![]() In the evaluation, the high-precision GNSS/IMU system POSLV220 was used as the reference value, and the effectiveness of the proposed method was confirmed by comparing the slip angle estimate by the proposed method and the trajectory estimate after slip angle correction with the reference value, respectively. In order to confirm the effectiveness of the slip angle correction by the proposed method, we focused on the accuracy of the trajectory in the road orthogonal direction and evaluated it using data acquired from two different environments (“ Evaluation tests” section). The slip angle estimated by our method allows us to make corrections to the trajectory, thereby realizing highly accurate vehicle trajectory estimation in the range of normal operation. In addition, our method does not require the construction of an observer and can be used universally because it utilizes not only conventional vehicle motion sensors such as IMU but also GNSS Doppler, which is information from outside the vehicle. The major gap between our method and conventional methods is that we do not estimate the parameters one by one, but rather eliminate variable parameters by rearranging the model equations and estimate fixed parameters. Therefore, in the proposed method, the parameters of the two-wheeled vehicle model are automatically estimated using GNSS Doppler to estimate the trajectory corrected for the slip angle. However, the two-wheeled models require one-by-one estimation of multiple parameters, which imparts error biases and makes the accurate estimation of vehicular trajectory difficult. Therefore, the slip angle estimation is generally carried out using a two-wheeled model to improve the accuracy of vehicular trajectory estimations. A difference is known to occur between the directions of the velocity vector and the heading angle (slip angle) when the vehicle turns. In addition, we focus on the normal driving range of vehicles and aim to increase the accuracy of the vehicle trajectory estimation performance. Therefore, the method proposed in this study aims to achieve accurate trajectory estimation using inexpensive sensors. However, the cost of using these expensive sensors is an issue. Moreover, conventional automated vehicles often use GNSS/IMU systems with expensive sensors, such as fiber-optic gyros, to achieve the required accuracy. ![]() The required accuracy is a 2D error of 0.3 m per 100 m of trajectory, which corresponds to the thickness of a tire. Accuracy is required for trajectory estimation of automated vehicles. Accurate trajectory information has been used in various studies such as constraints for position estimation, 3-D mapping for automated vehicles, route planning, and vehicular control. Highly accurate vehicular trajectory estimation has become imminently important for automated vehicles and advanced driver assistance systems that have been developed in the recent years.
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