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公开(公告)号：EP3617749B1
公开(公告)日：2020-11-11
申请号：EP18192330.1
申请日：2018-09-03
申请人： Zenuity AB
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公开(公告)号：EP3862916A1
公开(公告)日：2021-08-11
申请号：EP20155564.6
申请日：2020-02-05
申请人： Zenuity AB
IPC分类号： G06K9/00
摘要： The present disclosure relates to a method performed by a vehicle road model system (1) for providing a confidence-determined road model (5) for a vehicle (2). The vehicle road model system determines (1001) based on derived localization data, a position and orientation, pose (20), of the vehicle in view of a digital map (3), wherein the vehicle pose is associated with an uncertainty pertinent the localization data and/or the digital map. The vehicle road model system further transforms (1002) - based on the vehicle pose - at least a portion of the digital map into an ego-vehicle coordinate system (4). Moreover, the vehicle road model system determines (1003) based on the vehicle pose and the digital map, a road model (5) in the ego-vehicle coordinate system, which road model (5) comprises one or more static elements (6) positioned in vicinity and ahead of the vehicle pose. Furthermore, the vehicle road model system determines (1004) - based on the uncertainty and the one or more static elements - a respective confidence area (7) surrounding the one or more static elements, wherein respective confidence area represents a region which with a predeterminable confidence level encompasses a real-world position of respective one or more static elements.
The disclosure also relates to a vehicle road model system in accordance with the foregoing, a vehicle comprising such a vehicle road model system, and a respective corresponding computer program product and non-volatile computer readable storage medium.-
公开(公告)号：EP3839434A1
公开(公告)日：2021-06-23
申请号：EP19218793.8
申请日：2019-12-20
申请人： Zenuity AB
摘要： A method for generating and updating digital maps using a plurality of passages along a road portion by at least one road vehicle is provided. Each road vehicle comprises a perception system having at least one sensor configured to monitor a surrounding environment of the vehicle. The method comprises obtaining positioning data and sensor data of each passage from the at least one road vehicle. The positioning data comprises a plurality of longitudinal positions of each passage within a plurality of segments of the road portion, and the sensor data comprises information about a surrounding environment of each road vehicle at each longitudinal position. Further, the method comprises forming a sub-map representation of the surrounding environment at each obtained longitudinal position based on the obtained sensor data, and estimating a longitudinal error for each obtained longitudinal position within each segment. The estimation is done by performing a numerical optimization of the longitudinal error of each obtained longitudinal position within a common segment based on a similarity level of the formed sub-map representations from the common segment. Further, the method comprises determining a new plurality of longitudinal positions of each road vehicle for each passage by applying the estimated longitudinal error on each corresponding obtained longitudinal position, and applying the determined new plurality of longitudinal positions on associated sensor data in order to generate a first layer of a map representation of the surrounding environment along the road portion.
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4.发明公开
公开(公告)号：EP3617749A1
公开(公告)日：2020-03-04
申请号：EP18192330.1
申请日：2018-09-03
申请人： Zenuity AB
发明人： GUSTAFSSON, Tony , STENBORG, Erik , KVARNSTRÖM, Mats , MAGHSOOD, Roza , SÖRSTEDT, Joakim , LÖFMAN, Andreas , GUO, Linlin
摘要： Described herein is a method and arrangement (11) for sourcing of location information, generating and updating maps (16) representing the location. From at least two road vehicle (12) passages at the location is obtained (1, 2) vehicle registered data on the surrounding environment from environment sensors and positioning data from consumer-grade satellite positioning arrangements and from at least one of an inertial measurement unit and a wheel speed sensor. The positioning data is smoothed (3) to establish continuous trajectories for the respective vehicles (12). Individual surrounding environment maps are created using the data from each respective vehicle (12) passage at the location. From the individual surrounding environment maps are identified submaps (15) sharing area segments. Pairs of submaps (15) sharing area segments are cross-correlated (6). The information from the pairwise cross-correlation (6) of submaps (15) is used for optimizing each submaps (15) offset relative a full map (16) of the surrounding environment and the submaps (15) are merged into the full map (16).
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