-
公开(公告)号：EP4160154A1
公开(公告)日：2023-04-05
申请号：EP21200267.9
申请日：2021-09-30
发明人： COLLING, Pascal , CREMER, Peet
IPC分类号： G01C21/36
摘要： Another computer implemented method for estimating lanes for a vehicle may include the following steps carried out by computer hardware components: determining measurement data at a location of the vehicle using a sensor mounted at the vehicle; transforming the measurement data of the sensor into a global coordinate system to obtain transformed measurement data; and estimating lanes at the location for the vehicle based on the transformed measurement data.
-
公开(公告)号：EP4160153A1
公开(公告)日：2023-04-05
申请号：EP21200261.2
申请日：2021-09-30
发明人： COLLING, Pascal , CREMER, Peet
IPC分类号： G01C21/36
摘要： A computer implemented method for estimating lanes for a vehicle may include the following steps carried out by computer hardware components: determining a first preliminary estimate of lanes based on a plurality of lane markings at a location of the vehicle; determining a second preliminary estimate of lanes based on a plurality of trails of objects at the location of the vehicle; comparing the first preliminary estimate of lanes and the second preliminary estimate of lanes; and determining a final estimate of lanes at the location of the vehicle based on the comparing.
-
公开(公告)号：EP4138051A1
公开(公告)日：2023-02-22
申请号：EP21191933.7
申请日：2021-08-18
发明人： ARNOLD, Michael , BEHRENDS, Sönke , CREMER, Peet , MÜLLER, Dennis
IPC分类号： G07C5/00 , G07C5/08 , G01C21/34 , G08B13/196 , G08G1/01
摘要： A method, carried out in a vehicle (100), includes:
a) downloading over-the-air from a host system (200) a data collection target including a data value metric that is a function assigning a data value to a piece of data at a given point in time, representing an amount of progress towards an atomic collection target;
b) collecting data from data sources (110) in the vehicle (100) over time while the vehicle (100) is driving;
c) recording the collected data in a storing module (142);
d) computing the data values of the recording data, according to the data value metric;
e) selecting, from the recording data, recording data snippets of high value within a time window, based on the computed data values;
f) uploading only the selected recording data snippets of high value to the host system (200) over-the-air.-
公开(公告)号：EP4138057A1
公开(公告)日：2023-02-22
申请号：EP21191928.7
申请日：2021-08-18
发明人： ARNOLD, Michael , BEHRENDS, Sönke , CREMER, Peet , MÜLLER, Dennis
摘要： The computer-implemented method, carried out by a vehicle data recording device (140), includes:
downloading, from a host data collecting system (200), a recording target,
determining a plurality of possible routes for the vehicle (100);
for each route, generating a route encoding in numerical values an information on predicted values of said route for metrics, a metric being a function assigning a value representing an amount of progress in achieving an elementary recording target to a piece of data;
providing the route encodings and additional environmental information independent of the routes to a reinforcement learning agent that selects one of the routes in order to optimize a reward;
recording data from in-vehicle sources (110) while the vehicle drives along the selected route;
uploading at least part of the recording data to the host data collecting system and, in return, receiving a reward for the reinforcement learning agent.-
公开(公告)号：EP4099211A1
公开(公告)日：2022-12-07
申请号：EP21176922.9
申请日：2021-05-31
发明人： SCHOELER, Markus , SIEGEMUND, Jan , NUNN, Christian , SU, Yu , MEUTER, Mirko , BECKER, Adrian , CREMER, Peet
摘要： A method is provided for training a machine learning algorithm which relies on primary data captured by at least one primary sensor. Labels are identified based on auxiliary data provided by at least one auxiliary sensor. A care attribute or a no-care attribute is assigned to each label by determining a perception capability of the primary sensor for the label based on the primary data and based on the auxiliary data. Model predictions for the labels are generated via the machine learning algorithm. A loss function is defined for the model predictions. Negative contributions to the loss function are permitted for all labels. Positive contributions to the loss function are permitted for labels having a care attribute, while positive contributions to the loss function for labels having a no-care attribute are permitted only if a confidence of the model prediction for the respective label is greater than a threshold.
-
公开(公告)号：EP3767324A1
公开(公告)日：2021-01-20
申请号：EP19186811.6
申请日：2019-07-17
发明人： ZHU, Weimeng , SU, Yu , CREMER, Peet , MAOZ, Ori , LESSMANN, Stephanie , KOSSACZKÝ, Igor , DEHKORDI, Saeid Khalili , LABUSCH, Sven
IPC分类号： G01S7/41 , G01S13/42 , G01S13/58 , G01S13/64 , G01S13/931
摘要： A computer implemented method for detecting objects comprises the following steps carried out by computer hardware components: providing signal representation data comprising range information, velocity information and angular information; for each of a plurality of spatial scales, determining respective scaled data for the respective spatial scale based on the signal representation data, to obtain a plurality of scaled data; providing the plurality of scaled data to a plurality of detectors; and each detector carrying out object detection based on at least one of the plurality of scaled data.
-
-
-
-
-
搜索结果
6 条记录 (耗时 0.011 秒)
