Vehicle trajectory reconstruction for intersections: an integrated wavelet transform and Savitzky-Golay filter approach

References

• Ahn, S., S. Vadlamani, and J. Laval. 2013. “A Method to Account for Non-Steady State Conditions in Measuring Traffic Hysteresis.” Transportation Research Part C: Emerging Technologies 34: 138–147. doi:10.1016/j.trc.2011.05.020.
   Web of Science ®Google Scholar
• Alqasrawi, Y., M. Azzeh, and Y. Elsheikh. 2022. “Locally Weighted Regression with Different Kernel Smoothers for Software Effort Estimation.” Science of Computer Programming 214. doi:10.1016/j.scico.2021.102744.
   Web of Science ®Google Scholar
• Barmpounakis, Emmanouil, and Nikolas Geroliminis. 2020. “On the new era of Urban Traffic Monitoring with Massive Drone Data: The pNEUMA Large-Scale Field Experiment.” Transportation Research Part C: Emerging Technologies 111: 50–71. doi:10.1016/j.trc.2019.11.023.
   Web of Science ®Google Scholar
• Bichiou, Youssef, and Hesham A Rakha. 2018. “Developing an Optimal Intersection Control System for Automated Connected Vehicles.” IEEE Transactions on Intelligent Transportation Systems 20 (5): 1908–1916. doi:10.1109/TITS.2018.2850335
   Web of Science ®Google Scholar
• Chen, B., Y. Wang, D. Wang, and W. H. K. Lam. 2019. “Understanding Travel Time Uncertainty Impacts on the Equity of Individual Accessibility.” Transportation Research Part D: Transport and Environment 75: 156–169. doi:10.1016/j.trd.2019.08.027.
   Web of Science ®Google Scholar
• Chen, P., L. Wei, F. Meng, and N. Zheng. 2021. “Vehicle Trajectory Reconstruction for Signalized Intersections: A Hybrid Approach Integrating Kalman Filtering and Variational Theory.” Transportmetrica B: Transport Dynamics 9 (1): 22–41. doi:10.1080/21680566.2020.1781707.
   Web of Science ®Google Scholar
• Dong, S., Y. Zhou, T. Chen, S. Li, Q. Gao, and B. Ran. 2021. “An Integrated Empirical Mode Decomposition and Butterworth Filter Based Vehicle Trajectory Reconstruction Method.” Physica A: Statistical Mechanics and its Applications 583: 126295. doi:10.1016/j.physa.2021.126295.
   Web of Science ®Google Scholar
• Fard, M. R., A. S. Mohaymany, and M. Shahri. 2017. “A new Methodology for Vehicle Trajectory Reconstruction Based on Wavelet Analysis.” Transportation Research Part C: Emerging Technologies 74: 150–167. doi:10.1016/j.trc.2016.11.010.
   Web of Science ®Google Scholar
• Fu, H., Y. Wang, X. Tang, N. Zheng, and N. Geroliminis. 2020. “Empirical Analysis of Large-Scale Multimodal Traffic with Multi-Sensor Data.” Transportation Research Part C: Emerging Technologies 118: 102725. doi:10.1016/j.trc.2020.102725.
   Web of Science ®Google Scholar
• Krajewski, R., J. Bock, L. Kloeker, and L. Eckstein. 2018. The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. Paper presented at the 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, HI, USA, 4-7 Nov. 2018.
   Google Scholar
• Liu, P., and W. D. Fan. 2021. “Exploring the Impact of Connected and Autonomous Vehicles on Mobility and Environment at Signalized Intersections Through Vehicle-to-Infrastructure (V2I) and Infrastructure-to-vehicle (I2V) Communications.” Transportation Planning and Technology 44 (2): 129–138. doi:10.1080/03081060.2020.1868088.
   Web of Science ®Google Scholar
• Ma, W., K. An, and H. K. Lo. 2016. “Multi-stage Stochastic Program to Optimize Signal Timings Under Coordinated Adaptive Control.” Transportation Research Part C: Emerging Technologies 72: 342–359. doi:10.1016/j.trc.2016.10.002.
   Web of Science ®Google Scholar
• Ma, W., and S. Qian. 2020. “Measuring and Reducing the Disequilibrium Levels of Dynamic Networks with Ride-Sourcing Vehicle Data.” Transportation Research Part C: Emerging Technologies 110: 222–246. doi:10.1016/j.trc.2019.11.001.
   Web of Science ®Google Scholar
• Mallat, S. G. 1989. “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation.” IEEE Transactions on Pattern Analysis & Machine Intelligence 11 (4): 674–693. doi:10.1109/34.192463
   Google Scholar
• MOHURD. 2012. Code for Design of Urban Road Engineering. Beijing: Ministry of Housing and Urban-Rural Development of the People's Republic of China. MOHURD.
   Google Scholar
• Montanino, M., and V. Punzo. 2015. “Trajectory Data Reconstruction and Simulation-Based Validation Against Macroscopic Traffic Patterns.” Transportation Research Part B: Methodological 80: 82–106. doi:10.1016/j.trb.2015.06.010.
   Web of Science ®Google Scholar
• Noh, B., and H. Yeo. 2022. “A Novel Method of Predictive Collision Risk Area Estimation for Proactive Pedestrian Accident Prevention System in Urban Surveillance Infrastructure.” Transportation Research Part C: Emerging Technologies 137: 103570. doi:10.1016/j.trc.2022.103570.
   Web of Science ®Google Scholar
• Pan, T., W. H. K. Lam, A. Sumalee, and R. Zhong. 2021. “Multiclass Multilane Model for Freeway Traffic Mixed with Connected Automated Vehicles and Regular Human-Piloted Vehicles.” Transportmetrica A: Transport Science 17 (1): 5–33. doi:10.1080/23249935.2019.1573858.
   Web of Science ®Google Scholar
• Park, M., Y. Kim, and H. Yeo. 2020. “Development of an Asymmetric Car-Following Model and Simulation Validation.” Ieee Transactions on Intelligent Transportation Systems 21 (8): 3513–3524. doi:10.1109/Tits.2019.2930320.
   Web of Science ®Google Scholar
• Punzo, V., and F. Simonelli. 2005. “Analysis and Comparison of Microscopic Traffic Flow Models with Real Traffic Microscopic Data.” Transportation Research Record 1934 (1): 53–63. doi:10.1177/0361198105193400106
   Google Scholar
• Rahman, M. A., M. A. Rashid, and M. Ahmad. 2019. “Selecting the Optimal Conditions of Savitzky-Golay Filter for fNIRS Signal.” Biocybernetics and Biomedical Engineering 39 (3): 624–637. doi:10.1016/j.bbe.2019.06.004.
   Web of Science ®Google Scholar
• Saifuzzaman, M., Z. Zheng, M. M. Haque, and S. Washington. 2017. “Understanding the Mechanism of Traffic Hysteresis and Traffic Oscillations Through the Change in Task Difficulty Level.” Transportation Research Part B: Methodological 105: 523–538. doi:10.1016/j.trb.2017.09.023.
   Web of Science ®Google Scholar
• Savitzky, Abraham, and Mje Golay. 1964. “Smoothing and Differentiation of Data by Simplified Least Squares Procedures.” Analytical Chemistry 36 (8): 1627–1639. doi:10.1021/ac60214a047
   Web of Science ®Google Scholar
• Shi, X., D. Zhao, H. Yao, X. Li, D. K. Hale, and A. Ghiasi. 2021. “Video-Based Trajectory Extraction with Deep Learning for High-Granularity Highway Simulation (HIGH-SIM).” Communications in Transportation Research 1 (1): 100014. doi:10.1016/j.commtr.2021.100014
   Google Scholar
• Tang, K., C. Tan, Y. Cao, J. Yao, and J. Sun. 2020. “A Tensor Decomposition Method for Cycle-Based Traffic Volume Estimation Using Sampled Vehicle Trajectories.” Transportation Research Part C: Emerging Technologies 118: 102739. doi:10.1016/j.trc.2020.102739.
   Web of Science ®Google Scholar
• Thiemann, C., M. Treiber, and A. Kesting. 2008. “Estimating Acceleration and Lane-Changing Dynamics from Next Generation Simulation Trajectory Data.” Transportation Research Record 2088 (1): 90–101. doi:10.3141/2088-10.
   Google Scholar
• van Beinum, A., H. Farah, F. Wegman, and S. Hoogendoorn. 2018. “Driving Behaviour at Motorway Ramps and Weaving Segments Based on Empirical Trajectory Data.” Transportation Research Part C-Emerging Technologies 92: 426–441. doi:10.1016/j.trc.2018.05.018.
   Web of Science ®Google Scholar
• Venthuruthiyil, S. P., and M. Chunchu. 2018. “Trajectory Reconstruction Using Locally Weighted Regression: A New Methodology to Identify the Optimum Window Size and Polynomial Order.” Transportmetrica A: Transport Science 14 (10): 881–900. doi:10.1080/23249935.2018.1449032.
   Web of Science ®Google Scholar
• Venthuruthiyil, S. P., and M. Chunchu. 2020. “Vehicle Path Reconstruction Using Recursively Ensembled Low-Pass Filter (RELP) and Adaptive tri-Cubic Kernel Smoother.” Transportation Research Part C: Emerging Technologies 120: 102847. doi:10.1016/j.trc.2020.102847.
   Web of Science ®Google Scholar
• Wang, C., C. Xu, and Y. Dai. 2019. “A Crash Prediction Method Based on Bivariate Extreme Value Theory and Video-Based Vehicle Trajectory Data.” Accident Analysis and Prevention 123: 365–373. doi:10.1016/j.aap.2018.12.013.
   PubMed Web of Science ®Google Scholar
• Wu, W., Y. Liu, W. Hao, G. A. Giannopoulos, and Y. J. Byon. 2022. “Autonomous Intersection Management with Pedestrians Crossing.” Transportation Research Part C: Emerging Technologies 135: 103521. doi:10.1016/j.trc.2021.103521.
   Web of Science ®Google Scholar
• Wu, W., Y. Liu, W. Liu, F. Zhang, D. Rey, and V. Dixit. 2019. “An Integrated Approach for Optimizing Left-Turn Forbiddance Decisions at Multiple Intersections.” Transportmetrica B: Transport Dynamics 7 (1): 1481–1504. doi:10.1080/21680566.2019.1631901.
   Web of Science ®Google Scholar
• Xie, K., K. Ozbay, H. Yan, and C. Li. 2019. “Mining Automatically Extracted Vehicle Trajectory Data for Proactive Safety Analytics.” Transportation Research Part C: Emerging Technologies 106: 61–72. doi:10.1016/j.trc.2019.07.004.
   Web of Science ®Google Scholar
• Yang, D., Y. Wu, F. Sun, J. Chen, D. Zhai, and C. Fu. 2021. “Freeway Accident Detection and Classification Based on the Multi-Vehicle Trajectory Data and Deep Learning Model.” Transportation Research Part C: Emerging Technologies 130: 103303. doi:10.1016/j.trc.2021.103303.
   Web of Science ®Google Scholar
• Yu, C., Y. Feng, H. Liu, W. Ma, and X. Yang. 2018. “Integrated Optimization of Traffic Signals and Vehicle Trajectories at Isolated Urban Intersections.” Transportation Research Part B: Methodological 112: 89–112. doi:10.1016/j.trb.2018.04.007.
   Web of Science ®Google Scholar
• Zhang, C., B. Chen, W. H. K. Lam, H. W. Ho, X. Shi, X. Yang, W. Ma, S. C. Wong, and A. H. F. Chow. 2022. “Vehicle re-Identification for Lane-Level Travel Time Estimations on Congested Urban Road Networks Using Video Images.” IEEE Transactions on Intelligent Transportation Systems, 1–17. doi:10.1109/tits.2021.3118206.
   Web of Science ®Google Scholar
• Zhang, Cheng, H. W. Ho, William H. K. Lam, Wei Ma, S. C. Wong, and Andy H. F. Chow. 2022. “Lane-based Estimation of Travel Time Distributions by Vehicle Type via Vehicle re-Identification Using Low-Resolution Video Images.” Journal of Intelligent Transportation Systems, 1–20. doi:10.1080/15472450.2022.2027767.
   Web of Science ®Google Scholar
• Zhang, W., G. Jordan, and V. Livshits. 2016. “Generating a Vehicle Trajectory Database from Time-Lapse Aerial Photography.” Transportation Research Record 2594 (1): 148–158. doi:10.3141/2594-18.
   Google Scholar
• Zhang, Y., Y. Zou, J. Tang, and J. Liang. 2022. “Long-Term Prediction for High-Resolution Lane-Changing Data Using Temporal Convolution Network.” Transportmetrica B: Transport Dynamics 10 (1): 849–863. doi:10.1080/21680566.2021.1950072.
   Web of Science ®Google Scholar
• Zhao, Jing, Victor L. Knoop, and Meng Wang. 2020. “Two-dimensional Vehicular Movement Modelling at Intersections Based on Optimal Control.” Transportation Research Part B: Methodological 138: 1–22. doi:10.1016/j.trb.2020.04.001
   Web of Science ®Google Scholar
• Zhao, Jing, Victor L. Knoop, and Meng Wang. 2022. “Microscopic Traffic Modeling Inside Intersections: Interactions Between Drivers.” Transportation Science, doi:10.1287/trsc.2022.1163.
   Web of Science ®Google Scholar
• Zhou, M., X. Qu, and X. Li. 2017. “A Recurrent Neural Network Based Microscopic Car Following Model to Predict Traffic Oscillation.” Transportation Research Part C: Emerging Technologies 84: 245–264. doi:10.1016/j.trc.2017.08.027.
   Web of Science ®Google Scholar