Inertial Measurement Units-Based Probe Vehicles: Automatic Calibration, Trajectory Estimation, and Context Detection
Online Publication Date2017-12-06
Print Publication Date2017
Permanent link to this recordhttp://hdl.handle.net/10754/626790
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AbstractMost probe vehicle data is generated using satellite navigation systems, such as the Global Positioning System (GPS), Globalnaya navigatsionnaya sputnikovaya Sistema (GLONASS), or Galileo systems. However, because of their high cost, relatively high position uncertainty in cities, and low sampling rate, a large quantity of satellite positioning data is required to estimate traffic conditions accurately. To address this issue, we introduce a new type of traffic monitoring system based on inexpensive inertial measurement units (IMUs) as probe sensors. IMUs as traffic probes pose unique challenges in that they need to be precisely calibrated, do not generate absolute position measurements, and their position estimates are subject to accumulating errors. In this paper, we address each of these challenges and demonstrate that the IMUs can reliably be used as traffic probes. After discussing the sensing technique, we present an implementation of this system using a custom-designed hardware platform, and validate the system with experimental data.
CitationMousa M, Sharma K, Claudel CG (2017) Inertial Measurement Units-Based Probe Vehicles: Automatic Calibration, Trajectory Estimation, and Context Detection. IEEE Transactions on Intelligent Transportation Systems: 1–11. Available: http://dx.doi.org/10.1109/TITS.2017.2772080.
SponsorsThis work was supported by the Texas Department of Transportation through the Bringing Smart Transport to Texans: Ensuring the Benefits of a Connected and Autonomous Transport System in Texas Project, under Grant 0-6838. The Associate Editor for this paper was S. Kong.