomas, and H. Ziegler. 2008. “Visual Analytics: Scope and Challenges.” In Visual Data Mining: Theory, Techniques and Tools for Visual Analytics, edited by S. J. Simoff, M. H. Böhlen, and A. Mazeika, 76–90. Berlin, Heidelberg: Springer Berlin Heidelberg. https://link.springer.com/chapter/10.1007/978-3-540-71080-6_6
   Google Scholar
• Krüger, R., G. Simeonov, F. Beck, and T. Ertl. 2018. “Visual Interactive Map Matching.” Review Of. IEEE Transactions on Visualization and Computer Graphics 24 (6): 1881–1892. doi:10.1109/TVCG.2018.2816219.
   PubMed Web of Science ®Google Scholar
• Kveladze, I., and N. Agerholm. 2018. “Visual Analysis of Speed Bumps Using Floating Car Dataset.” Review Of. Journal of Location Based Services 12 (2): 119–139. doi:10.1080/17489725.2018.1521010.
   Web of Science ®Google Scholar
• Kveladze, I., M. J. Kraak, and C. P. J. M. van Elzakker. 2013. “A Methodological Framework for Researching the Usability of the Space-Time Cube.” Review Of. The Cartographic Journal 50 (3): 201–210. doi:10.1179/1743277413Y.0000000061.
   Web of Science ®Google Scholar
• Kveladze, I., M. J. Kraak, and C. P. J. M. van Elzakker. 2015. “The Space-time Cube as Part of a GeoVisual Analytics Environment to Support the Understanding of Movement Data.” Review Of. International Journal of Geographical Information Science 29 (11): 2001–2016. doi:10.1080/13658816.2015.1058386.
   Web of Science ®Google Scholar
• Kveladze, I., M. J. Kraak, and C. P. J. M. van Elzakker. 2017. “The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets.” In Advances in Cartography and GIScience, edited by ICACI 2017 M., 207−221, Cham: Springer International Publishing.
   Google Scholar
• Li, Y., and G. Fernie. 2010. “Pedestrian Behavior and Safety on a Two-stage Crossing with a Center Refuge Island and the Effect of Winter Weather on Pedestrian Compliance Rate.” Review Of. Accident Analysis & Prevention 42 (4): 1156–1163. doi:10.1016/j.aap.2010.01.004.
   PubMed Web of Science ®Google Scholar
• North, C., and B. Shneiderman. 1997. “A Taxonomy of Multiple Window Coordinations.” In Reports IfSRT, edited by Department of Computer Science, USA: University of Maryland.
   Google Scholar
• Peuquet, D. 1994. “It’s about Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems.” Review Of. In: Annals of the Association of American Geographers 84 (3): 441–461. doi:10.1111/j.1467-8306.1994.tb01869.x.
   Web of Science ®Google Scholar
• Peuquet, D. J. 2002. Representations of Space and Time. NY: Guilford Press.
   Google Scholar
• Ramos, L., L. Silva, M. Y. Santos, and J. M. Pires. 2015. “Detection of Road Accident Accumulation Zones with a Visual Analytics Approach.” Review Of. Procedia Computer Science 64: 969–976. doi:10.1016/j.procs.2015.08.615.
   Google Scholar
• Riveiro, M., M. Lebram, and M. Elmer. 2017. “Anomaly Detection for Road Traffic: A Visual Analytics Framework.” Review Of. IEEE Transactions on Intelligent Transportation Systems 18 (8): 2260–2270. doi:10.1109/tits.2017.2675710.
   Web of Science ®Google Scholar
• Robert, E. R. 2013. “Interactive Maps: What We Know and What We Need to Know.” Review Of. The Journal of Spatial Information Science 6: 59–115. doi:10.5311/JOSIS.2013.6.105.
   Google Scholar
• Robinson, A. C., U. Demšar, A. B. Moore, A. Buckley, B. Jiang, K. Field, M. J. Kraak, S. P. Camboim, and C. R. Sluter. 2017. “Geospatial Big Data and Cartography: Research Challenges and Opportunities for Making Maps that Matter.” Review Of. International Journal of Cartography 3 (sup1): 32–60. doi:10.1080/23729333.2016.1278151.
   Google Scholar
• Shneiderman, B. 1996. “The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations”. Paper presented at the the 1996 IEEE Symposium on Visual Languages, BouIder, Colorado, 3–6 September.
   Google Scholar
• Slingsby, A., J. Dykes, and J. Wood. 2008. “Using Treemaps for Variable Selection in Spatio-Temporal Visualisation.” Review Of. Information Visualization 7 (3–4): 210–224. doi:10.1057/palgrave.ivs.9500185.
   Web of Science ®Google Scholar
• Song, Y., and H. J. Miller. 2012. “Exploring Traffic Flow Databases Using Space-time Plots and Data Cubes.” Review Of. Transportation 39 (2): 215–234. doi:10.1007/s11116-011-9343-z.
   Web of Science ®Google Scholar
• Tanner, J. C. 1952. “Effect of Weather on Traffic Flow.” Review Of. Nature 169 (4290): 107. doi:10.1038/169107a0.
   Web of Science ®Google Scholar
• Taylor, M. A. P., P. W. Bonsall, and W. Young. 2000. Understanding Traffic Systems: Data Analysis and Presentation. 2nd ed. UK: Ashgate publishing .
   Google Scholar
• Tøfting, S., H. Lahrmann, N. Agerholm, B. Jørgensen, and L. V. Johannsen. 2014. “ITS Platform: Development of Intelligent Traffic”. Paper presented at the Proceedings – 10th Its European Congress, Helsinki, Finland.
   Google Scholar
• Tomaszewski, B., and A. MacEachren. 2012. “Geovisual Analytics to Support Crisis Management: Information Foraging for Geo-historical Context.” Review Of. Information Visualization 11 (4): 339–359. doi:10.1177/1473871612456122.
   Web of Science ®Google Scholar
• Tominski, C., H. Schumann, G. Andrienko, and N. Andrienko. 2012. “Stacking-Based Visualization of Trajectory Attribute Data.” Review Of. Visualization and Computer Graphics, IEEE Transactions On 18 (12): 2565–2574. doi:10.1109/tvcg.2012.265.
   PubMed Web of Science ®Google Scholar
• Tradisauskas, N., J. Juhl, H. Lahrmann, and C. S. Jensen. 2009. “Map Matching for Intelligent Speed Adaptation.” Review Of. IET Intelligent Transport Systems 3 (1): 57–66. doi:10.1049/iet-its:20070036.
   Web of Science ®Google Scholar
• van Elzakker, C. P. J. M., and K. Wealands. 2007. “Use and Users of Multimedia Cartography”. In Multimedia Cartographyedited by, W. Cartwright, M. Peterson, and G. Gartner, Second, pp. 487–504. Berlin: Springer. ISBN: 3-540-36650-4. doi: 10.1007/978-3-540-36651-5_34.
   Google Scholar
• Vanky, A. P., S. K. Verma, T. K. Courtney, P. Santi, and C. Ratti. 2017. “Effect of Weather on Pedestrian Trip Count and Duration: City-scale Evaluations Using Mobile Phone Application Data.” Review Of. Preventive Medicine Reports 8: 30–37. doi:10.1016/j.pmedr.2017.07.002.
   PubMedGoogle Scholar
• Vejdirektoratet. 2012. Håndbog i Trafikplanlægning i byer ANLÆG OG PLANLÆGNING. Denmak: Vejregler.
   Google Scholar
• Wang, Z., M. Lu, X. Yuan, J. Zhang, and H. V. D. Wetering. 2013. “Visual Traffic Jam Analysis Based on Trajectory Data.” Review Of. IEEE Transactions on Visualization and Computer Graphic 19 (12): 2159–2168. doi:10.1109/TVCG.2013.228.
   PubMed Web of Science ®Google Scholar