Vehicle Trajectory Reconstruction Incorporating Probe and Fixed Sensor Data
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 9
Abstract
Trajectory estimation is essential for obtaining a complete picture of traffic flow with limited and continuously detected traffic data, which are helpful in evaluating transportation performance and developing precise control measures. Most existing models assume the first-in-first-out principle, which generally is violated by the overtaking action in microscopic simulations and observations. This study focused on improving the accuracy of trajectory reconstruction by incorporating probes and fixed sensor data in multilane facilities. Accordingly, we developed a staircase vehicle order–changing model to describe the overtaking behaviors of vehicles. A field-test data set containing Global Positioning System (GPS) trajectories and automatic vehicle identification (AVI) observations was collected from some probe position units and fixed vehicle-identification cameras. Empirical studies demonstrated that the estimated error of the proposed algorithm was approximately 7%, which was approximately 22% and 12.5% less than that of two benchmark models. These results verified the superiority of our proposed algorithm and confirmed the importance of considering the overtaking behavior of vehicles in trajectory reconstruction.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
Acknowledgments
Authors Yue Deng and Qi Cao contributed equally to the work. The authors acknowledge the financial support provided by the National Natural Research Foundation of China (Grant Nos. 52202399 and 52072068), the China Postdoctoral Science Foundations (Grant No. 2022M710679), and the Postgraduate Research and Practice Innovation Program of Jiangsu Province (No. KYCX21_0129). The authors are grateful to the Shenzhen Urban Transport Center for the research data.
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 9 • September 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Oct 29, 2022
Accepted: Apr 11, 2023
Published online: Jun 30, 2023
Published in print: Sep 1, 2023
Discussion open until: Nov 30, 2023
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