Clearmotion, Inc.

Shenzhen Gudsen Technology Co., Ltd

The Mathworks, Inc.

Yu Jiang

David Francis Weatherwax

John Parker Eisenmann

Vijayaraghavan Sridhar

Chenyong Guan

Marco Giovanardi

Jack A Ekchian

Murali K Yeddanapudi

Fu Zhang

William Graves

Michael W Finnegan

Mario Flores Alanis

Aditya Chandrashekhar Chetty

Paul A DiZio

James R Lackner

Systems and methods of performing localization of a vehicle are provided. The system receives data comprising one or more of: raw images from one or more vision sensors, motion sensor data, or lane-level map information. The system determines, based on the data, a lane in which the vehicle is located and lateral displacement of a center of the vehicle relative to a center of the lane.

Image-based localization module

Systems and methods for determining the location of a vehicle are disclosed. In one embodiment, a method for localizing a vehicle includes driving over a first road segment, identifying by a first localization system a set of candidate road segments, obtaining vertical motion data while driving over the first road segment, comparing the obtained vertical motion data to reference vertical motion data associated with at least one candidate road segment, and identifying, based on the comparison, a location of the vehicle. The use of such localization methods and systems in coordination with various advanced vehicle systems such as, for example, active suspension systems or autonomous driving features, is contemplated.

Road surface-based vehicle control

Various systems and methods are disclosed for predicting, detecting or mitigating motion sickness of one or more occupants of a vehicle. Also, disclosed are systems and methods for measuring aspects of head motion and characteristics of at least one eye an occupant of a vehicle and using that information mitigate motion sickness.

Method and apparatus for motion sickness mitigation in a vehicle

Localization systems, including road surface-based localization systems, are disclosed that may work in conjunction with less precise systems, such as GPS, to accurately locate a vehicle on a road segment. Methods and apparatus are disclosed for the identification and selection of landmarks, including road surface-based landmarks.

Vehicular localization systems, methods, and controls

Systems, methods, and apparatuses for vehicle localization. The vehicle can include a data processing system ('DPS') including one or more processors and memory. The DPS can receive sensor data from sensors of the vehicle. The DPS can identify a historical road profile of the ground for a first location of the vehicle. The DPS can generate a current road profile of the ground. The DPS can determine a lateral deviation of the vehicle. The DPS can determine a match between the historical road profile and the current road profile at a second location that aligns with the lateral deviation. The DPS can provide an indication of a current location of the vehicle as the second location.

Simultaneous localization and mapping using road surface data

Systems, methods, and apparatuses for controlling components of a vehicle are provided. The vehicle can include a data processing system ('DPS') including one or more processors and memory. The DPS can receive sensor data from sensors of the vehicle. The DPS can determine a vehicle body height. The DPS can determine a vehicle roll angle. The DPS can determine a first height of a road and a second height or the road. The DPS can determine a road height based on the first height of the road and the second height of the road. The DPS can provide the road height to a controller of one or more vehicles. The DPS can adjust the component of the one or more vehicles.

Vehicle sensors arrangement and method for mapping the road profiles

Systems and methods may highlight paths through graphical models having executable semantics. Paths through a model leading from a starting location and terminating at final source and/or destination model elements may be identified. The paths may be highlighted. A model may include hierarchical levels, and the highlighting may be extended into lower or higher hierarchical levels relative to a current level. A model may execute over a plurality of simulation time steps, and the highlighting may indicate model elements executing in a given simulation time step.

Growing community of inventors

Wellesley, MA, United States of America

Yu Jiang