Abstract: A computer implemented method of validating an output from a GNSS at a receiver including a fusion system comprising location sensors. A location estimate and a location error estimate are computed. A navigation update including a sensor location estimate and sensor location error estimate is also computed with the fusion system based on sensor measurements from the location sensors. A determination is made as to whether or not GNSS filters should be applied based at least on the location estimate, the sensor location estimate, and the sensor location error estimate. When GNSS filters should be applied, the location estimate and/or the location error estimate may be adjusted or rejected and a new navigation update may be computed with the fusion system based on the adjustment or rejection. When the GNSS filters should not be applied, the new navigation update is computed with the location estimate and the location error estimate.

Abstract: Disclosed herein an autonomous driving system includes a first sensor installed in a vehicle, having a field of view facing in front of the vehicle, and configured to acquire front image data; a second sensor selected from the group consisting of a radar and a light detection and ranging, installed in the vehicle, having a detection field of view facing in front of the vehicle, and configured to acquire forward detection data; a communicator configured to receive a high definition map at a current location of the vehicle from an external server; and a controller including a processor configured to process the high definition map, the front image data, and the forward detection data.

Abstract: A method for providing incentives based on geolocation of mobile devices. The method includes storing, by a server, data including merchant information of merchants and points of interest, and associated incentive information. The method includes determining, based on communication with user's device of a user, a first location of the mobile device. The method includes determining, based on the first location, a first subset of merchants and associated first subset of incentives. The method includes communicating merchant data, including information on the first subsets of merchants and incentives, to the mobile device. The method includes communicating to the mobile device, in response to a determination that the mobile device is inside a geofence associated with at least one of the first subset of merchants, additional information on the at least one of the first subset of merchants, the additional information comprising one or more related incentives.

Abstract: Among other things, techniques are described for receiving, from at least one sensor of a vehicle, a sensor measurement indicative of at least one of a sound or a vibration associated with a road element; identifying the road element based on a pattern in the sensor measurement; determining, based on the road element, a vehicle behavior for the vehicle; and controlling the vehicle to operate according to vehicle behavior.

Abstract: Systems and methods are disclosed for the development and management of curated navigational routes are disclosed. The curated navigational route can be a particular path of travel that is specifically designed for one or more users. The curated navigational routes are carefully constructed paths of travel that are custom defined by a route manager.

Abstract: A synthetic aperture radar signal analysis device 20 includes: an extraction unit 21 that extracts a stable reflection point from time-series data acquired through observation, by a synthetic aperture radar, of a region to be observed from a predetermined observing direction; a generation unit 22 that generates a cluster which is a collection of stable reflection points on the basis of the extracted stable reflection point corresponding to the predetermined observing direction; an association unit 23 that associates the generated cluster corresponding to the predetermined observing direction with a structure indicated by map data corresponding to the region to be observed; and a synthesis unit 24 that performs vector-synthesis of displacement rates for a plurality of the clusters each corresponding to the observing direction associated with the structure.

Abstract: A location estimating device has a processor that is configured to calculate a first estimated location of a vehicle using positional information representing the location of a vehicle and first map data overlapping with a first section of a vehicle traveling route, to calculate a second estimated location of the vehicle using positional information and second map data that overlaps with a second section of the traveling route, the first section and the second section having an overlapping section, and to assess whether or not the precision of the second estimated location satisfies a predetermined assessment criterion when the vehicle is traveling in the overlapping section from the first section toward the second section.

Abstract: An Real-Time Kinematic (RTK) and/or Differential GNSS (DGNSS) system is disclosed in which correction data from a plurality of reference stations is provided to the mobile device. A selection of reference stations (from which correction data is provided to the mobile device) can be made based on factors such as the approximate location of the mobile device, geometry of the reference stations, and/or other factors. The mobile device can combine the correction data from the plurality of reference stations in different ways to determine an accurate position fix for the mobile device, without interpolating correction data from the plurality of reference stations.

Abstract: Locations for mobile computers may be adaptively determined in a system which includes a server, a set of mobile computers, and an administrator computer. In such a system, the set of mobile computers may each be programmed with instructions operable to, when executed, transmit multiple forms of location information to the server. Additionally, the server may be programmed with a set of location determination routines and these routines may be used in determining a location for each of the mobile computers from the set of mobile computers. These locations may then be used to populate an interface of the administrator computer with icons at positions corresponding to the mobile computers' locations.

Abstract: An autonomous driving system includes an electronic control unit configured to generate, based on a target route, a target path in a predetermined coordinate system and a speed plan specifying a passage time at a control point on the target path, and rebuild, based on an actual speed of a vehicle, the speed plan when an operation intervention is performed during autonomous driving performed by autonomous driving control for causing the vehicle to travel along the target path according to the speed plan, the operation intervention changing a braking force acting on the vehicle, and perform the autonomous driving control by using an actuator mounted on the vehicle.

Abstract: Methods and systems are disclosed for presenting user specific information based on mobile device proximity to short-range wireless technology beacons. For example, by determining the proximity of a mobile device to a short-range wireless technology beacon, user specific information may be displayed on a user interface such that a user may have easy access to user specific information without the need to rely on their mobile device for such access, thereby conserving mobile device battery life and improving the experience of the user.

Abstract: A self-position correction method and/or a self-position correction device use a coordinate of the axis parallel to a front-rear direction of a vehicle as a longitudinal coordinate, calculate a corrected vehicle speed by adding a vehicle speed to a correction amount set based on a longitudinal correction amount obtained by subtracting a value of the longitudinal coordinate of a position of a target object detected by a detection unit from a value of the longitudinal coordinate of a position of a target object registered on a map data, and correct a position of the vehicle on the map data by estimating a position of the vehicle based on sequential integration of a calculated movement amount of the vehicle based on the corrected vehicle speed and a yaw rate of the vehicle.

Abstract: A method performed by a wireless device (110, 210, 410, 1200) is disclosed. The method comprises sending (801), to a network node (120, 115, 215, 220, 225, 460), a request for reference station transfer information. The method comprises obtaining (802) the reference station transfer information for at least one pair of satellites (235, 240). The method comprises determining (803) an integer ambiguity solution associated with a new reference station (230B) based on the obtained reference station transfer information and an integer ambiguity solution associated with a current reference station (230A).

Abstract: Techniques are described including displaying an interface associated with a computing device, the interface being configured to present a form including a text entry box, receiving data from an activity information pipeline associated with a self-reporting service, the activity information pipeline having a source of activity information associated with a tool configured to geotag the activity information and another source of associated with a mobile sensor configured to capture other activity information geotagged by the tool, the other activity information being processed by the self-reporting service to deprioritize a suggestion over another suggestion, displaying, in response to selection of the text entry box, a suggestion indicative of a journey and identified as prioritized and presented proximate to the center of the interface of the display device, and dynamically adjusting the suggestion while prioritizing display of the suggestion over a generic suggestion.

Abstract: A computing device determines a disaggregated solution vector of a plurality of variables. A first value is computed for a known variable using a predefined density distribution function, and a second value is computed for an unknown variable using the computed first value, a predefined correlation value, and a predefined aggregate value. The predefined correlation value indicates a correlation between the known variable and the unknown variable. A predefined number of solution vectors is computed by repeating the first value and the second value computations. A solution vector is the computed first value and the computed second value. A centroid vector is computed from solution vectors computed by repeating the computations. A predefined number of closest solution vectors to the computed centroid vector are determined from the solution vectors. The determined closest solution vectors are output.

Abstract: A system coupled to a packet-based network is configured to generate geo-blocks for location-based information services. Each of the geo-blocks corresponds to a geographical region within a geographical area and has at least one border defined by a real-world object. The system is configured to obtain geo data related to real-world objects including transportation routes and natural boundaries in the geographical area, partition the geographical area into initial geo-blocks using the geo data, process a plurality of information requests with respect to at least some of the initial geo-blocks and with respect to initial geo-fences associated with a plurality of points of interests (POIs) to generate entries in one or more databases, and enrich at least some of the initial geo-block with block-level meta data derived from the entries in the one or more databases to form enriched geo-blocks that are highly indicative of location dependent attributes such as intention and demographics.

Abstract: Techniques and methods for determining a distance between a point within an environment and a reference line are discussed herein. For instance, a vehicle may be navigating. While navigating, the vehicle may receive a reference line that represents a road segment and determine various regions relative to the reference line. Additionally, the vehicle may generate sensor data representing the environment and identify an object using the sensor data. The vehicle may then determine that a location of the object corresponds to a region from the regions. Based on the region, the vehicle may determine a rule for identifying the distance between the vehicle and the reference line. The vehicle may then determine the distance using the rule, the location of the object, and the reference line. Additionally, the vehicle may determine an action for the vehicle to perform that is based on the distance.

Abstract: To provide a work machine that can maintain the construction precision of semi-automatic control irrespective of excavation depths and differences in soil nature. A controller acquires soil-nature information on the basis of an operation command given to a work implement, a bucket-claw-tip position outputted from a bucket-position measuring device, and a drive load of the work implement outputted from a load measuring device; generates a soil-nature map on the basis of the bucket-claw-tip position, and the soil-nature information; calculates an estimated load that is an estimate of an excavation load on the basis of the soil-nature map and a bucket-claw-tip target position; and corrects the operation command in accordance with the estimated load.

Abstract: A computer-implemented method may include monitoring an age of a tile of a map, where the map includes multiple tiles including the tile. The method may also include, based on the age exceeding a threshold age, determining that the tile of the map is to be updated, and receiving a location indicator from a vehicle. The method may additionally include transmitting an update message to a vehicle traversing a track within the tile as indicated by the location indicator, where the update message includes instructions to cause the vehicle to gather and submit sensor data to a computing system. The method may also include receiving the sensor data from the vehicle, and updating the tile of the map based on the received sensor data.

Abstract: The present invention relates to a method for updating strapdown inertial navigation solutions based on a launch-centered earth-fixed (LCEF) frame (g frame). The present invention uses the g frame as a navigation reference frame of a medium-to-short-range surface-to-surface missile. This is beneficial to establish a relative relationship between the missile and the ground so as to keep the same missile parameters required by a missile control and guidance system. The calculation of a navigation algorithm in the g frame is moderate, which is suitable for an embedded system.

Abstract: Provided herein is a system and method of a vehicle. The system comprises one or more sensors, processors, maps, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: monitoring a location of the vehicle while driving; detecting a sign while the vehicle is driving; capturing, frame-by-frame, data of the sign until the sign disappears from a field of view of the sensor; synchronizing each frame of the data with the location of the vehicle; determining a location of the sign based on the frame-by-frame data; in response to determining, at a frame immediately before the sign disappears from the field of view of the sensor, that the vehicle is driving towards the sign, uploading the detected sign and the location of the sign onto the one or more maps; and implementing a driving action based on the sign.

Abstract: A method can include receiving sensor data, receiving satellite observations, determining a positioning solution (e.g., PVT solution, PVA solution, kinematic parameters, etc.) based on the sensor data and the satellite observations. A system can include a sensor, a GNSS receiver, and a processor configured to determine a positioning solution based on readings from the sensor and the GNSS receiver.

Abstract: Embodiments herein include a method executable by a processor coupled to a memory. The processor is local to a vehicle can operable to determine initial location and direction information associated with the vehicle at an origin of a trip request. The processor receives one or more frames captured while the vehicle is traveling along a navigable route relative to the trip request and estimates an execution time for each of one or more computations respective to an analyzing of the one or more frames. The processor, also, off-loads the one or more computations to processing resources of a cloud-based system that is in communication with the processor of the vehicle in accordance with the corresponding execution times.

Abstract: Locations for mobile computers may be adaptively determined in a system which includes a server, a set of mobile computers, and an administrator computer. In such a system, the set of mobile computers may each be programmed with instructions operable to, when executed, transmit multiple forms of location information to the server. Additionally, the server may be programmed with a set of location determination routines and these routines may be used in determining a location for each of the mobile computers from the set of mobile computers. These locations may then be used to populate an interface of the administrator computer with icons at positions corresponding to the mobile computers' locations.

Abstract: A method of mapping and localization is disclosed that includes, reconstructing a point cloud and a camera pose based on VSLAM, synchronizing the camera pose and a GPS timestamp at a first set of GPS coordinate points and transforming the first set of GPS coordinate points corresponding to the GPS timestamp into a first set of ECEF coordinate points. The method also includes determining a translation and a rotation between the camera pose and the first set of ECEF coordinate points, transforming the point cloud and the camera pose into a second set of ECEF coordinates based on the translation and the rotation and transforming the point cloud and the camera pose into a second set of GPS coordinate points. The method further includes constructing and storing a key-frame image, a key-frame timestamp and a key-frame GPS based on the second set of GPS coordinate points.

Abstract: Embodiments of the present disclosure disclose a method for calibrating a relative pose, a device, and a medium. The method includes: obtaining first point cloud data of a scene collected by the laser radar in an automatic driving mobile carrier and first pose data collected by the navigation positioning system in the automatic driving mobile carrier; and determining the relative pose between the laser radar and the navigation positioning system based on the first point cloud data, the first pose data, second point cloud data pre-collected by a laser scanner in the scene and second pose data pre-collected by a positioning device in the scene.

Abstract: The preferred embodiments of the present invention are directed to methods and systems for dynamic route estimation and prediction using discrete sampled location updates from various mobile devices for the purpose of providing a graphical representation of a mobile device's route along a known network path of map data. The embodiments also provide supplemental route metrics, such as traveled distance, elapsed time, etc., and the capability to assign destination points for the purpose of providing the ability to modify location update points in an application, such as a route planner, and/or to store the dynamically generated route based on various preferences for later retrieval.

Abstract: A nearshore real-time positioning and mapping method for an unmanned surface vehicle with multiple distance measuring sensors comprises: acquiring predicted gesture data of the unmanned surface vehicle by an inertia measurement unit; acquiring radar point cloud data by a laser radar, projecting the radar point cloud data to a depth map, and reserving ground points and break points on the depth map; dividing the depth map into six sub depth maps, obtaining a feature point set via a curvature of each laser point, and converting all the feature point sets of the laser radar into coordinates of the unmanned surface vehicle; obtaining a relative gesture transformation matrix of the current unmanned surface vehicle via the radar cloud point data of two adjacent frames; accruing multiple factors, and optimizing a gesture of the unmanned surface vehicle in form of a factor pattern; and constructing a three-dimensional cloud point pattern.

Abstract: A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

Abstract: Technologies for sharing route navigation data in a community cloud include a mobile navigation device of a vehicle and a remote mobile navigation device of a remote vehicle. The mobile navigation device generates sensor data associated with a current route of the vehicle and determines whether a reference traffic event occurs within a segment of the current route of the vehicle. In response to a determination that a reference traffic event occurs, the mobile navigation devices transmits route update data to the remote mobile navigation device. Based on the route update data, the remote mobile navigation device updates a current route of the remote vehicle to avoid the reference traffic event within a corresponding segment of the current route of the remote vehicle. The mobile navigation device may also transmit the sensor data to a community compute device, which may transmit route update data to the remote mobile navigation device.

Abstract: Neighbor list adaptive mapping may be provided. A request to a client device to provide a client device view of a network may be sent periodically at a time interval. A length of the time interval may be dependent on a condition at the client device and identity data may be associated with the client device. In response to sending the request to the client device, data corresponding to the client device view of the network may be received. Then, in response to receiving the data, a map of the network may be updated based on the received data corresponding to the client device view of the network. The map may be associated with the identity data associated with the client device.

Abstract: A method of controlling a plurality of lighting devices is disclosed. The method comprises obtaining a 360 degree panoramic image, rendering the 360 degree panoramic image at least partially on an image rendering device, obtaining positions of the plurality of lighting devices relative to the image rendering device, mapping the 360 degree panoramic image onto the plurality of lighting devices based on the positions of the plurality of lighting devices, such that each lighting device is associated with a part of the 360 degree panoramic image, determining, for each lighting device, a light setting based on an image characteristic of the part of the 360 degree image, and controlling each lighting device according to the respective light setting.

Abstract: Disclosed are a method and an apparatus for determining a location of a vehicle and a system for controlling driving.

Abstract: A method, a device, and a computer-readable storage medium with instructions for determining the location of a datum detected by a transportation vehicle wherein at least one pose estimation is ascertained. An uncertainty of the at least one pose estimation is determined wherein the uncertainty of the pose estimation includes a process of scaling an uncertainty estimation of the pose estimation, wherein the scaling process is based on a comparison of the pose estimation with a priori information. The at least one pose estimation is fused solely with at least one additional pose estimation with a weighting according to the uncertainties.

Abstract: In one embodiment, a match application identifies an edge corresponding to a road segment based on an observational point specifying an estimated position and an estimated heading. The match application performs search operations on a road network graph based on the estimated position to identify multiple candidate edges. For a first candidate edge, the match application computes a first quality level based on at least a distance between the estimated position and the first candidate edge and an angle between the estimated heading and a direction associated with the first candidate edge. Subsequently, the match application determines that the first quality level indicates that the first candidate edge has a higher quality than any other candidate edge. Finally, the match application transmits the first candidate edge to an application that associates content specified in relation to the estimated position with the first candidate edge.

Abstract: A method, apparatus, computer program or system includes obtaining fingerprints including a piece of position information and gathered in a venue; determining a first metric based on the fingerprints indicative of a quality value of the obtained fingerprints that indicates for each piece of position information of the fingerprints whether or not the quality and/or a quantity of the obtained fingerprints with respect to the piece of position information is sufficient; determining a second metric based on the obtained fingerprints indicative of a quality value of an infrastructure of the venue, the fingerprints are gathered from one or more radio nodes of the infrastructure, and the second metric indicates for each of the pieces of position information of each of the respective fingerprints whether or not the quality of the infrastructure is sufficient; determining a third metric indicative of an evaluation of the quality of the infrastructure of the venue based on the second metric; and outputting the first me

Abstract: A method and a system of a two-step object data processing by a vehicle and a database for generating and updating a digital road description database containing object-based information about road objects is disclosed. First, the server database comprises fourth data sets and generates and forwards first data sets to the vehicle, which are related to the area of interest of the vehicle. The vehicle is collecting a plurality of ambient data sets at least along a specific section of its path. It is performing the first step of object data processing by evaluating a selection of the plurality of ambient data sets and generating at least one second data set comprising at least location information and detailed object-based information. It further generates third data sets containing differences between the object-based information of the second data sets and the object-based information of the first data sets and forwards the third data sets to the server database.

Abstract: A method for wrong-way driver detection, including a step of reading map data mapping road segments of a road network negotiable by a vehicle, a step of determining a plurality of instantaneous particles using a measured instantaneous position of the vehicle, one particle representing an assumed position of the vehicle and a weighting assigned to the assumed position, a step of reading in a plurality of previously filtered particles representing particles filtered in a preceding step of filtering using a particle filter, a step of determining a set of plausible road segments, using the plurality of instantaneous particles and the plurality of previously filtered particles, and a step of filtering the plurality of instantaneous particles based on the set of plausible road segments, using the particle filter, to determine a plurality of filtered particles.

Abstract: The position of a moving object is estimated with high accuracy using landmark information, and highly accurate state estimation is performed appropriately at high speed. A landmark detection unit obtains a distance between the moving object and each of two or more landmarks as landmark distance information based on observation data obtained by an observation obtaining unit. A candidate area obtaining unit determines a candidate area for a position of the moving object based on the landmark distance information obtained by the landmark detection unit, and obtains candidate area information indicating the determined candidate area. A state estimation unit estimates an internal state of the moving object based on the observation data, the landmark distance information, and the candidate area information to obtain moving object internal state estimation data, and estimates the environmental map based on the candidate area information and the landmark distance information to obtain environmental map data.

Abstract: In an embodiment, a method for determining a speed of a vehicle in a dead-reckoning system includes measuring a centripetal acceleration, using an accelerometer, of the vehicle traversing a curved path on a plane of travel. The method also includes measuring an angular velocity, using a gyroscope, of the vehicle. The speed of the vehicle is calculated from the centripetal acceleration and the angular velocity.

Abstract: Systems and methods are provided for distributing a crowdsourced sparse map for autonomous vehicle navigation. In one implementation, a method of generating a road navigation model for use in autonomous vehicle navigation may include receiving navigation information associated with a common road segment from a plurality of vehicles; storing the navigation information associated with the common road segment; generating at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information; and distributing the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating along the common road segment. The autonomous vehicle road navigation model may include at least one line representation of a road surface feature extending along the common road segment, and each line representation may representing a path along the common road segment substantially corresponding with the road surface feature.

Abstract: A lane keeping control device performs lane keeping control to allow a host vehicle (V) to travel in a travel lane (21) in which the host vehicle is currently traveling. The lane keeping control device continues to perform the lane keeping control such that the host vehicle travels toward a branch road (30) ahead, when the branch road (30) has been detected, and a turn signal (WL) has been activated to indicate a direction toward the branch road (30).

Abstract: A system and method for feeding back and incorporating the uncertainty distribution of the state estimate output by the INS in the image geo-registration process to handle larger navigation errors, provide a full six degree of freedom position and attitude absolute navigation update for the navigation system and provide a more accurate update for autonomous aerial, underwater or ground vehicles. Generating the update simultaneously for multiple images may provide a more robust solution to address any observability issues that may be present, the ability to fuse different sensor modalities and in general more accurate updates. Key frames may be used to improve the computational efficiency of the method.

Abstract: Example embodiments include determining a map of an environment of a robotic vehicle. The map includes locations of a plurality of mapped landmarks within the environment and a false detection source region within the environment. The embodiments further include detecting a plurality of candidate landmarks, and determining which of the detected candidate landmarks correspond to one of the plurality of mapped landmarks and which correspond to false detections. The embodiments additionally include estimating a pose of the robotic vehicle within the environment. The embodiments further include determining which of the detected candidate landmarks determined to correspond to false detections fall within the false detection source region. The embodiments still further include determining a confidence level of the pose estimate based on which of the detected candidate landmarks determined to correspond to false detections fall within the false detection source region.

Abstract: Robotic vision-based framework wherein an on-board camera device is used for scale estimation. Unlike conventional scale estimation methods that require inputs from more than one or more sensors, implementations include a system and method to estimate scale online solely, without any other sensor, for monocular SLAM by using multirotor dynamics model in an extended Kalman filter framework. This approach improves over convention scale estimation methods which require information from some other sensors or knowledge of physical dimension of an object within the camera view. An arbitrary scaled position and an Euler angle of a multirotor are estimated from vision SLAM (simultaneous localization and mapping) technique. Further, dynamically integrating, computed acceleration to estimate a metric position. A scale factor and a parameter associated with the multirotor dynamics model is obtained by comparing the estimated metric position with the estimated arbitrary position.

Abstract: A system including a processor and a memory, the memory including instructions to be executed by the processor to determine map data, determine uncalibrated LIDAR data, determine a location of a vehicle in the map data by combining the map data with the uncalibrated LIDAR data, and operate the vehicle based on the location of the vehicle in the map data.

Abstract: Method and apparatus are disclosed for managing location uncertainty areas for a passive start system of a vehicle. An example vehicle includes antenna modules for determining signal strengths of communication with a mobile device. The example vehicle also includes a wireless module configured to, when the mobile device is in a location uncertainty area (LUA), determine first and second location predictors. The wireless module is also configured to enable passive start when the first and second location predictors both indicate the mobile device is inside the vehicle. The wireless module is further configured to disable passive start if the mobile device is outside the vehicle.

Abstract: A mobile navigation system includes: a radar antenna carried by the vehicle, and emitting first and second sensing beams at first and second time points, respectively; first and second retro-directive antennas or beam-reflecting objects disposed at first and second positions, respectively, and being a specific distance from each other; and a processing device electrically coupled to the radar antenna. The first and second retro-directive antennas or beam-reflecting objects respectively return first and second retro waves corresponding to a direction of the first sensing beam, and respectively return third and fourth retro waves corresponding to a direction of the second sensing beam. The processing device receives the first, second, third and fourth retro waves, and determines a moving direction of the vehicle according to the first, second, third and fourth retro waves and the specific distance.

Abstract: This application discloses a computing system to implement vehicle localization in an assisted or automated driving system. The computing system can receive an environmental model populated with measurement data captured by sensors mounted in a vehicle. The computing system can detect a location of the vehicle relative to the map data based on a correlation between the measurement data and the map data. The computing system can detect landmarks in the map data and switch to sparsely-populated map data from higher-definition map data for subsequent location detections. When the computing system does not detect a vehicle location, the computing system can track movement of the vehicle based on subsequent measurement data in the environmental model. After reacquiring a vehicle location, the computing can realign the tracked movement of the vehicle and measured data to the map data or modify the map data to include the tracked data.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a localization method includes receiving sensor data relating to an environment of a vehicle, the sensor data including a plurality of sensor returns associated with objects in the environment, each of the sensor returns having a plurality of corresponding attributes, and constructing a first plurality of sensor data groups, each including a self-consistent subset of the plurality of sensor returns based on their corresponding attributes. The method further includes defining, for each of the first plurality of sensor data groups, a first set of features, wherein each feature is based on at least one of the corresponding attributes and each has an associated feature location, and determining, with a processor, a feature correlation between the first set of features and a second, previously determined set of features.