Inference of HDVs real-time locations in mixed autonomous traffic flow scenario

References

• Ambühl, L., A. Loder, M. Menendez, and K. W. Axhausen. 2016. “Empirical Macroscopic Fundamental Diagrams: New Insights from Loop Detector and Floating Car Data.” In The 96th Annual Meeting of the Transportation Research Board. Washington, DC. doi:10/gk2383.
   Google Scholar
• Awal, T., L. Kulik, and K. Ramamohanrao. 2013. “A K-Leader Fuel-Efficient Traffic Model.” In 2013 IEEE Intelligent Vehicles Symposium (IV), 1014–1021. Gold Coast City: IEEE. doi:10/gk26rf.
   Google Scholar
• Balico, L. N., A. A. F. Loureiro, E. F. Nakamura, R. S. Barreto, R. W. Pazzi, and H. A. B. F. Oliveira. 2018. “Localization Prediction in Vehicular Ad Hoc Networks.” IEEE Communications Surveys & Tutorials 20 (4): 2784–2803. doi:10.1109/COMST.2018.2841901.
   Web of Science ®Google Scholar
• Bekiaris-Liberis, N., C. Roncoli, and M. Papageorgiou. 2016. “Highway Traffic State Estimation with Mixed Connected and Conventional Vehicles.” IEEE Transactions on Intelligent Transportation Systems 17 (12): 3484–3497. doi:10.1109/TITS.2016.2552639.
   Web of Science ®Google Scholar
• Challa, S., M. R. Morelande, D. Mušicki, and R. J. Evans. 2011. Fundamentals of Object Tracking. Cambridge: Cambridge University Press.
   Google Scholar
• Chen, J., Z. Shi, and Y. Hu. 2012. “Stabilization Analysis of a Multiple Look-ahead Model with Driver Reaction Delays.” International Journal of Modern Physics C 23 (6): 1250048. doi:10.1142/S0129183112500489.
   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
• Gingerich, K., H. Maoh, and W. Anderson. 2016. “Classifying the Purpose of Stopped Truck Events: An Application of Entropy to GPS Data.” Transportation Research Part C: Emerging Technologies 64 (March): 17–27. doi:10.1016/j.trc.2016.01.002.
   Google Scholar
• Himmelsbach, M., A. Mueller, T. Lüttel, and H. J. Wünsche. 2008. “LIDAR-based 3D Object Perception.” Proceedings of 1st International Workshop on Cognition for Technical Systems.
   Google Scholar
• Keane, R., and H. Oliver Gao. 2021. “Fast Calibration of Car-following Models to Trajectory Data Using the Adjoint Method.” Transportation Science 55 (3): 592–615. doi:10.1287/trsc.2020.1027.
   Web of Science ®Google Scholar
• Khan, S. M., K. C. Dey, and M. Chowdhury. 2017. “Real-time Traffic State Estimation with Connected Vehicles.” IEEE Transactions on Intelligent Transportation Systems 18 (7): 1687–1699. doi:10.1109/TITS.2017.2658664.
   Web of Science ®Google Scholar
• Li, L., X. (Micheal) Chen, and L. Zhang. 2016. “A Global Optimization Algorithm for Trajectory Data Based Car-following Model Calibration.” Transportation Research Part C: Emerging Technologies 68 (July): 311–332. doi:10.1016/j.trc.2016.04.011.
   Google Scholar
• Liu, W., and Y. Shoji. 2019. “Edge-assisted Vehicle Mobility Prediction to Support V2X Communications.” IEEE Transactions on Vehicular Technology 68 (10): 10227–10238. doi:10.1109/TVT.2019.2937825.
   Web of Science ®Google Scholar
• Miyajima, C., and K. Takeda. 2016. “Driver-behavior Modeling Using On-Road Driving Data: A New Application for Behavior Signal Processing.” IEEE Signal Processing Magazine 33 (6): 14–21. doi:10.1109/MSP.2016.2602377.
   Web of Science ®Google Scholar
• Papadopoulou, S., C. Roncoli, N. Bekiaris-Liberis, I. Papamichail, and M. Papageorgiou. 2018. “Microscopic Simulation-based Validation of a Per-Lane Traffic State Estimation Scheme for Highways with Connected Vehicles.” Transportation Research Part C: Emerging Technologies 86 (January): 441–452. doi:10.1016/j.trc.2017.11.012.
   Google Scholar
• Petrovskaya, A., and S. Thrun. 2009. “Model Based Vehicle Detection and Tracking for Autonomous Urban Driving.” Autonomous Robots 26 (2–3): 123–139. doi:10.1007/s10514-009-9115-1.
   Web of Science ®Google Scholar
• Punzo, V., M. Teresa Borzacchiello, and B. Ciuffo. 2011. “On the Assessment of Vehicle Trajectory Data Accuracy and Application to the Next Generation SIMulation (NGSIM) Program Data.” Transportation Research Part C: Emerging Technologies 19 (6): 1243–1262. doi:10.1016/j.trc.2010.12.007.
   Web of Science ®Google Scholar
• Sanders, C., and Y. Wang. 2020. “Localizing Spoofing Attacks on Vehicular GPS Using Vehicle-to-Vehicle Communications.” IEEE Transactions on Vehicular Technology 69 (12): 15656–15667. doi:10.1109/TVT.2020.3031576.
   Web of Science ®Google Scholar
• Sharath, M. N., and N. R. Velaga. 2020. “Enhanced Intelligent Driver Model for Two-dimensional Motion Planning in Mixed Traffic.” Transportation Research Part C: Emerging Technologies 120 (November): 102780. doi:10.1016/j.trc.2020.102780.
   Google Scholar
• Szeliski, Richard. 2010. Computer Vision: Algorithms and Applications. Berlin: Springer Science & Business Media.
   Google Scholar
• Tang, K., S. Zhu, Y. Xu, and F. Wang. 2016. “Modeling Drivers’ Dynamic Decision-making Behavior During the Phase Transition Period: An Analytical Approach Based on Hidden Markov Model Theory.” IEEE Transactions on Intelligent Transportation Systems 17 (1): 206–214. doi:10.1109/TITS.2015.2462738.
   Web of Science ®Google Scholar
• Wang, J., H. Yan, Z. Feng, C. Jiang, H. Zhang, and Victor C. M. Leung. 2018. “Reliable Traffic Density Estimation in Vehicular Network.” IEEE Transactions on Vehicular Technology 67 (7): 6424–6437. doi:10.1109/TVT.2018.2803062.
   Web of Science ®Google Scholar
• Yang, Z., Y. Feng, and H. X. Liu. 2021. “A Cooperative Driving Framework for Urban Arterials in Mixed Traffic Conditions.” Transportation Research Part C: Emerging Technologies 124 (March): 102918. doi:10.1016/j.trc.2020.102918.
   Google Scholar
• Zheng, N., R. A. Waraich, K. W. Axhausen, and N. Geroliminis. 2012. “A Dynamic Cordon Pricing Scheme Combining the Macroscopic Fundamental Diagram and an Agent-based Traffic Model.” Transportation Research Part A: Policy and Practice 46 (8): 1291–1303. doi:10.1016/j.tra.2012.05.006.
   Web of Science ®Google Scholar