A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Range-based localization for estimating pedestrian trajectory in intersection with roadside anchors
In ITS research field, recently a lot of efforts have been made to develop driving safety support systems (DSSS) for car drivers such as warning to drivers “danger” in potential blind spots at intersections. In this paper, we propose a localization method to estimate the movement trajectories (position, speed and direction) of pedestrians near intersections by using some roadside anchors. In our method, we assume that each pedestrian is equipped with a small device which periodically emits a radio beacon signal and each roadside anchor can receive the signal and measure its received signal strength (RSS). Our method estimates the pedestrian position from RSS at each anchor based on the Maximum Likelihood Estimation (MLE) method. Moreover, to obtain an accurate pedestrian trajectory, our method applies the Bayes' theorem to a series of estimated positions and reduces estimation errors caused by uncertainty from radio interference and other factors. Through computer simulations with RapLab, we confirmed that our method estimates pedestrian positions within 2m error.
Range-based localization for estimating pedestrian trajectory in intersection with roadside anchors
In ITS research field, recently a lot of efforts have been made to develop driving safety support systems (DSSS) for car drivers such as warning to drivers “danger” in potential blind spots at intersections. In this paper, we propose a localization method to estimate the movement trajectories (position, speed and direction) of pedestrians near intersections by using some roadside anchors. In our method, we assume that each pedestrian is equipped with a small device which periodically emits a radio beacon signal and each roadside anchor can receive the signal and measure its received signal strength (RSS). Our method estimates the pedestrian position from RSS at each anchor based on the Maximum Likelihood Estimation (MLE) method. Moreover, to obtain an accurate pedestrian trajectory, our method applies the Bayes' theorem to a series of estimated positions and reduces estimation errors caused by uncertainty from radio interference and other factors. Through computer simulations with RapLab, we confirmed that our method estimates pedestrian positions within 2m error.
Range-based localization for estimating pedestrian trajectory in intersection with roadside anchors
Weihua Sun, (author) / Yamaguchi, Hirozumi (author) / Yasumoto, Keiichi (author) / Ito, Minoru (author)
2009-10-01
2139244 byte
Conference paper
Electronic Resource
English
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