Kinematics-enabled lossless compression of freeway and arterial vehicle trajectories

References

• Alexiadis, V., Colyar, J., Halkias, J., Hranac, R., & McHale, G. (2004). The next generation simulation program. ITE Journal, 74(8), 22–26.
   Web of Science ®Google Scholar
• Bellman, R. (1961). On the approximation of curves by line segments using dynamic programming. Communications of the ACM, 4(6), 284. doi:10.1145/366573.366611
   Web of Science ®Google Scholar
• Chen, C., Li, L., Hu, J., & Geng, C. (2010). Calibration of MITSIM and IDM car-following model based on NGSIM trajectory datasets. In Proceedings of the 2010 IEEE international conference on vehicle electronics and safety (ICVES), QingDao, China (pp. 48–53).
   Google Scholar
• Coifman, B., & Li, L. (2017). A critical evaluation of the Next Generation Simulation (NGSIM) vehicle trajectory dataset. Transportation Research Part B, 105, 362–377. doi:10.1016/j.trb.2017.09.018
   Google Scholar
• Douglas, D., & Peucker, T. (1973). Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica, 10(2), 112–122.
   Google Scholar
• Fard, M. R., Mohaymany, A. S., & Shahri, M. (2017). A new methodology for vehicle trajectory reconstruction based on wavelet analysis. Transportation Research Part C, 74, 150–167. doi:10.1016/j.trc.2016.11.010
   Web of Science ®Google Scholar
• FHWA (2016a). Next Generation Simulation (NGSIM) US Route 101 Dataset. U.S. Department of Transportation Intelligent Transportation Systems Joint Program Office (JPO). Retrieved from https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj
   Google Scholar
• FHWA (2016b). Next Generation Simulation (NGSIM) Interstate 80 Freeway Dataset. U.S. Department of Transportation Intelligent Transportation Systems Joint Program Office (JPO). Retrieved from https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj
   Google Scholar
• FHWA (2016c). Next Generation Simulation (NGSIM) Lankershim Boulevard Dataset. U.S. Department of Transportation Intelligent Transportation Systems Joint Program Office (JPO). Retrieved from https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj
   Google Scholar
• FHWA (2016d). Next Generation Simulation (NGSIM) Peachtree Street Dataset. U.S. Department of Transportation Intelligent Transportation Systems Joint Program Office (JPO). Retrieved from https://data.transportation.gov/Automobiles/Next-Generation-Simulation-NGSIM-Vehicle-Trajector/8ect-6jqj
   Google Scholar
• Kovvali, V., Alexiadis, V., & Zhang, L. (2007). Video-based vehicle trajectory data collection. In Proceedings of the 86th annual meeting of the transportation research board. Washington, DC: National Academy of Science.
   Google Scholar
• Langdon, G. G. Jr.(1984). An introduction to arithmetic coding. IBM Journal of Research and Development, 28(2), 135–149. doi:10.1147/rd.282.0135
   Web of Science ®Google Scholar
• LeClercq, L., Chiabaut, N., Laval, J., & Buisson, C. (2007). Relaxation phenomenon after changing lanes: An experimental validation with the NGSIM dataset. Transportation Research Record: Journal of the Transportation Research Board, 1999(1), 79–85. doi:10.3141/1999-09
   Google Scholar
• Li, G., Sun, L., Pan, Y., & Yu, Y. (2016). Analysis of merging behavior parameters using NGSIM data sets. In Proceedings of the 16th COTA international conference of transportation professionals, Shanghai, China (pp. 78–88).
   Google Scholar
• Lin, C.-Y., Chen, H.-C., Chen, Y.-Y., Lee, W.-C., & Chen, L.-J. (2010). Compressing trajectories using inter-frame coding (Technical Report No. TR-IIS-10-007). Taipei: Institute of Information Science, Academia Sinica.
   Google Scholar
• Lingxiao, Y., Xiaomei, Z., & Jianfeng, Z. (2011). Correlations among various parameters in car-following models with NGSIM trajectory data. Applied Mechanics and Materials, 66–68, 179–184.
   Google Scholar
• Liu, K., Li, Y., Dai, J., Shang, S., & Zheng, K. (2014). Compressing large scale urban trajectory data. In Proceedings of the 4th international workshop on cloud data and platforms (CloudDP ’14), Amsterdam, The Netherlands (pp. 3–8).
   Google Scholar
• Liu, X. C., Taylor, J., Porter, R. J., & Wei, R. (2018). Using trajectory data to explore roadway characterization for bikeshare network. Journal of Intelligent Transportation Systems, 22(6), 530–546. doi:10.1080/15472450.2018.1444484
   Web of Science ®Google Scholar
• Lovell, D. J. (2018). Lossless compression of all vehicle trajectories in a common roadway segment. Computer-Aided Civil and Infrastructure Engineering, 33(6), 481–497. doi:10.1111/mice.12354
   Web of Science ®Google Scholar
• Lu, X. Y., Varaiya, P., & Horowitz, R. (2009). Fundamental diagram modelling and analysis based NGSIM data. IFAC Proceedings Volumes, 42(15), 367–374. doi:10.3182/20090902-3-US-2007.0068
   Google Scholar
• Montanino, M., & Punzo, V. (2013). Making NGSIM data useable for studies on traffic flow theory: Multistep method for vehicle trajectory reconstruction. Transportation Research Record: Journal of the Transportation Research Board, 2390(1), 99–111. doi:10.3141/2390-11
   Google Scholar
• Montanino, M., & Punzo, V. (2015). Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns. Transportation Research Part B, 80, 82–106. doi:10.1016/j.trb.2015.06.010
   Google Scholar
• Muckell, J., Olsen, P. W., Jr., Hwang, J.-H., Lawson, C. T., & Ravi, S. S. (2014). Compression of trajectory data: A comprehensive evaluation and new approach. GeoInformatica, 18(3), 435–460. doi:10.1007/s10707-013-0184-0
   Web of Science ®Google Scholar
• Punzo, V., Borzacchiello, M. T., & Ciuffo, B. (2011). On the assessment of vehicle trajectory data accuracy and application to the Next Generation Simulation (NGSIM) program data. Transportation Research Part C, 19(6), 1243–1262. doi:10.1016/j.trc.2010.12.007
   Web of Science ®Google Scholar
• Said, A. (2003). Introduction to arithmetic coding – theory and practice. In Sayood, K. (Ed.), Lossless compression handbook. San Diego, CA: Academic Press.
   Google Scholar
• Stone, H. (1961). Approximations of curves by line segments. Mathematics of Computation, 15(73), 40–47. doi:10.1090/S0025-5718-1961-0119390-6
   Google Scholar
• Sun, P., Xia, S., Yuan, G., & Li, D. (2016). An overview of moving object trajectory compression algorithms. Mathematical Problems in Engineering, 2016, 1–13. doi:10.1155/2016/6587309
   Web of Science ®Google Scholar
• Thiemann, C., Treiber, M., & Kesting, A. (2008). Estimating acceleration and lane-changing dynamics from Next Generation Simulation trajectory data. Transportation Research Record: Journal of the Transportation Research Board, 2088(1), 90–101. doi:10.3141/2088-10
   Google Scholar
• Toledo, T., Koutsopoulos, H. N., & Ahmed, K. I. (2007). Estimation of vehicle trajectories with locally weighted regression. Transportation Research Record: Journal of the Transportation Research Board, 1999(1), 161–169. doi:10.3141/1999-17
   Web of Science ®Google Scholar
• Wandelt, S., & Sun, X. (2015). Efficient compression of 4D-trajectory data in air traffic management. Journal of Intelligent Transportation Systems, 16(2), 844–853.
   Google Scholar
• Wandelt, S., Sun, X., & Leser, U. (2018). Column-wise compression of open relational data. Information Sciences, 457–458, 48–61. doi:10.1016/j.ins.2018.04.074.
   Web of Science ®Google Scholar