Automotive Research & Testing Center

United Microelectronics Corp.

Ying-Ren Chen

Siang-Min Siao

Ching-Wen Hung

Yi-Feng Su

Li-You Hsu

Yun-Ling Chang

Peng-Hsiu Chen

Su-Ming Hsieh

The invention provides a layout pattern of a semiconductor varactor, which comprises a plurality of varactor units arranged on a substrate, wherein each varactor unit comprises a plurality of fin structures arranged in parallel with each other, a plurality of gate structures arranged in parallel with each other, located on the substrate and spanning the fin structures, and a gate metal layer electrically connected with the plurality of gate structures.

Layout pattern of semiconductor varactor and forming method thereof

An object detection method includes steps that are to be performed for each piece of point cloud data received from a lidar module, of selecting a first to-be-combined image from among images received from a camera device that corresponds in time to the piece of point cloud data, selecting a second to-be-combined image from among the images that is the Nimage before the first to-be-combined image in the time order, combining the first to-be-combined image and the second to-be-combined image to generate a combined image, generating a result image by incorporating the piece of point cloud data into the combined image, and inputting the result image into a trained machine learning model in order to determine a class to which each object in the result image belongs.

Object detection method

A map-information obstacle-tracking system and a method thereof are provided. The system is installed in a vehicle. The method includes: using a vehicular dynamic positioning module to acquire a position of a vehicle, and using a map-information module to acquire map-information routes of an area neighboring the position of the vehicle; comparing position of the vehicle with the map-information routes to find out candidate routes in the moving direction of the vehicle; determining one of the candidate routes where said obstacle appears, and predicting a moving trajectory of the obstacle; estimating and outputting a position of the obstacle. The present invention is characterized in using map-information and able to acquire the curvature and slope of the front curved lane. Therefore, the present invention can improve the precision of the obstacle position and stabilizes the accuracy of detecting an obstacle in a curved lane.

Map-information obstacle-tracking system and method

The lidar detection device uses four two-dimensional lidars to scan an obstacle, to obtain original point-cloud data corresponding to the obstacle, and the original point-cloud data includes a relative distance, a relative angle and a relative speed of the obstacle relative to the vehicle, Next, the point-cloud data is classified into at least one point-cloud group corresponding to the obstacle, and a border length of the obstacle is obtained according to a contour of the point-cloud group. Kalman filter and extrapolation are used to estimate and track a movement path of a dynamic obstacle, and transmit the relative speed and the border length of the dynamic obstacle to an automatic driving controlling device. According to the relative distance, a coordinate of the dynamic obstacle nearest the vehicle can be obtained and transmitted to the automatic driving controlling device efficiently.

Growing community of inventors

Changhua County, Taiwan

Ying-Ren Chen