Visual analysis of speed bumps using floating car dataset

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.” Transportation Research Part F: Traffic Psychology and Behaviour 46 (Part B): 263–270. doi:10.1016/j.trf.2016.06.022.
   Web of Science ®Google Scholar
• Ahas, R., A. Aasa, Y. Yuan, M. Raubal, Z. Smoreda, Y. Liu, C. Ziemlicki, M. Tiru, and M. Zook. 2015. “Everyday Space–Time Geographies: Using Mobile Phone-Based Sensor Data to Monitor Urban Activity in Harbin, Paris, and Tallinn.” International Journal of Geographical Information Science 29 (11): 2017–2039. doi:10.1080/13658816.2015.1063151.
   Web of Science ®Google Scholar
• Ahn, K., and H. Rakha. 2009. “A Field Evaluation Case Study of the Environmental and Energy Impacts of Traffic Calming.” Transportation Research Part D: Transport and Environment 14 (6): 411–424. doi:10.1016/j.trd.2009.01.007.
   Web of Science ®Google Scholar
• Andrienko, G., and N. Andrienko. 2008. “Spatio-Temporal Aggregation for Visual Analysis of Movements.” In 2008 IEEE Symposium on Visual Analytics Science and Technology (VAST), 51–58. Washington, DC: IEEE Computer Society. doi: 10.1109/VAST.2008.4677356
   Google Scholar
• Andrienko, G., N. Andrienko, U. Demsar, D. Dransch, J. Dykes, S. I. Fabrikant, M. Jern, M. J. Kraak, H. Schumann, and C. Tominski. 2010. “Space, Time and Visual Analytics.” International Journal of Geographical Information Science 24 (10): 1577–1600. doi:10.1080/13658816.2010.508043.
   Web of Science ®Google Scholar
• Andrienko, G., N. Andrienko, C. Hurter, S. Rinzivillo, and S. Wrobel. 2011. “From Movement Tracks through Events to Places: Extracting and Characterizing Significant Places from Mobility Data.” In 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), 161–170. Washington, DC: IEEE Computer Society. doi: 10.1109/VAST.2011.6102454
   Google Scholar
• Andrienko, G., N. Andrienko, H. Schumann, and C. Tominski. 2014. “Visualization of Trajectory Attributes in Space-Time Cube and Trajectory Wall.” In Cartography from Pole to Pole, edited by M. Buchroithner, N. Prechtel, and D. Burghardt, 157–163. Berlin Heidelberg: Springer.
   Google Scholar
• Andrienko, N., G. Andrienko, and S. Rinzivillo. 2015. “Exploiting Spatial Abstraction in Predictive Analytics of Vehicle Traffic.” ISPRS International Journal of Geo-Information 4 (2): 591–606. doi:10.3390/ijgi4020591.
   Web of Science ®Google Scholar
• Antić, B., D. Pešić, M. Vujanić, and K. Lipovac. 2013. “The Influence of Speed Bumps Heights to the Decrease of the Vehicle Speed – Belgrade Experience.” Safety Science 57: 303–312. doi:10.1016/j.ssci.2013.03.008.
   Web of Science ®Google Scholar
• Davies, H. W., J. J. Vlaanderen, S. B. Henderson, and M. Brauer. 2009. “Correlation between Co-Exposures to Noise and Air Pollution from Traffic Sources.” Occupational and Environmental Medicine 66 (5): 347–350. doi:10.1136/oem.2008.041764.
   PubMed Web of Science ®Google Scholar
• Dewulf, B., T. Neutens, M. Vanlommel, S. Logghe, P. De Maeyer, F. Witlox, Y. De Weerdt, and N. Van de Weghe. 2015. “Examining Commuting Patterns Using Floating Car Data and Circular Statistics: Exploring the Use of New Methods and Visualizations to Study Travel Times.” Journal of Transport Geography 48: 41–51. doi:10.1016/j.jtrangeo.2015.08.006.
   Web of Science ®Google Scholar
• Dixon, M. A., J. A. Alvarez, J. Rodriguez, and J. A. Jacko. 1997. “The Effect of Speed Reducing Peripherals on Motorists’ Behavior at Pedestrian Crossings.” Computers & Industrial Engineering 33 (1–2): 205–208. doi:10.1016/s0360-8352(97)00075-2.
   Web of Science ®Google Scholar
• Dorling, D. 1993. “From Computer Cartography to Spatial Visualization: A New Cartogram Algorithm.” In Proceedings of the Eleventh International Symposium on Computer-assisted Cartography (Auto-Carto 11), 208–217. Bethesda, Md. : American Congress on Surveying and Mapping and the American Society for Photogrammetry and Remote Sensing.
   Google Scholar
• Dorling, D. 1996. Area Cartograms: Their Use and Creation. Vol. 59 of Concepts and Techniques in Modern Geography. Norwich: Environmental Publications: University of East Anglia.
   Google Scholar
• Duan, Z., L. Liu, and W. Sun. 2009. “ Traffic Congestion Analysis of Shanghai Road Network Based on Floating Car Data.” In Proceedings of the Second International Conference on Transportation Engineering, edited by Q. Peng, K. C. P. Wang, Y. Qiu, Y. Pu, X. Luo, and B. Shuai, 2731–2736. Reston, VA: American Society of Civil Engineers. doi:10.1061/41039(345)450
   Google Scholar
• Eksler, V., M. Popolizio, and R. Allsop (2009). How Far from Zero? Benchmarking of Road Safety Performance in the Nordic Countries. (Report No. 9789081467506). Brussels: European Transport Safety Council.
   Google Scholar
• Elvik, R. 2001. “Area-Wide Urban Traffic Calming Schemes: A Meta-Analysis of Safety Effects.” Accident; Analysis and Prevention 33 (3): 327–336. doi:10.1016/S0001-4575(00)00046-4.
   PubMed Web of Science ®Google Scholar
• Elvik, R., A. Hoye, T. Vaa, and M. Sorensen. 2009. The Handbook of Road Safety Measures. Bingley: Emerald Group Publishing Limited.
   Google Scholar
• Environmental Agency. (2012). “Noise Mapping.” http://miljoegis.mim.dk/
   Google Scholar
• Ewing, R. 2001. “Impacts of Traffic Calming. Surface Transportation Policy Project.” Transportation Quarterly 55 (1): 33–46.
   Google Scholar
• Feldman, L. P., and J. Hornik. 1981. “The Use of Time: An Integrated Conceptual Model.” Journal of Consumer Research 7 (4): 407–419. doi:10.1086/208831.
   Web of Science ®Google Scholar
• Fredrikson, A., C. North, C. Plaisant, and B. Shneiderman. 1999. “Temporal, Geographical and Categorical Aggregations Viewed through Coordinated Displays: A Case Study with Highway Incident Data.” In Conference on Information and Knowledge Management (CIKM99), 26-34. New York, NY: ACM.
   Google Scholar
• García, A., A. J. Torres, M. A. Romero, and A. T. Moreno. 2011. “Traffic Microsimulation Study to Evaluate the Effect of Type and Spacing of Traffic Calming Devices on Capacity.” Procedia – Social and Behavioral Sciences 16 (Suppl C): 270–281. doi:10.1016/j.sbspro.2011.04.449.
   Google Scholar
• Goldberg, M. S., R. T. Burnett, and J. R. Brook. 2008. “Counterpoint: Time-Series Studies of Acute Health Events and Environmental Conditions are Not Confounded by Personal Risk Factors.” Regulatory Toxicology and Pharmacology 51 (2): 141–150. doi:10.1016/j.yrtph.2008.03.006.
   PubMed Web of Science ®Google Scholar
• Gonzalo-Orden, H., M. Rojo, H. Pérez-Acebo, and A. Linares. 2016. “Traffic Calming Measures and Their Effect on the Variation of Speed.” Transportation Research Procedia 18 (Suppl C): 349–356. doi:10.1016/j.trpro.2016.12.047.
   Google Scholar
• Grana, A., T. Giuffrè, and M. Guerrieri. 2010. “Exploring Effects of Area-Wide Traffic Calming Measures on Urban Road Sustainable Safety.” Journal of Sustainable Development 3 (4): 38–49. doi:10.5539/jsd.v3n4p38.
   Google Scholar
• Gühnemann, A., R. P. Schäfer, K. U. Thiessenhusen, and P. Wagner. 2004. “Monitoring Traffic and Emissions by Floating Car Data.” In Institute of Transport Studies Working Paper, ITS-WP-04-07. London: RAILTRACK PLC.
   Google Scholar
• Hägerstrand, T. 1970. “What about People in Regional Science?” Papers of the Regional Science Association 24 (1): 6–21. doi:10.1007/bf01936872.
   Google Scholar
• Jensen, S. S. 1995. “Driving Patterns and Emissions from Different Types of Roads.” Science of the Total Environment 169 (1–3): 123–128. doi:10.1016/0048-9697(95)04640-m.
   Web of Science ®Google Scholar
• Johansson, C., P. Rosander, and L. Leden. 2011. “Distance between Speed Humps and Pedestrian Crossings: Does It Matter?” Accident; Analysis and Prevention 43 (5): 1846–1851. doi:10.1016/j.aap.2011.04.020.
   PubMed Web of Science ®Google Scholar
• Keim, D., G. Andrienko, J.-D. Fekete, C. Görg, J. Kohlhammer, and G. Melançon. 2008. “Visual Analytics: Definition, Process, and Challenges.” In Information Visualization, edited by A. Kerren, A. T. Stasko, J. D. Fekete, and C. North, 154–175. Berlin-Heidelberg: Springer.
   Google Scholar
• Keim, D. A., F. Mansmann, J. Schneidewind, J. Thomas, and H. Ziegler. 2008. “Visual Analytics: Scope and Challenges.” In Visual Data Mining, edited by S. Simoff, M. Böhlen, and A. Mazeika, Vol. 4404, 76–90. Berlin, Heidelberg: Springer.
   Google Scholar
• Kelly, F. J., and J. C. Fussell. 2015. “Air Pollution and Public Health: Emerging Hazards and Improved Understanding of Risk.” Environmental Geochemistry and Health 37 (4): 631–649. doi:10.1007/s10653-015-9720-1.
   PubMed Web of Science ®Google Scholar
• Khademi, A., S. A. Mirzapour, S. S. Hosseini, and N. Mohd Yusof. 2014. “The Best Location for Speed Bump Installation Using Taguchi and Classical Design of Experiments.” Quality Engineering 26 (4): 392–403. doi:10.1080/08982112.2013.858748.
   Web of Science ®Google Scholar
• Kim, K., K. Oh, Y. K. Lee, S. Kim, and J.-Y. Jung. 2014. “An Analysis on Movement Patterns between Zones Using Smart Card Data in Subway Networks.” International Journal of Geographical Information Science 28 (9): 1781–1801. doi:10.1080/13658816.2014.898768.
   Web of Science ®Google Scholar
• Lahrmann, H., N. Agerholm, N. Tradisauskas, K. K. Berthelsen, and L. Harms. 2012. “Pay as You Speed, ISA with Incentive for Not Speeding: Results and Interpretation of Speed Data.” Accident; Analysis and Prevention 48 (Suppl C): 17–28. doi:10.1016/j.aap.2011.03.015.
   PubMed Web of Science ®Google Scholar
• Leden, L., P. E. Wikstrom, P. Garder, and P. Rosander. 2006. “Safety and Accessibility Effects of Code Modifications and Traffic Calming of an Arterial Road.” Accident Analysis and Prevention 38 (3): 455–461. doi:10.1016/j.aap.2005.11.002.
   PubMed Web of Science ®Google Scholar
• Li, D., B. Fu, Y. Wang, G. Lu, Y. Berezin, H. E. Stanley, and S. Havlin. 2015. “Percolation Transition in Dynamical Traffic Network with Evolving Critical Bottlenecks.” Proceedings of the National Academy of Sciences of the United States of America 112 (3): 669–672. doi:10.1073/pnas.1419185112.
   PubMed Web of Science ®Google Scholar
• Liu, X., L. Gong, Y. Gong, and Y. Liu. 2015. “Revealing Travel Patterns and City Structure with Taxi Trip Data.” Journal of Transport Geography 43: 78–90. doi:10.1016/j.jtrangeo.2015.01.016.
   Web of Science ®Google Scholar
• Liu, Y., F. Wang, Y. Xiao, and S. Gao. 2012. “Urban Land Uses and Traffic ‘Source-Sink Areas’: Evidence from GPS-enabled Taxi Data in Shanghai.” Landscape and Urban Planning 106 (1): 73–87. doi:10.1016/j.landurbplan.2012.02.012.
   Web of Science ®Google Scholar
• Ma, S., Y. Zheng, and O. Wolfson. 2015. “Real-Time City-Scale Taxi Ridesharing.” IEEE Transactions on Knowledge and Data Engineering 27 (7): 1782–1795. doi:10.1109/tkde.2014.2334313.
   Web of Science ®Google Scholar
• Moreno, A. T., and A. Garcia. 2013. “Use of Speed Profile as Surrogate Measure: Effect of Traffic Calming Devices on Crosstown Road Safety Performance.” Accident Analysis and Prevention 61 (Suppl C): 23–32. doi:10.1016/j.aap.2012.10.013.
   PubMed Web of Science ®Google Scholar
• Nilsson, G. (2004). “Traffic Safety Dimensions and the Power Model to Describe the Effect of Speed on Safety.” PhD diss., Lund University of Technology and Society, Lund, Sweden.
   Google Scholar
• Pau, M., and S. Angius. 2001. “Do Speed Bumps Really Decrease Traffic Speed? An Italian Experience.” Accident Analysis & Prevention 33 (5): 585–597. doi:10.1016/s0001-4575(00)00070-1.
   PubMed Web of Science ®Google Scholar
• Pei, T., S. Sobolevsky, C. Ratti, S.-L. Shaw, T. Li, and C. Zhou. 2014. “A New Insight into Land Use Classification Based on Aggregated Mobile Phone Data.” International Journal of Geographical Information Science 28 (9): 1988–2007. doi:10.1080/13658816.2014.913794.
   Web of Science ®Google Scholar
• Pitchika, A., R. Hampel, K. Wolf, U. Kraus, J. Cyrys, W. Babisch, A. Peters, and A. Schneider. 2017. “Long-Term Associations of Modeled and Self-Reported Measures of Exposure to Air Pollution and Noise at Residence on Prevalent Hypertension and Blood Pressure.” The Science of the Total Environment 593–594 (Suppl C): 337–346. doi:10.1016/j.scitotenv.2017.03.156.
   PubMed Web of Science ®Google Scholar
• Rahman, F., A. Kojima, and H. Kubota. 2009. “Investigation on North American Traffic Calming Device Selection Practices.” IATSS Research 33 (2): 105–119. doi:10.1016/s0386-1112(14)60249-1.
   Google Scholar
• Rashidi, M., I. Batros, T. K. Madsen, M. T. Riaz, and T. Paulin. 2012. “Placement of Road Side Units for Floating Car Data Collection in Highway Scenario.” In 2012 IV International Congress on Ultra Modern Telecommunications and Control Systems, 114–118. Washington, DC: IEEE Computer Society. doi:10.1109/ICUMT.2012.6459649
   Google Scholar
• Ross, Z., I. Kheirbek, J. E. Clougherty, K. Ito, T. Matte, S. Markowitz, and H. Eisl. 2011. “Noise, Air Pollutants and Traffic: Continuous Measurement and Correlation at a High-Traffic Location in New York City.” Environmental Research 111 (8): 1054–1063. doi:10.1016/j.envres.2011.09.004.
   PubMed Web of Science ®Google Scholar
• Samet, J. M. 2007. “Traffic, Air Pollution, and Health.” Inhalation Toxicology 19 (12): 1021–1027. doi:10.1080/08958370701533541.
   PubMed Web of Science ®Google Scholar
• Shneiderman, B. 1996. “The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations.” In Proceedings of the 1996 IEEE Symposium on Visual Languages, 336–343. Los Alamitos, CA: IEEE Computer Society. doi:10.1109/VL.1996.545307
   Google Scholar
• Silm, S., and R. Ahas. 2010. “The Seasonal Variability of Population in Estonian Municipalities.” Environment and Planning A 42 (10): 2527–2546. doi:10.1068/a43139.
   Web of Science ®Google Scholar
• Silva, S. F., and T. Catarci. 2000. “Visualization of Linear Time-Oriented Data: A Survey.” In Proceedings of the First International Conference on Web Information Systems Engineering – Volume 1, edited by Q. Li, Z. M. Ozsoyoglu, R. Wagner, Y. Kambayashi, and Y. Zhang, 310–323. Los Alamitos, CA: IEEE Computer Society. doi:10.1109/WISE.2000.882407
   Google Scholar
• Tetreault, L. F., S. Perron, and A. Smargiassi. 2013. “Cardiovascular Health, Traffic-Related Air Pollution and Noise: Are Associations Mutually Confounded? A Systematic Review.” International Journal of Public Health 58 (5): 649–666. doi:10.1007/s00038-013-0489-7.
   PubMed Web of Science ®Google Scholar
• Tiedong, W., and H. Jingjing. 2014. “Applying Floating Car Data in Traffic Monitoring.” In 2014 IEEE International Conference on Control Science and Systems Engineering, 96–99. Los Alamitos, CA: IEEE Computer Society. doi:10.1109/CCSSE.2014.7224516.
   Google Scholar
• Tominski, C., H. Schumann, G. Andrienko, and N. Andrienko. 2012. “Stacking-Based Visualization of Trajectory Attribute Data.” IEEE Transactions on Visualization and Computer Graphics 18 (12): 2565–2574. doi:10.1109/TVCG.2012.265.
   PubMed Web of Science ®Google Scholar
• Tonne, C., J. I. Halonen, S. D. Beevers, D. Dajnak, J. Gulliver, F. J. Kelly, P. Wilkinson, and H. R. Anderson. 2016. “Long-Term Traffic Air and Noise Pollution in Relation to Mortality and Hospital Readmission among Myocardial Infarction Survivors.” International Journal of Hygiene and Environmental Health 219 (1): 72–78. doi:10.1016/j.ijheh.2015.09.003.
   PubMed Web of Science ®Google Scholar
• TradišAuskas, N., J. Juhl, H. Lahrmann, and C. S. Jensen. 2009. “Map Matching for Intelligent Speed Adaptation.” IET Intelligent Transport Systems 3 (1): 57–66. doi:10.1049/iet-its:20070036.
   Web of Science ®Google Scholar
• Tyner, J. A. 2010. “Cartograms and Diagrams.” In Principles of Map Design, 189–199. New York: Guilford Press.
   Google Scholar
• Wang, T., T. Fang, J. Han, and J. Wu. 2010. “Traffic Monitoring Using Floating Car Data in Hefei.” In 2010 International Symposium on Intelligence Information Processing and Trusted Computing, 122–124. Washington, DC: IEEE Computer Society.
   Google Scholar
• Wang, Z., T. Ye, M. Lu, X. Yuan, H. Qu, J. Yuan, and Q. Wu. 2014. “Visual Exploration of Sparse Traffic Trajectory Data.” IEEE Transactions on Visualization and Computer Graphics 20 (12): 1813–1822.
   Google Scholar
• Watt, G. R. (1973). Road Humps for the Control of Vehicle Speeds (Report No. NLR59 R & D Rpt). The Hague, Netherlands: R. D. T. C. ANWBhttps://trid.trb.org/view/139512.
   Google Scholar
• World Health Organization. 2005. Health Effects of Transport-Related Air Pollution. Copenhagen: WHO Regional Office for Europe.
   Google Scholar
• Xu, L., Y. Yue, and Q. Li. 2013. “Identifying Urban Traffic Congestion Pattern from Historical Floating Car Data.” Procedia – Social and Behavioral Sciences 96: 2084–2095. doi:10.1016/j.sbspro.2013.08.235.
   Google Scholar
• Yannis, G., A. Kondyli, and X. Georgopoulou. 2014. “Investigation of the Impact of Low Cost Traffic Engineering Measures on Road Safety in Urban Areas.” International Journal of Injury Control and Safety Promotion 21 (2): 181–189. doi:10.1080/17457300.2013.796387.
   PubMed Web of Science ®Google Scholar
• Zein, S., E. Geddes, S. Hemsing, and M. Johnson. 1997. “Safety Benefits of Traffic Calming.” Transportation Research Record: Journal of the Transportation Research Board 1578: 3–10. doi:10.3141/1578-01.
   Google Scholar
• Zheng, Y., F. Liu, and H.-P. Hsieh. 2013. “U-Air: When Urban Air Quality Inference Meets Big Data.” In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining – KDD‘13, edited by R. Ghani, T. E. Senator, P. Bradley, R. Parekh, and J. He, 1436-1444. New York, NY: ACM.
   Google Scholar