Abstract: A driver assistance method includes determining, with a horizon provider module, a first path comprising a first road segment and a second road segment based on a position of a vehicle and a predetermined horizon distance. A second path comprising the first road segment and a third road segment is determined based on the position of the vehicle and the predetermined horizon distance. Path data characterizing the first path, the second path, a position of the vehicle relative to the first path, and a position of the vehicle relative to the second path is then transmitted to a reconstructor module.

Abstract: According to one aspect, a distance determination system for a vehicle includes an apparatus for generating and displaying a pattern generated by a holographic encoded medium in operable communication with an actuator and in communication with an electromagnetic radiation source configured to produce coherent electromagnetic waves. The distance determination system also includes an imager and a distance determination module in communication with the imager. The imager is configured to acquire image data representative of a field of view from the vehicle. The distance determination module is configured to locate at least one feature of the pattern in the image data and determine an estimated distance between the vehicle and the at least one feature based at least in part on a known position of the apparatus, a known position of the imager, and a layout of the pattern.

Abstract: A method is disclosed for improved target grouping of sensor measurements in an object detection system. The method uses road curvature information to improve grouping accuracy by better predicting a new location of a known target object and matching it to sensor measurements. Additional target attributes are also used for improved grouping accuracy, where the attributes includes range rate, target cross-section and others. Distance compression is also employed for improved grouping accuracy, where range is compressed in a log scale calculation in order to diminish errors in measurement of distant objects. Grid-based techniques include the use of hash tables and a flood fill algorithm for improved computational performance of target object identification, where the number of computations can be reduced by an order of magnitude.

Abstract: A method that utilizes high-definition street level images provided by a network of stationary traffic cameras to identify potential hazards or concerns located beyond the range of vehicle mounted devices, and to provide an advanced warning or to take some other remedial action in response thereto. In one embodiment, the method uses multiple items taken from the street level images to corroborate a potential concern before saving that concern to a concern profile where the concern is linked or otherwise associated with a particular geographic zone. By taking remedial actions well in advance of a potential concern, the method provides more opportunity to adjust or otherwise address the potential concern, which can be particularly advantageous when the host vehicle is being operated in an automated driving mode.

Abstract: A method of detecting and tracking objects using multiple radar sensors. Objects relative to a host vehicle are detected from radar data generated by a sensing device. The radar data includes Doppler measurement data. Clusters are formed, by a processor, as a function of the radar data. Each cluster represents a respective object. Each respective object is classified, by the processor, as stationary or non-stationary based on the Doppler measurement data of each object and a vehicle speed of the host vehicle. Target tracking is applied, by the processor, on an object using Doppler measurement data over time in response to the object classified as a non-stationary object; otherwise, updating an occupancy grid in response to classifying the object as a stationary object.

Abstract: A system and method for selectively reducing or filtering data provided by one or more vehicle mounted sensors before using that data to detect, track and/or estimate a stationary object located along the side of a road, such as a guardrail or barrier. According to one example, the method reduces the amount of data by consolidating, classifying and pre-sorting data points from several forward looking radar sensors before using those data points to determine if a stationary roadside object is present. If the method determines that a stationary roadside object is present, then the reduced or filtered data points can be applied to a data fitting algorithm in order to estimate the size, shape and/or other parameters of the object. In one example, the output of the present method is provided to automated or autonomous driving systems.

Abstract: A method that utilizes high-definition street level images provided by a network of stationary traffic cameras to identify potential hazards or concerns located beyond the range of vehicle mounted devices, and to provide an advanced warning or to take some other remedial action in response thereto. In one embodiment, the method uses multiple items taken from the street level images to corroborate a potential concern before saving that concern to a concern profile where the concern is linked or otherwise associated with a particular geographic zone. By taking remedial actions well in advance of a potential concern, the method provides more opportunity to adjust or otherwise address the potential concern, which can be particularly advantageous when the host vehicle is being operated in an automated driving mode.

Abstract: A method of detecting and tracking objects using multiple radar sensors. Objects relative to a host vehicle are detected from radar data generated by a sensing device. The radar data includes Doppler measurement data. Clusters are formed, by a processor, as a function of the radar data. Each cluster represents a respective object. Each respective object is classified, by the processor, as stationary or non-stationary based on the Doppler measurement data of each object and a vehicle speed of the host vehicle. Target tracking is applied, by the processor, on an object using Doppler measurement data over time in response to the object classified as a non-stationary object; otherwise, updating an occupancy grid in response to classifying the object as a stationary object.

Abstract: According to one aspect, a distance determination system for a vehicle includes an apparatus for generating and displaying a pattern generated by a holographic encoded medium in operable communication with an actuator and in communication with an electromagnetic radiation source configured to produce coherent electromagnetic waves. The distance determination system also includes an imager and a distance determination module in communication with the imager. The imager is configured to acquire image data representative of a field of view from the vehicle. The distance determination module is configured to locate at least one feature of the pattern in the image data and determine an estimated distance between the vehicle and the at least one feature based at least in part on a known position of the apparatus, a known position of the imager, and a layout of the pattern.

Abstract: An apparatus for generating and displaying a projected digital image includes an actuator, a holographic encoded medium with a holographic pattern, a light source, and a controller. The holographic encoded medium is disposed in operable communication with the actuator. The light source is configured to produce a coherent light disposed in optical communication with the holographic encoded medium. The controller is operable to control synchronization of the coherent light from the light source with a position of the holographic encoded medium as driven by the actuator to produce the projected digital image on a projection surface based on directing the coherent light to different portions of the holographic pattern at different times.

Abstract: A system and method for providing visual assistance through a graphic overlay super-imposed on a back-up camera image for assisting a vehicle operator when backing up a vehicle to align a tow ball with a trailer tongue. The method includes providing camera modeling to correlate the camera image in vehicle coordinates to world coordinates, where the camera modeling provides the graphic overlay to include a tow line having a height in the camera image that is determined by an estimated height of the trailer tongue. The method also includes providing vehicle dynamic modeling for identifying the motion of the vehicle as it moves around a center of rotation. The method then predicts the path of the vehicle as it is being steered including calculating the center of rotation.

Abstract: Methods and systems are provided for measurement association in vehicles. An object proximate a vehicle is identified. Measurements or classifications are obtained via one or more sensors. A first tracking gate is generated that is based at least in part on a characteristic of one of the sensors used to obtain the measurements or classifications. A second tracking gate is generated that is based at least on part on the first tracking gate and a measurement history.

Abstract: A method and system for localizing a vehicle in a digital map includes generating GPS coordinates of the vehicle on the traveled road and retrieving from a database a digital map of a region traveled by the vehicle based on the location of the GPS coordinates. The digital map includes a geographic mapping of a traveled road and registered roadside objects. The registered roadside objects are positionally identified in the digital map by longitudinal and lateral coordinates. Roadside objects in the region traveled are sensed by the vehicle. The sensed roadside objects are identified on the digital map. A vehicle position on the traveled road is determined utilizing coordinates of the sensed roadside objects identified in the digital map. The position of the vehicle is localized in the road as a function of the GPS coordinates and the determined vehicle position utilizing the coordinates of the sensed roadside objects.

Abstract: Methods and systems are provided for making lane determinations as to a roadway on which the vehicle is travelling. A determination is made as to a lane of a roadway in which a vehicle is travelling. An identification is made as to an adjacent lane that is adjacent to the lane in which the vehicle is travelling. An assessment is made as to a drivability of the adjacent lane.

Abstract: A combination includes a vehicle and an apparatus disposed in the vehicle for generating and displaying a predefined light pattern. The apparatus includes an actuator, a light source productive of collimated light disposed in operable communication with the actuator, and an optical beam shaper disposed in optical communication with the light source. The optical beam shaper is operable to transform collimated light from the light source into non-collimated light productive of a predefined light pattern on a projection surface.

Abstract: A method to selectively prevent a vehicle from resuming a vehicle set speed stored in memory of a cruise control system includes monitoring a vehicle speed, determining that the vehicle speed indicates operation in a low speed range, determining a threshold slow zone maneuver based upon the vehicle speed substantially remaining in the low speed range through a predetermined duration, and inhibiting resumption of the vehicle set speed based upon the threshold slow zone maneuver.

Abstract: A vehicle system and method that estimates or approximates the mass of a vehicle so that a more accurate vehicle mass estimate can be made available to other vehicle systems, such as an adaptive cruise control (ACC) system or an automated lane change (LCX) system. In an exemplary embodiment, the method compares an actual acceleration of the vehicle to an expected acceleration while the vehicle is under the control of an automated acceleration event. The difference between these two acceleration values, along with other potential input, may then be used to approximate the actual mass of the vehicle in a way that takes into account items such as passengers, cargo, fuel, etc. Once an accurate vehicle mass estimate is generated, the method may make this estimate available to other vehicle components, devices, modules, systems, etc. so that their performance can be improved.

Abstract: A system and method designed to improve sensor visibility for a host vehicle operating in an autonomous driving mode when one or more forward-looking sensors are being occluded or obstructed. According to an exemplary embodiment, when a forward-looking object detection sensor is being obstructed by a target vehicle located closely ahead of the host vehicle, the method determines if lateral movement by the host vehicle within its own lane is appropriate to improve sensor visibility around the target vehicle. If lateral movement is deemed appropriate, the method generates lateral movement commands that dictate the direction and distance of the lateral movement by the host vehicle. This may enable the object detection sensors to at least partially see around the obstructing target vehicle and improve the preview distance of the sensors.

Abstract: A method and tools for virtually aligning object detection sensors on a vehicle without having to physically adjust the sensors. A sensor misalignment condition is detected during normal driving of a host vehicle by comparing different sensor readings to each other. At a vehicle service facility, the host vehicle is placed in an alignment target fixture, and alignment of all object detection sensors is compared to ground truth to determine alignment calibration parameters. Alignment calibration can be further refined by driving the host vehicle in a controlled environment following a leading vehicle. Final alignment calibration parameters are authorized and stored in system memory, and applications which use object detection data henceforth adjust the sensor readings according to the calibration parameters.

Abstract: A method for selecting an anchor lane for tracking in a vehicle lane tracking system. Digital map data and leading vehicle trajectory data are used to predict lane information ahead of a vehicle. Left and right lane boundary markers are also detected, where available, using a vision system. The lane marker data from the vision system is combined with the lane information from the digital map data and the leading vehicle trajectory data in a lane curvature fusion calculation. The left and right lane marker data from the vision system are also evaluated for conditions such as parallelism and sudden jumps in offsets, while considering the presence of entrance or exit lanes as indicated by the map data. An anchor lane for tracking is selected based on the evaluation of the vision system data, using either the fused curvature calculation or the digital map and leading vehicle trajectory data.