Abstract: A low-floor electric axle assembly including: an axle housing, two hub motors, two planetary gear reducers, two hubs, a brake system, two C-shaped beams, and a suspension system. Mechanical mounting of the suspension system is compatible with a conventional axle. The axle housing has a left and right symmetrical dumbbell-shaped structure configured to bear a weight of a vehicle. The hub motors are inner rotor type motors and are separately arranged at two ends of the axle housing left and right symmetrically. The hub motors are arranged coaxially with two wheels respectively. Two hub motor rotors are connected to the planetary gear reducers respectively. Each of the planetary gear reducers is a single-stage planetary gear reducer. A sun gear of each of the planetary gear reducers receives power outputted by each of the hub motor. Two planetary gear reducer housings are power output ends connected to two rims respectively.

Abstract: A vehicle is described, and includes an on-board controller, an extra-vehicle communication system, a GPS sensor, a spatial monitoring system, and a navigation system that employs an on-vehicle navigation map. Operation includes capturing a 3D sensor representation of a field of view and an associated GPS location, executing a feature extraction routine, executing a semantic segmentation of the extracted features, executing a simultaneous location and mapping (SLAM) of the extracted features, executing a context extraction from the simultaneous location and mapping of the extracted features, and updating the on-vehicle navigation map based thereon. A parsimonious map representation is generated based upon the updated on-vehicle navigation map, and is communicated to a second, off-board controller. The second controller executes a sparse map stitching to update a base navigation map based upon the parsimonious map representation. The on-vehicle navigation map is updated based upon the off-board navigation map.

Abstract: A vehicle is described, and includes an on-board controller, an extra-vehicle communication system, a GPS sensor, a spatial monitoring system, and a navigation system that employs an on-vehicle navigation map. Operation includes capturing a 3D sensor representation of a field of view and an associated GPS location, executing a feature extraction routine, executing a semantic segmentation of the extracted features, executing a simultaneous location and mapping (SLAM) of the extracted features, executing a context extraction from the simultaneous location and mapping of the extracted features, and updating the on-vehicle navigation map based thereon. A parsimonious map representation is generated based upon the updated on-vehicle navigation map, and is communicated to a second, off-board controller. The second controller executes a sparse map stitching to update a base navigation map based upon the parsimonious map representation. The on-vehicle navigation map is updated based upon the off-board navigation map.

Abstract: Systems and method are provided for controlling an autonomous vehicle. In one embodiment, a method includes: receiving sensor data from a sensor of the vehicle; determining a three dimensional point cloud map segment from the sensor data; determining a vehicle pose associated with the three-dimensional point cloud map segment; determining a pose difference based on the vehicle pose, another vehicle pose, and a two-step process, wherein the two-step process includes computing a coarse-granularity pose difference, and computing a fine-granularity pose difference; aligning the three dimensional point cloud map segment with another three dimensional point cloud map segment associated with the other vehicle pose based on the pose difference; and controlling the vehicle based on the aligned three dimensional point cloud map segments.

Abstract: Systems and method are provided for controlling an autonomous vehicle. In one embodiment, a method includes: receiving sensor data from a sensor of the vehicle; determining a three dimensional point cloud map segment from the sensor data; determining a vehicle pose associated with the three-dimensional point cloud map segment; determining a pose difference based on the vehicle pose, another vehicle pose, and a two-step process, wherein the two-step process includes computing a coarse-granularity pose difference, and computing a fine-granularity pose difference; aligning the three dimensional point cloud map segment with another three dimensional point cloud map segment associated with the other vehicle pose based on the pose difference; and controlling the vehicle based on the aligned three dimensional point cloud map segments.

Abstract: A system and method is taught for vehicles controlled by automated driving systems, particularly those configured to automatically control vehicle steering, acceleration, and braking during a drive cycle without human intervention. In particular, the present disclosure teaches a system and method for generation situational awareness and path planning data and transmitting this information via vehicle to vehicle communications where one vehicle has an obstructed view to objects not within an obstructed view of a second vehicle.

Abstract: A system and method is taught for vehicles controlled by automated driving systems, particularly those configured to automatically control vehicle steering, acceleration, and braking during a drive cycle without human intervention. In particular, the present disclosure teaches a system and method for generation situational awareness and path planning data and transmitting this information via vehicle to vehicle communications where one vehicle has an obstructed view to objects not within an obstructed view of a second vehicle.