No abstract

Accurate vehicular trajectory estimation is important for the recently developed autonomous driving systems. As the accuracy of the vehicular trajectory estimation is reduced with the slippage that occurs during turning, we propose a method in this study to accurately estimate the trajectory of a vehicle, focusing on the slip angle estimation. Although the two-wheel model is used as a general concept slip angle estimation, the accurate estimation of the parameters was difficult using the conventional methods. Therefore, a global navigation satellite system (GNSS) Doppler was used for parameter estimation. In addition, the roll angle was estimated as it occurs during turning and affects the slip angle of the vehicle. Specifically, we verified the improvement in accuracy of the vehicular trajectory estimation using the cost-effective GNSS Doppler/IMU.

No abstract

Autonomous driving support systems and self-driving cars require the determination of reliable vehicle positions with high accuracy. The real time kinematic (RTK) algorithm with global navigation satellite system (GNSS) is generally employed to obtain highly accurate position information. Because RTK can estimate the fix solution, which is a centimeter-level positioning solution, it is also used as an indicator of the position reliability. However, in urban areas, the degradation of the GNSS signal environment poses a challenge. Multipath noise caused by surrounding tall buildings degrades the positioning accuracy. This leads to large errors in the fix solution, which is used as a measure of reliability. We propose a novel position reliability estimation method by considering two factors; one is that GNSS errors are more likely to occur in the height than in the plane direction; the other is that the height variation of the actual vehicle travel path is small compared to the amount of movement in the horizontal directions. Based on these considerations, we proposed a method to detect a reliable fix solution by estimating the height variation during driving. To verify the effectiveness of the proposed method, an evaluation test was conducted in an urban area of Tokyo. According to the evaluation test, a reliability judgment rate of 99% was achieved in an urban environment, and a plane accuracy of less than 0.3 m in RMS was achieved. The results indicate that the accuracy of the proposed method is higher than that of the conventional fix solution, demonstratingits effectiveness.

In this study, by utilizing GNSS Doppler and low cost sensor, we estimate vehicle motion robustly and estimate highly accurate vehicle trajectory even in urban environment where satellite signal deteriorates. In addition, we propose a method that can improve the position accuracy by selecting the positioning result of GNSS using highly accurate vehicle locus. The proposed method intentionally does not estimate fluctuation of the clock error of the receiver, thereby making it possible to use the long distance (several 100 meters) trajectory and has the feature that position estimation accuracy is improved by the averaging effect.

No abstract

No abstract

Accurate vehicular trajectory estimation is important for the recently developed autonomous driving systems. As the accuracy of the vehicular trajectory estimation is reduced with the slippage that occurs during turning, we propose a method in this study to accurately estimate the trajectory of a vehicle, focusing on the slip angle estimation. Although the two-wheel model is used as a general concept slip angle estimation, the accurate estimation of the parameters was difficult using the conventional methods. Therefore, a global navigation satellite system (GNSS) Doppler was used for parameter estimation. In addition, the roll angle was estimated as it occurs during turning and affects the slip angle of the vehicle. Specifically, we verified the improvement in accuracy of the vehicular trajectory estimation using the cost-effective GNSS Doppler/inertial measurement unit.