Name
Abstract | ||
|---|---|---|
A method for integrating, processing and analysis of sensing data from vehicle-mounted sensors for intelligent forecasting and decision-making is introduced. This Dead Reckoning with Dynamic Errors (DRWDE) is for a large-scale integration of distributed resources and sensing data inter-vehicle collision avoidance system. This sensor fusion algorithm is introduced to predict the future trajectory of a vehicle. Current systems that predict a vehicle’s future trajectory, necessary in a network of collision avoidance systems, tend to have a lot of errors when the vehicles are moving in a non-straight path. Our system has been designed with the objective of improving the estimations during curves. To evaluate this system, our research uses a Garmin 16HVS GPS sensor, an AutoEnginuity OBDII ScanTool, and a Crossbow 3-axis accelerometer. Using Kalman Filters (KF) a dynamic noise covariance matrix merged together with an Interacting Multiple Models system, our DRWDE produces the future position estimation of where the vehicle will be 3 seconds later in time. The ability to handle the change in noise, depending on unavailable sensor measurements, permits a flexibility to use any type of sensor and still have the system run at the fastest frequency available. Compared to a more common KF implementation that runs at the rate of its slowest sensor (1Hz in our setup), our experimental results showed that our DRWDE (running at 10Hz) yielded more accurate predictions (25-50% improvement) during abrupt changes in the heading of the vehicle. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TII.2015.2514086 | IEEE Trans. Industrial Informatics |
Keywords | Field | DocType |
Collision avoidance, course correction, dead reckoning, global positioning system, Kalman filters, road vehicles, sensor fusion | Accelerometer,Computer science,Simulation,Sensor fusion,Real-time computing,Kalman filter,Control engineering,Dead reckoning,Vehicle dynamics,Global Positioning System,Collision avoidance system,Trajectory | Journal |
Volume | Issue | ISSN |
PP | 99 | 1551-3203 |
Citations | PageRank | References |
4 | 0.46 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Barrios, C. | 1 | 38 | 3.29 |
| Yuichi Motai | 2 | 230 | 24.68 |
| Huston, D. | 3 | 4 | 1.13 |