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公开(公告)号：US20180066957A1
公开(公告)日：2018-03-08
申请号：US15259954
申请日：2016-09-08
Applicant: HERE Global B.V.
Inventor： Matei STROILA , Bo XU , Jane MACFARLANE
CPC classification number: G01C21/3694 , G01C21/32 , G01C21/3446 , G08G1/0112 , G08G1/0129 , G08G1/0141
Abstract: An approach is provided for generating trajectory bundles for map data analysis. The approach involves receiving probe data associated with the bounded geographic area. The probe data are collected from sensors of a plurality of devices traveling in the bounded geographic area, and includes probe points indicating a position, a heading, a speed, a time, or a combination thereof. The approach also involves constructing a plurality of trajectories from the probe points to represent respective movement paths of said each of the plurality of devices. The approach further involves computing similarities among a plurality of curves represented by the plurality of trajectories. The approach further involves clustering the plurality of trajectories into trajectory bundles based on the similarities with each bundle representing a possible maneuver within the bounded geographic area. The approach further involves generating a map of the bounded geographic area based on the trajectory bundles.
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公开(公告)号：US20240142245A1
公开(公告)日：2024-05-02
申请号：US17977679
申请日：2022-10-31
Applicant: HERE Global B.V.
Inventor： Basel HASHISHO , Bo XU , Rohit GUPTA , Reinhard KOHN , Sebastian Hendrik VAN DE HOEF
CPC classification number: G01C21/3453 , G01C21/3874
Abstract: An approach is provided for stop classification and journey extraction from vehicle location trace data. The approach involves, for example, processing vehicle location trace data to determine a sequence of vehicle stop locations. The sequence of vehicle stop locations comprises a first stop location, a second stop location, and a third stop location in chronological order. The approach also involves determining a first route cost (e.g., a first route length) from the first stop location to the third stop location via the second stop location and a second route cost (e.g., a second route length) from the first stop location directly to the third stop location. The approach further involves determining a classification of the second stop location as either a task stop or a rest stop based, at least in part, on a comparison of the first route length and the second route length.
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公开(公告)号：US20240087448A1
公开(公告)日：2024-03-14
申请号：US17941580
申请日：2022-09-09
Applicant: HERE Global B.V.
Inventor： Rohit GUPTA , David JONIETZ , Bo XU , Ali SOLEYMANI , Reinhard Walter KÖHN
CPC classification number: G08G1/0133 , G06F16/29 , G06K9/6262 , G08G1/017
Abstract: An approach is provided for spatial aggregation for location based services. The approach involves, for example, determining a plurality of partitions for a geographic area. The approach also involves determining a set of destinations that is common to a first partition and a second partition of the plurality of partitions. The set of destinations are associated with a plurality of trips originating from first partition, the second partition, or a combination thereof. The approach further involves determining a statistical property of the plurality of trips between any of the set of destinations and the first partition, the second partition, or a combination thereof. The approach further involves merging the first partition with the second partition into the traffic analysis zone based on the statistical property.
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4.发明公开公开(公告)号：US20240085205A1
公开(公告)日：2024-03-14
申请号：US17941607
申请日：2022-09-09
Applicant: HERE Global B.V.
Inventor： David JONIETZ , Bo XU , Rohit GUPTA , Ali SOLEYMANI , Reinhard Walter KÖHN
CPC classification number: G01C21/3484 , G06N5/022
Abstract: An approach is provided for machine learning-based prediction of an estimated time of arrival (ETA) or any other trip characteristic. The approach involves, for example, receiving a request for an ETA (or any other trip characteristic). The request specifies an origin, a destination, and a time of departure. The approach also involves discretizing the origin to an origin ETA homogenous zone and the destination to a destination ETA homogenous zone. The approach further involves determining one or more features of one or more pre-computed k-shortest paths for an origin-destination (O-D) zone pair comprising the origin ETA homogenous zone and the destination ETA homogenous zone. The approach further involves providing the one or more features as an input to a trained machine learning to predict the ETA of the trip (or any other trip characteristic).
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5.发明公开公开(公告)号：US20230160705A1
公开(公告)日：2023-05-25
申请号：US17533877
申请日：2021-11-23
Applicant: HERE Global B.V.
Inventor： Bo XU , Rohit GUPTA , David JONIETZ , Ali SOLEYMANI
CPC classification number: G01C21/3461 , G06N5/04 , G06K9/6256 , G06K9/6277
Abstract: An approach is provided for linearizing a network of features for machine learning tasks. The approach involves, for instance, receiving a graph representation of a network of a plurality of features. For example, a plurality of vertices of the graph representation, an edge connecting two vertices of the plurality of vertices, or a combination thereof respectively represents the plurality of features. The approach also involves determining a linear order of the plurality of features based on a selected criterion. The approach further involves generating a vector representation of the plurality of features based on the linear order. The approach further involves using the vector representation as an input, an output, or a combination thereof of a machine learning model.
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Patent Agency Ranking
公开(公告)号：US20220292091A1
公开(公告)日：2022-09-15
申请号：US17197974
申请日：2021-03-10
Applicant: HERE Global B.V.
Inventor： Catalin CAPOTA , David JONIETZ , Ali SOLEYMANI , Bo XU , Moritz NEUN
IPC: G06F16/2458 , G06F16/29
Abstract: An approach is provided for compression of sparse data for machine learning or equivalent tasks. The approach involves, for instance, receiving data that is binned into a plurality of bins. The data, for instance, represents a spatial surface such as a geographic region. The approach also involves processing the data by applying a compression criterion to classify one or more bins of the plurality of bins as either data-containing bins or empty bins. The approach further involves establishing a space filling curve over the plurality of bins, wherein the space filling curve linearizes the plurality of bins according to a placement order. The approach further involves storing the data-containing bins of the plurality of bins in a compressed data structure based on the placement order of the space filling curve.
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7.发明申请公开(公告)号：US20180224293A1
公开(公告)日：2018-08-09
申请号：US15425531
申请日：2017-02-06
Applicant: HERE Global B.V.
Inventor： Bo XU , Muhammed MAS-UD HUSSAIN
CPC classification number: G01C21/3446 , G01C21/30 , G06F17/30958
Abstract: An approach is provided for filtering device location points in a sampled trajectory while maintaining path reconstructability. The approach involves determining a first location point in the sampled trajectory that is an unfiltered location point. The sampled trajectory includes device location points sampled by a device traversing a road network. The approach also involves determining a fastest alternative path from the first location point to a second location point. The approach further involves calculating a sampling time difference between a time at which the first location point was sampled and another time at which the second location point was sampled. The approach further involves designating the second location point as a next unfiltered location point when the sampling time difference is within a threshold value of a free-flow travel time calculated for the fastest alternative path. Otherwise, the second location point is designated as a filtered location point.
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公开(公告)号：US20170352262A1
公开(公告)日：2017-12-07
申请号：US15172897
申请日：2016-06-03
Applicant: HERE Global B.V.
Inventor： Bo XU , Tiffany BARKLEY , Andrew LEWIS , Jane MACFARLANE , Davide PIETROBON , Matei STROILA
IPC: G08G1/01
CPC classification number: G08G1/0133 , G08G1/0112
Abstract: An approach is provided for classifying a traffic jam from probe data. The approach involves receiving the probe data that is map-matched to a roadway on which the traffic jam is detected. The probe data is collected from one or more vehicles traveling the roadway. The approach also involves determining a jam area of the roadway based on the probe data. The jam area corresponds to one or more segments of the roadway affected by the traffic jam. The approach further involves determining a set of features indicated by the probe data from a portion of the probe data collected from the jam area. The approach further involves classifying, using a machine learning classifier, the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features.
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9.发明申请公开(公告)号：US20160247397A1
公开(公告)日：2016-08-25
申请号：US14629628
申请日：2015-02-24
Applicant: HERE Global B.V.
Inventor： Bo XU , Jane MACFARLANE
CPC classification number: G08G1/0125 , G08G1/012 , G08G1/0133 , G08G1/0141 , G08G1/052
Abstract: An approach is provided for predicting starting points and/or ending points for traffic jams in one or more travel segments. The approach involves processing and/or facilitating a processing of probe data associated with at least one travel segment to cause, at least in part, a generation of at least one speed curve with respect to a distance dimension and a time dimension, wherein the probe data includes speed information, and wherein the at least one speed curve indicates at least one previous starting point, at least one previous ending point, or a combination thereof for one or more previous traffic jams based, at least in part, on the speed information. The approach also involves processing and/or facilitating a processing of the at least one previous starting point, the at least one previous ending point, or a combination thereof to determine at least one starting point trend curve, at least one ending point trend curve, or a combination thereof with respect to the distance dimension and the time dimension. The approach further involves determining at least one predicted evolution of at least one starting point, at least one ending point, or a combination thereof for at least one traffic jam in the at least one travel segment based, at least in part, on the at least one starting point trend curve, the at least one ending point trend curve, or a combination thereof.
Abstract translation: 提供了一种用于预测一个或多个旅行段中的交通拥堵的起始点和/或终点的方法。 该方法包括处理和/或促进与至少一个行进段相关联的探测数据的处理，以至少部分地相对于距离维度和时间维度产生至少一个速度曲线，其中探针 数据包括速度信息，并且其中至少一个速度曲线至少部分地基于速度信息指示至少一个先前起始点，至少一个先前结束点或其组合，用于一个或多个先前的交通拥堵 。 该方法还涉及处理和/或促进对至少一个先前起始点，至少一个先前结束点或其组合的处理，以确定至少一个起始点趋势曲线，至少一个终点趋势曲线， 或其相对于距离尺寸和时间维度的组合。 所述方法进一步涉及至少部分地基于所述至少一个起始点，至少一个终点或其组合来确定所述至少一个行进段中的至少一个交通堵塞的至少一个预测演变 至少一个起点趋势曲线，至少一个终点趋势曲线或其组合。
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10.发明申请公开(公告)号：US20230067464A1
公开(公告)日：2023-03-02
申请号：US17410624
申请日：2021-08-24
Applicant: HERE Global B.V.
Inventor： David JONIETZ , Michael KOPP , Moritz NEUN , Bo XU , Ali SOLEYMANI
Abstract: An approach is provided for end-to-end traffic estimation. The approach involves, for instance, retrieving probe data or other sensor data collected from sensors of devices traveling in a geographic area. The approach also involves optionally aggregating the probe or sensor data into a sequence of frames. Each frame comprises a plurality of spatial cells representing the geographic area at a respective time interval. The probe or sensor data is spatially and temporally binned into the spatial cells. The approach further involves initiating an offline pre-processing pipeline to associate the probe or sensor data with road segments of a geographic database and/or otherwise determining a ground-truth traffic state for each frame or sensor data. The approach further involves training a machine learning model using the ground-truth traffic state to determine a predicted traffic state directly from input frames or sensor data.
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