Shoma Hisaka

GPS multipath detection and rectification using 3D maps

Global Navigation Satellite Systems (GNSSs) suffer from the problems of invisible satellites and multipath effect in urban canyons. Many approaches have been employed to eliminate multipath signals in order to reduce positioning errors. Among these, those that consider the geometry of surrounding buildings to improve the evaluation of possible multipath signals have gained most interest. However, such approaches, although successful, require many satellites for positioning after eliminating multipath signals. This study proposes an approach in which the multipath signals themselves are used for positioning error correction. The proposed algorithm evaluates the pseudoranges of the possible multipath signals by referring to the building geometry. The assumed position is estimated by using the pseudoranges and is evaluated by the likelihood of the possible positioning error. The proposed method was verified through field experiments in urban canyons in Tokyo.

On-board wireless sensor for collision avoidance: Vehicle and pedestrian detection at intersection

In this paper, a dedicated on-board ‘sensor’ utilizing wireless communication devices was developed for the collision avoidance around intersection. Four wireless receivers of Zigbee are installed in the four corners of the drivers vehicle. Each receiver is shielded and has slightly directivity. These effects enable ‘sensor’ to estimate positions of transmitters, which is brought by pedestrians, bicycles, motor cycles, and vehicles based on comparison of four signal strength of four receivers. Positions are obtained relative to the drivers vehicle as combinations of four directions, near or far, and approaching or leaving. Since the estimation algorithm is focusing on relative values among four wireless receivers, the detection results should not be affected by the transmission power. On-board sensors utilizing vision, LIDAR and radar cannot detect objects hidden by road facilities and other vehicle. Although infrastructure sensors for Vehicle-to-Infrastructure cooperative systems can detect such the hidden objects, they are much expensive than on-board sensors. The on-board wireless ‘sensor’ developed in this paper would be an alternative method for the collision avoidance around intersections.

Developments of wireless sensing method for intersection safety (poster)

In this paper, a dedicated on-board ‘sensor’ utilizing wireless communication devices was developed for the collision avoidance around intersection. Four wireless receivers of Zigbee are installed in the four corners of the drivers vehicle. Each receiver is shielded and has slightly directivity. These effects enable ‘sensor’ to estimate positions of transmitters, which is brought by pedestrians, bicycles, motor cycles, and vehicles based on comparison of four signal strength of four receivers. Positions are obtained relative to the drivers vehicle as combinations of four directions, distances. Since the estimation algorithm is focusing on relative values among four wireless receivers, the detection results should not be affected by the transmission power. On-board sensors utilizing vision, LIDAR and radar cannot detect objects hidden by road facilities and other vehicle. Although infrastructure sensors for Vehicle-to-Infrastructure cooperative systems can detect such the hidden objects, they are much expensive than on-board sensors. The on-board wireless ‘sensor’ developed in this paper would be an alternative method for the collision avoidance around intersections.

Positioning of road users by RSSI with road surface reflection model

We have developed a dedicated onboard “sensor” utilizing wireless communication devices for collision avoidance around road intersections. The “sensor” estimates the positions of transmitters on traffic participants by comparing the strengths of signals received by four ZigBee receivers installed at the four corners of observing vehicle. In our previous work, the “sensor” was proposed as an alternative tool for collision avoidance around intersections. Herein, we extend our previous work by considering a road surface reflection model to improve the estimation accuracy. By using this model, we succeeded in reducing the error mismatches between the observed data and the calibration data of the estimation algorithm. The validity of the reflection model is verified via FDTD electro-magnetic wave propagating simulation. The proposed system will be realized on the basis of these enhancements.

Developments of wireless sensor system for intersection safety

In this paper, a dedicated on-board ‘sensor’ utilizing wireless communication devices was developed for the collision avoidance around intersections. Four wireless receivers of Zigbee are installed in the four corners of the drivers vehicle. The signal intensities of the four receivers were compared to estimate positions of transmitters brought by pedestrians, bicycles, motor cycles, and vehicles. Positions are obtained relative to the drivers vehicle as combinations of four directions, near or far, and approaching or leaving. Since the estimation algorithm is focusing on relative values among four wireless receivers, the detection results should not be affected by the transmission power. On-board sensors utilizing Vision, LIDAR and Radar cannot detect objects hidden by road facilities and other vehicle. Although infrastructure sensors for Vehicle-to-Infrastructure cooperative systems can detect such the hidden objects, they are much more expensive than on-board sensors. The on-board wireless ‘sensor’ developed in this paper would be an alternative method for the collision avoidance around intersections.

Road user positioning by RSSI combinations with pavement reflection at real intersection

We have developed a dedicated onboard “sensor” utilizing wireless communication devices for collision avoidance around road intersections. The “sensor” estimates the positions of transmitters on traffic participants by comparing the strengths of signals received by four ZigBee receivers installed at the four corners of observing vehicle. In our previous work, the “sensor” was proposed as an alternative tool for collision avoidance around intersections. Herein, we extend our previous work by considering a road surface reflection model to improve the estimation accuracy. By using this model, we succeeded in reducing the error mismatches between the observed data and the calibration data of the estimation algorithm. The validity of the reflection model is verified via FDTD electro-magnetic wave propagating simulation. The proposed system will be realized on the basis of these enhancements. In addition to these improvements, we performed experiments at real intersection using customized vehicle. We report the basic evaluation of the experimental results in this paper.

Onboard Sensing System for Intersection Safety: Use of Received Signal Strength Indication

A dedicated onboard sensor that used wireless communications devices was developed for collision avoidance around intersections. Four ZigBee wireless receivers were installed in the four corners of the drivers vehicle. Each receiver was shielded and had slight directivity. These settings enabled the sensor to estimate the positions of transmitters on pedestrians, bicycles, motorcycles, and vehicles on the basis of a comparison of four signal strengths received from the four receivers. Positions were obtained relative to the drivers vehicle as combinations of four directions: near or far and approaching or leaving. Because the estimation algorithm considered relative values obtained from the four wireless receivers, the detection results should not have been affected by the transmission power. Onboard sensors with vision, lidar, and radar cannot detect objects hidden by road facilities and other vehicles. Although infrastructure sensors for vehicle-to-infrastructure cooperative systems can detect such hidden objects, they are substantially more expensive than onboard sensors. The onboard wireless sensor developed in this work would function as an alternative tool for collision avoidance around intersections.