Abstract: A method of coupling a sensor to a metal bumper for a vehicle, including providing a substrate configured as a sheet of metal for forming the metal bumper. The metal bumper is formed from the sheet of metal, the metal bumper having an exterior side and an interior side. An aperture is formed within the sheet of metal, including forming a perimeter of the aperture to receive the sensor therein and forming a tab configured to support the sensor. The sensor is inserted into the aperture from the interior side to an assembled position in which a front end of the sensor is flush with the aperture and the sensor is fixed to the metal bumper by the tab.

Abstract: A method of coupling a sensor to a metal bumper for a vehicle includes providing a substrate configured as a sheet of metal for forming the metal bumper, forming an aperture within sheet of metal, and inserting the sensor into the aperture such that the sensor is directly supported by the sheet of metal without an intervening retainer.

Abstract: Systems and methods for ice removal system for an ultrasonic sensor. One example system includes the ultrasonic sensor including a transducer and an electronic processor. The electronic processor is configured to output, at the transducer, a chirp signal. The electronic processor is configured to determine, based on the chirp signal, whether a mechanical impedance is present at the transducer. The electronic processor is configured to, in response to determining that the mechanical impedance is present, output, at the transducer, a frequency sweep signal. The electronic processor is configured to receive, at the transducer, a reflected frequency sweep signal. The electronic processor is configured to determine, based on the reflected frequency sweep signal, a resonant frequency. The electronic processor is configured to output, at the transducer, an output signal according to the resonant frequency.

Abstract: A lidar system including an integrated optical transmitter and receiver capable of transmitting light to optically scan the system's field of view (FOV) without employing moving parts and of detecting light produced by reflections of the transmitted light in the FOV. In an example, the integrated optical transmitter and receiver includes a two-dimensional array of semiconductor diodes supported on a common substrate. Each of the semiconductor diodes is individually configurable to operate in a plurality of modes including a light-emitting mode and a photodetector mode. The lidar system includes circuitry to apply forward and reverse electrical biases to different selected subsets of the semiconductor diodes to enable the light-emitting and photodetector modes, respectively. The lidar system may further include circuitry to generate a depth map of the FOV based on time-of-flight measurements performed using the integrated optical transmitter and receiver.

Abstract: A light source capable of scanning the field of view (FOV) thereof without employing moving parts. In an example embodiment, the light source includes an addressable array of semiconductor lasers provided with an optical FOV adaptor in which optical fibers are spatially arranged in a fanout configuration to provide suitable sampling spots within a relatively large FOV suitable for lidar-based or structured-light-based depth mapping. For example, by selectively firing different individual lasers of the laser array at different times in a raster pattern, the light source can effectively optically scan the FOV in a manner suitable for lidar applications. Different optical FOV adaptors can beneficially be used to enable the same laser array to optimally sample differently shaped FOVs typically encountered in different specific applications. Due to the non-mechanical scanning structure thereof, the laser source is well suited for mobile-platform applications, such as autonomous driving.

Abstract: A low clearance detection system for a vehicle. In one example, the system includes a first sensor configured to detect an object in front of the vehicle and generate an object clearance signal. The system includes a second sensor configured to detect a load height of a load of the vehicle and generate a load height signal. The system includes a third sensor configured to detect a distance between the third sensor to a ground surface and to generate a ground reference signal. The system also includes an electronic processor configured to receive the object clearance signal, the load height signal, and the ground reference signal. The electronic processor determines an object clearance threshold, a clearance height of the load, and a load collision condition when the clearance height exceeds the object clearance threshold. In response to determining the load collision condition, the electronic processor controls a vehicle system.

Abstract: A platform for visualization of traffic information at an observed roadway or traffic intersection converts data collected from sensors for rendering as dynamic animations on a virtual map of the observed roadway or traffic intersection. The platform parses and curates incoming sensor data from either a single or multiple sensors representing one or more objects at the observed roadway or traffic intersection, and translates at least location data of each object for correlation of the object's movement relative to the observed roadway or traffic intersection. The platform then generates dynamic animations of the movement of each object and displays the animations as an overlay on the virtual map.

Abstract: A framework for precision traffic analysis estimates vehicle queue length at an observed roadway and calculates vehicle delay for improvements in traffic flow efficiency at a corresponding traffic intersection. The framework identifies a traffic detection area for a roadway at or near the traffic intersection and detects objects in the traffic detection area from sensors located proximate to the roadway. The framework then analyzes sensor data to determine the efficiency of the traffic network and to determine adjustments to timing of various phases of the signal timing plan for the traffic intersection.

Abstract: A platform for visualization of traffic information at an observed roadway or traffic intersection converts data collected from sensors for rendering as dynamic animations on a virtual map of the observed roadway or traffic intersection. The platform parses and curates incoming sensor data from either a single or multiple sensors representing one or more objects at the observed roadway or traffic intersection, and translates at least location data of each object for correlation of the object's movement relative to the observed roadway or traffic intersection. The platform then generates dynamic animations of the movement of each object and displays the animations as an overlay on the virtual map.

Abstract: A framework for precision traffic analysis estimates dilemma zone activity to dynamically adjust phase cycle timing for improved efficiency of traffic flow at a roadway intersection. The framework identifies a traffic detection area at or near a traffic intersection, and detects objects in the traffic detection area from sensors located proximate to the traffic intersection. The framework then correlates lapsed phase cycle times for the traffic signal with associations between object characteristics and known speed characteristics for the roadway for a determination of whether there is dilemma zone activity for the remainder of that phase cycle. The framework then determines whether to adjust a timing of the current phase cycle.

Abstract: An augmented reality visualization framework for precision traffic analysis combines traffic data with content representative of physical-world characteristics, such as conditions in an intersection or roadway in which traffic activity occurs, and images of the intersection and roadway itself. The framework includes a visualization platform that enables display of the combined traffic data and content representing physical-world characteristics, and continual augmentations of such information in response to adjustments directed by users or automatically detected from actions such as user movement, other user manipulation, or movement of the visualization platform itself. The framework enables traffic applications such that a user can, when the platform is interfaced with intersection or roadway equipment, adjust machine activity or signal timing based upon the visualizations or data presented via the visualization platform.

Abstract: A framework for precision traffic analysis combines traffic sensor data from multiple sensor types, combining the strengths of each sensor type within various conditions in an intersection or roadway in which traffic activity occurs. The framework calibrates coordinate systems in images taken of the same area by multiple sensors, so that fields of view from one sensor system are transposed onto fields of view from other sensor systems to fuse the images taken into a combined detection zone, and so that objects are properly detected and classified for enhanced traffic signal control.

Abstract: A framework for precision traffic analysis combines traffic sensor data from multiple sensor types, combining the strengths of each sensor type within various conditions in an intersection or roadway in which traffic activity occurs. The framework calibrates coordinate systems in images taken of the same area by multiple sensors, so that fields of view from one sensor system are transposed onto fields of view from other sensor systems to fuse the images taken into a combined detection zone, and so that objects are properly detected and classified for enhanced traffic signal control.

Abstract: A framework for precision traffic analysis combines traffic sensor data from multiple sensor types, combining the strengths of each sensor type within various conditions in an intersection or roadway in which traffic activity occurs. The framework calibrates coordinate systems in images taken of the same area by multiple sensors, so that fields of view from one sensor system are transposed onto fields of view from other sensor systems to fuse the images taken into a combined detection zone, and so that objects are properly detected and classified for enhanced traffic signal control.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: A vehicular observation and detection apparatus and system incorporates a detection framework using video analysis to differentiate between motorized vehicles and bicycles for improved traffic flow and safety at intersections. The detection framework creates virtual zones overlaid on lanes of a roadway and analyzes input data representing objects in the virtual zones collected from one or more cameras positioned at or near the roadway.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

Abstract: A multi-object zonal traffic detection framework analyzes temporal and spatial information from one or more sensors in a classification engine that identifies and differentiates objects within a single identified traffic detection zone. The classification engine applies a whole scene analysis and an adaptive background zone detection model to classify cars, trucks, bicycles, pedestrians, incidents, and other objects within the single identified traffic detection zone and generates counts for each object type for traffic system management.