Abstract
Cooperative safety systems which utilize roadside sensors or smartphones are expected to be solutions for cyclistrelated accidents at intersections with poor visibility. However, in actual environments, it is required to estimate positions of traffic participants with the limited number of real-time sensors. To compensate for the lack of real-time sensor data, this study proposes a method to utilize statistical information as virtual observations for Kalman Filter. First, we design virtual observations based on the statistical data of cyclist's velocity and the time-series effect of position estimation. Then, through the evaluations in the simulations and the real-world experiments, we confirm that the uncertainty of position estimation is reduced by the proposed method. This study will contribute to the cooperative safety systems under the situation of the limited real-time sensor data.
