Tusimple, Inc.

Toyota Motor Engineering & Manufacturing North America, Inc.

University of Technology Sydney

Xue Mei

Danil V Prokhorov

Xiaoling Han

Xiaodi Hou

Mingdong Wang

Chenzhe Qian

Katsuhiro Sakai

Yujie Wei

Nobuhide Kamata

Zehua Huang

Ke Xu

Dazhou Guo

Dacheng Tao

Yi Luo

Naoki Nagasaka

Chenyang Li

Zhibin Hong

Chaohui Wang

Bunyo Okumura

Haibin Ling

Zhe Chen

Masahiro Harada

Kuan-Hui Lee

Michael James Delp

Huchuan Lu

Luning Liu

Yi Wu

Jun Li

Devices, systems and methods for operating a rear-facing perception system for vehicles are described. An exemplary rear-facing perception system contains two corner units and a center unit, with each of the two corner units and the center unit including a camera module and a dual-band transceiver. A method for operating the rear-facing perception system includes pairing with a control unit by communicating, using the dual-band transceiver, over at least a first frequency band, transmitting a first trigger signal to the two corner units over a second frequency band non-overlapping with the first frequency band, and switching to an active mode. In an example, the first trigger signal causes the two corner units to switch to the active mode, which includes orienting the camera modules on the center unit and the two corner units to provide an unobstructed view of an area around a rear of the vehicle.

Rear-facing perception system for vehicles

Systems and methods for detecting trailer angle are provided. In one aspect, an in-vehicle control system includes an optical sensor configured to be mounted on a tractor so as to face a trailer coupled to the tractor, the optical sensor further configured to generate optical data indicative of an angle formed between the trailer and the tractor. The system further includes a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to receive the optical data from the optical sensor, determine at least one candidate plane representative of a surface of the trailer visible in the optical data based on the optical data, and determine an angle between the trailer and the tractor based on the at least one candidate plane.

Systems and methods for detecting trailer angle

Various embodiments of the present disclosure provide a system and method for lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In the embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a camera; and a computer connected to the locating device, database, and camera, wherein the computer is adapted to: receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information form the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and generate a predicted vehicle location based on the comparison of the response map and region map.

Lane marking localization

Various embodiments provide a system and method for iterative lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In an embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a plurality of cameras; and a computer connected to the locating device, database, and cameras, wherein the computer is adapted to receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information from the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and iteratively generate a predicted vehicle location based on the comparison of the response map and the region map.

Lane marking localization and fusion

Disclosed are devices, systems and methods for capturing an image. In one aspect an electronic camera apparatus includes an image sensor with a plurality of pixel regions. The apparatus further includes an exposure controller. The exposure controller determines, for each of the plurality of pixel regions, a corresponding exposure duration and a corresponding exposure start time. Each pixel region begins to integrate incident light starting at the corresponding exposure start time and continues to integrate light for the corresponding exposure duration. In some example embodiments, at least two of the corresponding exposure durations or at least two of the corresponding exposure start times are different in the image.

Adaptive illumination for a time-of-flight camera on a vehicle

A system and method for large-scale lane marking detection using multimodal sensor data are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on a vehicle; receiving point cloud data from a distance and intensity measuring device mounted on the vehicle; fusing the image data and the point cloud data to produce a set of lane marking points in three-dimensional (3D) space that correlate to the image data and the point cloud data; and generating a lane marking map from the set of lane marking points.

System and method for large-scale lane marking detection using multimodal sensor data

Disclosed are devices, systems and methods for curb detection using light detection and ranging (LiDAR) sensors. One example of a method for curb detection includes acquiring, based on a scan of an area around a vehicle, a point-cloud frame that includes a description of an intensity of a reflection of the area around the vehicle, selecting a subset of points from the point-cloud frame, seeding each of a plurality of clusters based on the selected points, determining a criterion for each of the selected points, increasing a size of each of the plurality of clusters by including additional points from the point-cloud frame that meet the criterion for the corresponding cluster, identifying a largest cluster of the plurality of clusters upon completion of the increasing step, and detecting a curb based on a boundary of the largest cluster.

Curb detection by analysis of reflection images

Growing community of inventors

Ann Arbor, MI, United States of America

Xue Mei