Abstract: This document describes methods and systems for vehicle localization based on radar detections. Radar localization starts with building a radar reference map. The radar reference map may be generated and updated using different techniques as described herein. Once a radar reference map is available, real-time localization may be achieved with inexpensive radar sensors and navigation systems. Using the techniques described in this document, the data from the radar sensors and the navigation systems may be processed to identify stationary localization objects, or landmarks, in the vicinity of the vehicle. Comparing the landmark data originating from the onboard sensors and systems of the vehicle with landmark data detailed in the radar reference map may generate an accurate pose of the vehicle in its environment. By using inexpensive radar systems and lower quality navigation systems, a highly accurate vehicle pose may be obtained in a cost-effective manner.

Abstract: Methods and systems are described that enable radar reference map generation. A high-definition (HD) map is received and one or more HD map objects within the HD map are determined. Attributes of the respective HD map objects are determined, and, for each HD map object, one or more occupancy cells of a radar occupancy grid are indicated as occupied space based on the attributes of the respective HD map object. By doing so, a radar reference map may be generated without a vehicle traversing through an area corresponding to the radar reference map.

Abstract: Methods and systems are described that enable vehicle routing based on availability of radar-localization objects. A request to navigate to a destination is received, and at least two possible routes to the destination are determined. Availabilities of radar-localization objects for the possible routes are determined, and a route is selected based on the availabilities of the radar-localization objects. Furthermore, while traveling along a route, the vehicle is localized based on radar detections of radar-localization objects. A radar-localization quality of the localizing is monitored, and a determination is made that the radar-localization quality has dropped or will drop. Based on the radar-localization quality dropping, the route is modified and/or an operation of a radar module is adjusted. In this way, availabilities of radar-localization objects may be used to select an optimal route and to adjust a current navigation along a route to minimize driver takeover.

Abstract: Methods and systems are described that enable vehicle routing based on availability of radar-localization objects. A request to navigate to a destination is received, and at least two possible routes to the destination are determined. Availabilities of radar-localization objects for the possible routes are determined, and a route is selected based on the availabilities of the radar-localization objects. Furthermore, while traveling along a route, the vehicle is localized based on radar detections of radar-localization objects. A radar-localization quality of the localizing is monitored, and a determination is made that the radar-localization quality has dropped or will drop. Based on the radar-localization quality dropping, the route is modified and/or an operation of a radar module is adjusted. In this way, availabilities of radar-localization objects may be used to select an optimal route and to adjust a current navigation along a route to minimize driver takeover.

Abstract: This document describes techniques and systems to detect and localize NLOS objects using multipath radar reflections and map data. In some examples, a processor of radar system can identify a detection of an object using reflected EM energy and determine, using map data, whether a direct-path reflection associated with the detection is within a roadway. In response to determining that the direct-path reflection is not located within the roadway, the processor can determine whether a multipath reflection (e.g., a multipath range and multipath angle) associated with the detection is viable. In response to determining that the multipath reflection is viable, the processor can determine that the detection corresponds to an NLOS object. The processor can also provide the NLOS object as an input to an autonomous or semi-autonomous driving system of the vehicle, thereby improving the safety of such systems.

Abstract: Methods and systems are described that enable radar reference map generation. A radar occupancy grid is received, and radar attributes are determined from occupancy probabilities within the radar occupancy grid. Radar reference map cells are formed, and the radar attributes are used to determine Gaussians for the radar reference map cells that contain a plurality of the radar attributes. A radar reference map is then generated that includes the Gaussians determined for the radar referenced map cells that contain the plurality of radar attributes. By doing so, the generated radar reference map is accurate while being spatially efficient.

Abstract: Methods and systems are described that enable vehicle routing based on availability of radar-localization objects. A request to navigate to a destination is received, and at least two possible routes to the destination are determined. Availabilities of radar-localization objects for the possible routes are determined, and a route is selected based on the availabilities of the radar-localization objects. Furthermore, while traveling along a route, the vehicle is localized based on radar detections of radar-localization objects. A radar-localization quality of the localizing is monitored, and a determination is made that the radar-localization quality has dropped or will drop. Based on the radar-localization quality dropping, the route is modified and/or an operation of a radar module is adjusted. In this way, availabilities of radar-localization objects may be used to select an optimal route and to adjust a current navigation along a route to minimize driver takeover.

Abstract: Methods and systems are described that enable radar reference map generation. A high-definition (HD) map is received and one or more HD map objects within the HD map are determined. Attributes of the respective HD map objects are determined, and, for each HD map object, one or more occupancy cells of a radar occupancy grid are indicated as occupied space based on the attributes of the respective HD map object. By doing so, a radar reference map may be generated without a vehicle traversing through an area corresponding to the radar reference map.

Abstract: This document describes methods and systems for vehicle localization based on radar detections. Radar localization starts with building a radar reference map. The radar reference map may be generated and updated using different techniques as described herein. Once a radar reference map is available, real-time localization may be achieved with inexpensive radar sensors and navigation systems. Using the techniques described in this document, the data from the radar sensors and the navigation systems may be processed to identify stationary localization objects, or landmarks, in the vicinity of the vehicle. Comparing the landmark data originating from the onboard sensors and systems of the vehicle with landmark data detailed in the radar reference map may generate an accurate pose of the vehicle in its environment. By using inexpensive radar systems and lower quality navigation systems, a highly accurate vehicle pose may be obtained in a cost-effective manner.

Abstract: A camera adjustment system includes a camera, an actuator, an inertial-measurement-unit, and one or more controller-circuits. The camera renders an image of lane-markings of a roadway traveled by a host-vehicle. The actuator is operable for controlling an aim-direction of the camera. The inertial-measurement-unit detects relative-movement of the host-vehicle. The one or more controller-circuits are in communication with the camera, the actuator, and the inertial-measurement-unit. The one or more controller-circuits determine whether a range-of-detection of the lane-markings in the image is less than a detection-threshold and adjust the aim-direction based on the relative-movement.

Abstract: A camera adjustment system includes a camera, an actuator, an inertial-measurement-unit, and one or more controller-circuits. The camera renders an image of lane-markings of a roadway traveled by a host-vehicle. The actuator is operable for controlling an aim-direction of the camera. The inertial-measurement-unit detects relative-movement of the host-vehicle. The one or more controller-circuits are in communication with the camera, the actuator, and the inertial-measurement-unit. The one or more controller-circuits determine whether a range-of-detection of the lane-markings in the image is less than a detection-threshold and adjust the aim-direction based on the relative-movement.

Abstract: A camera adjustment system includes a camera, an actuator, an inertial-measurement-unit, and one or more controller-circuits. The camera renders an image of lane-markings of a roadway traveled by a host-vehicle. The actuator is operable for controlling an aim-direction of the camera. The inertial-measurement-unit detects relative-movement of the host-vehicle. The one or more controller-circuits are in communication with the camera, the actuator, and the inertial-measurement-unit. The one or more controller-circuits determine whether a range-of-detection of the lane-markings in the image is less than a detection-threshold and adjust the aim-direction based on the relative-movement.

Abstract: A camera adjustment system includes a camera, an actuator, an inertial-measurement-unit, and one or more controller-circuits. The camera renders an image of lane-markings of a roadway traveled by a host-vehicle. The actuator is operable for controlling an aim-direction of the camera. The inertial-measurement-unit detects relative-movement of the host-vehicle. The one or more controller-circuits are in communication with the camera, the actuator, and the inertial-measurement-unit. The one or more controller-circuits determine whether a range-of-detection of the lane-markings in the image is less than a detection-threshold and adjust the aim-direction based on the relative-movement.

Abstract: A parking-assist system suitable for use on an automated vehicle includes a radar sensor and a controller. The radar-sensor detects a first-vehicle and a second-vehicle adjacent to a travel-path of a host-vehicle. A distance between the first-vehicle and the second-vehicle defines a parking-space. The controller is in communication with the radar-sensor. The controller determines the distance before the host-vehicle enters a zone of the travel-path adjacent to the parking-space. The zone has a length determined by the distance, and the controller determines when the parking-space is large enough to accommodate the host-vehicle based on the distance.

Abstract: A parking-assist system suitable for use on an automated vehicle includes a radar sensor and a controller. The radar-sensor detects a first-vehicle and a second-vehicle adjacent to a travel-path of a host-vehicle. A distance between the first-vehicle and the second-vehicle defines a parking-space. The controller is in communication with the radar-sensor. The controller determines the distance before the host-vehicle enters a zone of the travel-path adjacent to the parking-space. The zone has a length determined by the distance, and the controller determines when the parking-space is large enough to accommodate the host-vehicle based on the distance.