EP4315298A1 - Verfahren und warnvorrichtung zum warnen eines nachfolgefahrzeugs auf einem definierten fahrbahnabschnitt vor einem hindernis - Google Patents
Verfahren und warnvorrichtung zum warnen eines nachfolgefahrzeugs auf einem definierten fahrbahnabschnitt vor einem hindernisInfo
- Publication number
- EP4315298A1 EP4315298A1 EP22714359.1A EP22714359A EP4315298A1 EP 4315298 A1 EP4315298 A1 EP 4315298A1 EP 22714359 A EP22714359 A EP 22714359A EP 4315298 A1 EP4315298 A1 EP 4315298A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- ego
- time interval
- obstacle
- difference
- trajectories
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
- G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/164—Centralised systems, e.g. external to vehicles
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096716—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information does not generate an automatic action on the vehicle control
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096733—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place
- G08G1/096758—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place where no selection takes place on the transmitted or the received information
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
Definitions
- the invention relates to a method and a warning device for warning a following vehicle on a defined roadway section of an obstacle.
- vehicles are able to automatically detect obstacles on sections of road with the aid of their vehicle sensors provided for this purpose. Data about detected obstacles can then be sent to following vehicles, for example via a backend or directly via V2X communication, in order to warn them.
- following vehicles to which data about potential obstacles are communicated from the backend or directly via V2X communication, can react early and, for example, warn the driver and thus help to avoid accidents.
- warning signals that are issued to following vehicles on the basis of automated detections of obstacles on sections of the road are classified as rather unreliable.
- the object of the invention is therefore to propose a method and a warning device for warning a following vehicle on a defined section of the roadway indicate an obstacle that are more reliable than the previously known methods and devices.
- This object is achieved with a method for warning a following vehicle on a defined section of the road of an obstacle with the combination of features of claim 1.
- a warning device for warning a following vehicle on a defined section of the road ahead of an obstacle is the subject of the independent claim.
- a method for warning a following vehicle on a defined section of the road ahead of an obstacle has the following steps:
- Swarm trajectories are created from the movement data of ego vehicles. If there is a sudden, statistically significant local change in the swarm trajectory over time, e.g. B. by performed evasive maneuvers, this indicates an obstacle on the road section.
- Such evasive maneuvers are mostly initiated by people who control the ego vehicles, so that the people or the drivers themselves serve as sensors and obstacles that are normally difficult to detect for dedicated vehicle sensors can also be reliably detected.
- the advantage of the method is that no special vehicle sensors are required in the vehicle in comparison to direct obstacle detection by vehicle sensors.
- the swarm trajectory is determined by a large number of trajectory positions or trajectory points arranged one after the other with a value in the direction of travel and a value arranged perpendicular thereto on the roadway section. If both types of values are represented in one coordinate system, the y-value represents the direction of travel, while the x-value is arranged perpendicular to it.
- the difference between the x-values of the first and second swarm trajectories to be compared is preferably formed at a predetermined y-value, so that the deviation in the x-direction is decisive.
- GNSS Global Navigation Satellite System
- GNSS data or mobile phone data Due to the use of GNSS data or mobile phone data, there is a very large number of ego vehicles that participate in detecting obstacles. This increases the coverage of the road network and the reliability of the data obtained.
- the first and the second time interval, in which the ego trajectories are recorded can be constant in terms of time and, for example, cover a period of 10 min.
- the first or second time interval can be flexible in terms of time and to be determined by a predetermined number of ego vehicles that pass the defined roadway section. For example, a swarm trajectory can only be formed from a large number of ego trajectories when at least 10 ego vehicles have passed the defined roadway section.
- the first time interval and the second time interval can also overlap in time.
- a second swarm trajectory is advantageously selected whose second time stamp is offset in time by at least 20 minutes, in particular at least 10 minutes, more particularly at least 5 minutes, from the first time stamp of the first swarm trajectory.
- the predetermined threshold value is preferably 10 m, in particular 5 m, more particularly 2 m.
- the difference is used in order to take into account debris that can reach the roadway section from both sides perpendicular to the direction of travel y.
- a correspondingly reliable warning signal can be output to a following vehicle, which is moving behind the ego vehicles in time on the defined roadway section with the obstacle.
- the obstacle present on the roadway section is preferably recognized by a backend, with the warning signal preferably being output by the backend to the following vehicle.
- the backend advantageously processes ego trajectories, which have been transmitted from the ego vehicles to the backend, into the swarm trajectories, compares them and, by calculating the difference in the x-value, recognizes whether an obstacle has meanwhile entered the roadway section.
- the backend then outputs the warning signal directly to the following vehicle to warn it of the obstacle and prepare the driver to initiate an evasive maneuver.
- Ego driving speeds average speeds for the first and for the second time interval are determined, with a difference between a first average speed for the first time interval and a second Average speed is formed for the second time interval, with an existing obstacle being detected on the roadway section if the difference is greater than 50%, in particular greater than 70%, of the first average speed.
- a change in the average speed of ego vehicles that pass the defined road section is another indicator of an obstacle. This is because vehicles usually slow down in the area of obstacles. If this reduction in average speed is significant, i.e. greater than about 50% or even 70%, this clearly indicates an obstacle on the defined section of the road. With appropriate processing of this information, for example in the backend, an obstacle detected in this way can then be sent as a warning to the following vehicles following the ego vehicles.
- average speeds are compared, which are calculated from the ego driving speeds.
- a difference is calculated from these average speeds, with the amount not being relevant here, but rather the information as to whether the second average speed is significantly lower than the first average speed. For this reason, the evaluation does not work with the difference, as is the case when comparing the swarm trajectories, but with the absolute value of the difference. If the second average speed is significantly lower than the first average speed, there is a relatively large difference. This is not the case if the two average speeds are similar, in which case a relatively small difference would arise when the difference is formed. Therefore, if the difference is greater than 50% or even 70% of the first average speed, it means that the second
- Average speed is low and the ego vehicles slow down significantly on the defined section of the road, which clearly indicates an obstacle. For example, if the first average speed is 50 km/h and the second average speed is only 10 km/h, then the difference, namely 40 km/h, is 80% of the first average speed.
- An advantageous warning device for warning a following vehicle on a defined section of the road ahead of an obstacle is preferably designed to carry out the method as described above.
- the warning device comprises a processing device for forming the first and second swarm trajectories from the plurality of ego trajectories, respectively, and a storage device for storing the formed first and second swarm trajectories together with their associated first and second time stamps.
- the warning device also has a comparison device for forming the difference between the first and second swarm trajectories, an evaluation device for comparing the difference with the predetermined threshold value and for detecting the obstacle when the threshold value is exceeded by the difference formed, and a warning device for outputting the warning signal to the following vehicle .
- the warning device is formed in such a way that it recognizes an obstacle on the defined roadway section from an abrupt change in the course of the swarm trajectories and can output this information as a warning signal to following vehicles.
- the processing device is advantageously designed to determine average speeds and the comparison device is designed to form the difference between the average speeds.
- the evaluation device is also advantageously designed to compare the difference formed between the average speeds with the first average speed and to detect the obstacle if the difference is more than 50%, in particular 70%, of the first average speed.
- the warning device is not only designed to recognize the obstacle based on an abrupt change in the course of the swarm trajectories, but also to evaluate the ego driving speeds in such a way as to recognize that ego vehicles are suddenly passing the defined section of the road at a lower driving speed and also to find out that there is a traffic jam on the defined section of the road.
- FIG. 1 shows a schematic plan view of a defined roadway section with ego vehicles moving thereon and a first swarm trajectory resulting from ego trajectories of these ego vehicles in a first time interval [ti; t2];
- FIG. 2 shows a schematic plan view of the defined roadway section from FIG. 1 at a second time interval [t3; t4] with ego vehicles moving thereon and a second swarm trajectory resulting from the ego trajectories of the ego vehicles;
- FIG. 3 shows a schematic representation of a difference formation between the first swarm trajectory from FIG. 1 and the second swarm trajectory from FIG. 2;
- FIG. 4 is a schematic flow chart showing the steps of a method for warning a following vehicle on the defined roadway section from FIG. 2 of an obstacle.
- FIG. 1 shows a schematic plan view of a defined roadway section 10 at a first time interval [ti; t2].
- Three ego vehicles 12 move along their associated ego trajectories 14 on roadway section 10, each with their own driving speed vi, V2, V3. All three ego vehicles 12 send their GNSS data 18 recorded via GNSS receiver 16 to a backend 20.
- the ego vehicles 12 Have cellular modules 22, and then triangulated cellular data 24 to the backend 20 can send. It is possible to infer the ego trajectories 14 of the ego vehicles 12 from the GNSS data 18 or the mobile radio data 24 .
- the backend 20 has a backend receiver 26 .
- the backend 20 then processes the data received from the ego vehicles 12—GNSS data 18 and/or mobile radio data 24—to form a swarm trajectory 30.
- the backend 20 then stores this swarm trajectory 30 in a storage device 32 together with a time stamp T1 off.
- the ego vehicles 12 use speed detection modules 34 to record their ego driving speeds vi, V2, V3, with which they drive along the roadway section 10 in the first time interval [ti; t2] happen.
- the recorded ego driving speeds vi, V2, V3 are then also sent to the backend 20, received there by the backend receiver 26 and then processed in the processing device 28 to form an average speed VD.
- FIG. 2 shows a further plan view of road section 10 from FIG. 1 , but at a different, second time interval [t3; t4], which is later than the first time interval [ti; t2]. It can be seen that in the meantime a rumble 36 has reached the right side of the roadway section 10 .
- the ego vehicles 12 running during the second time interval [t3; t4] pass the roadway section 10, dodge this obstacle 36, as a result of which their ego trajectories 14 no longer run in a straight line on the roadway section 10, as is approximately the case in FIG. 1, but instead have a bend.
- the processing device 28 uses this to form a second swarm trajectory 38, which has a significantly different course than the first swarm trajectory 30.
- the backend 20 stores this second swarm trajectory 38 with a second time stamp T2 in the storage device 32. Due to the obstacle, the ego vehicles 12 also drive at reduced driving speeds vi, V2, V3 over the roadway section 10, brake in front of the obstacle 36 and drive around it more slowly than if they could pass the roadway section 10 without being impaired. As a result, lower ego driving speeds vi, V2, V3 are also recorded by the speed detection modules 34 of the ego vehicles 12 and sent to the backend 20, so that the processing device 28 calculates a lower average speed VD therefrom.
- the backend 20 in Fig. 1 and Fig. 2 is now designed to process this information from the ego vehicles 12 that drive around the obstacle 36 in such a way that the backend 20 can send a warning signal 40 to a following vehicle 42 that follows the ego vehicles 12 on the road section 10 in time.
- the backend 20 has a comparison device 44 that calculates a difference
- a difference between the first swarm trajectory 30 and the second swarm trajectory 38 forms.
- a difference between the first swarm trajectory 30 and the second swarm trajectory 38 forms.
- a difference between the first swarm trajectory 30 and the second swarm trajectory 38 forms.
- a difference
- the x-values of the two swarm trajectories 30, 38 are subtracted from one another at a large number of predefined y-values and the absolute value is formed from the result.
- compared with a predetermined threshold value x s and recognized that the obstacle 36 is present on the road section 10 when the difference
- the threshold value x s can, for example, be generously selected at 10 m, but it is also possible to provide lower threshold values x s , such as 5 m or 2 m. Depending on the size of the obstacle 36, this threshold value x s thus defines whether the impairment the obstacle 36 is worth warning a following vehicle 42 about. If the evaluation device 46 determines that the threshold value x s has been exceeded and thus recognizes the obstacle 36 , a warning device 48 in the backend 20 outputs the warning signal 40 to the following vehicle 42 . A driver of following vehicle 42 is thus prepared for the fact that he will soon encounter an obstacle 36 on roadway section 10 to be driven on, and can adjust himself and his journey accordingly.
- the ego vehicles 12 also transmit their ego driving speeds, v i , V2 , V3 , so that the processing device 28 can form average speeds V D therefrom.
- These average speeds VD are also stored in the memory device 32 with the corresponding time stamp T1, T2.
- the comparison device 44 compares the average speed VD corresponding to the first time stamp T1 and thus to the first time interval [ti; t2], with the average speed VD corresponding to the second time stamp T2 and thus to the second time interval [t3; t4] by forming a difference Dn of the average speeds VD.
- This difference Dn is then evaluated by the evaluation device 46 by comparing the difference Dn with the first average speed VD.
- the evaluation device 46 decides that the obstacle 36 is present on the roadway section 10, and the backend 20 indicates this via the warning device 48 Warning signal 40 to the following vehicle 42 from.
- FIG. 4 shows a schematic flow diagram that shows the steps of the method for warning the following vehicle 42 of the obstacle 36 .
- a multiplicity of ego trajectories 14 are recorded which are to be assigned to ego vehicles 12 which are in the first time interval [ti; t2] move on the road section 10.
- the first swarm trajectory 30 is then formed in the next step and this is then stored together with the first time stamp T1 in a further step.
- a further plurality of ego trajectories 14, now at the second time interval [t3; t4] is detected, a second swarm trajectory 38 is formed therefrom and this is also stored together with its second time stamp T2.
- educated is also stored together with its second time stamp T2.
- next step it is detected whether there is a obstacle 36 on the section of road 10 if the determined difference
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Atmospheric Sciences (AREA)
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102021203186.2A DE102021203186A1 (de) | 2021-03-30 | 2021-03-30 | Verfahren und Warnvorrichtung zum Warnen eines Nachfolgefahrzeugs auf einem definierten Fahrbahnabschnitt vor einem Hindernis. |
| PCT/DE2022/200048 WO2022207045A1 (de) | 2021-03-30 | 2022-03-18 | Verfahren und warnvorrichtung zum warnen eines nachfolgefahrzeugs auf einem definierten fahrbahnabschnitt vor einem hindernis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4315298A1 true EP4315298A1 (de) | 2024-02-07 |
Family
ID=81325475
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP22714359.1A Withdrawn EP4315298A1 (de) | 2021-03-30 | 2022-03-18 | Verfahren und warnvorrichtung zum warnen eines nachfolgefahrzeugs auf einem definierten fahrbahnabschnitt vor einem hindernis |
Country Status (8)
| Country | Link |
|---|---|
| US (1) | US20240242612A1 (de) |
| EP (1) | EP4315298A1 (de) |
| JP (1) | JP2024512141A (de) |
| KR (1) | KR20230142579A (de) |
| CN (1) | CN117296085A (de) |
| BR (1) | BR112023017688A2 (de) |
| DE (1) | DE102021203186A1 (de) |
| WO (1) | WO2022207045A1 (de) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102021002295B3 (de) * | 2021-04-30 | 2022-09-22 | Mercedes-Benz Group AG | Verfahren zur Ermittlung und Ausgabe einer an eine Fahrsituation angepassten Fahrgeschwindigkeit |
| DE102023124125B3 (de) | 2023-09-07 | 2025-01-23 | Cariad Se | Längsregelung eines Kraftfahrzeuges mittels eines Fahrerassistenzsystems |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US9459625B1 (en) * | 2012-03-16 | 2016-10-04 | Google Inc. | Approach for consolidating observed vehicle trajectories into a single representative trajectory |
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| JP4240321B2 (ja) * | 2005-04-04 | 2009-03-18 | 住友電気工業株式会社 | 障害物検出センター装置及び障害物検出方法 |
| US7912627B2 (en) * | 2006-03-03 | 2011-03-22 | Inrix, Inc. | Obtaining road traffic condition data from mobile data sources |
| JP4759476B2 (ja) * | 2006-09-06 | 2011-08-31 | 日本無線株式会社 | 道路情報収集・提供方法 |
| JP4946903B2 (ja) * | 2008-02-12 | 2012-06-06 | トヨタ自動車株式会社 | 車両用背景画像収集装置 |
| US20120065871A1 (en) * | 2010-06-23 | 2012-03-15 | Massachusetts Institute Of Technology | System and method for providing road condition and congestion monitoring |
| US8930123B2 (en) * | 2010-11-19 | 2015-01-06 | International Business Machines Corporation | Systems and methods for determining traffic intensity using information obtained through crowdsourcing |
| US8781721B2 (en) * | 2012-06-06 | 2014-07-15 | Google Inc. | Obstacle evaluation technique |
| US8972175B2 (en) * | 2013-03-14 | 2015-03-03 | Qualcomm Incorporated | Navigation using crowdsourcing data |
| DE102013210923A1 (de) | 2013-06-12 | 2014-12-18 | Robert Bosch Gmbh | Vorausschauende Steuerung eines Kraftfahrzeugs |
| US20170279957A1 (en) * | 2013-08-23 | 2017-09-28 | Cellepathy Inc. | Transportation-related mobile device context inferences |
| US9969329B2 (en) * | 2015-09-16 | 2018-05-15 | Sony Corporation | System and method for generation of a preventive alert |
| DE102015014651A1 (de) | 2015-11-12 | 2017-05-18 | Audi Ag | Verfahren zum Bereitstellen einer Spurinformation einer Fahrspur und System |
| DE102016201249A1 (de) | 2016-01-28 | 2017-08-03 | Conti Temic Microelectronic Gmbh | Vorrichtung und verfahren zur ermittlung eines fahrbahnmodells |
| US10034066B2 (en) * | 2016-05-02 | 2018-07-24 | Bao Tran | Smart device |
| DE102016216153A1 (de) | 2016-08-29 | 2018-03-01 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren und Vorrichtung zur situationsbasierten Warnung eines Fahrers eines Fahrzeugs |
| US20180060970A1 (en) * | 2016-09-01 | 2018-03-01 | International Business Machines Corporation | System and method for context-based driver monitoring |
| US20190301891A1 (en) * | 2018-03-29 | 2019-10-03 | Qualcomm Incorporated | Method and Apparatus for Obtaining and Displaying Map Data On a Mobile Device |
| JP7066545B2 (ja) * | 2018-06-22 | 2022-05-13 | 株式会社Subaru | 運転支援システム、サーバ、および運転支援方法 |
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| CN110069887B (zh) * | 2019-05-05 | 2022-04-15 | 腾讯科技(深圳)有限公司 | 一种驾驶仿真方法、装置、设备及存储介质 |
| CN115578711A (zh) * | 2019-05-21 | 2023-01-06 | 华为技术有限公司 | 自动换道方法、装置及存储介质 |
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-
2021
- 2021-03-30 DE DE102021203186.2A patent/DE102021203186A1/de not_active Withdrawn
-
2022
- 2022-03-18 CN CN202280025558.8A patent/CN117296085A/zh not_active Withdrawn
- 2022-03-18 EP EP22714359.1A patent/EP4315298A1/de not_active Withdrawn
- 2022-03-18 US US18/553,399 patent/US20240242612A1/en active Pending
- 2022-03-18 BR BR112023017688A patent/BR112023017688A2/pt unknown
- 2022-03-18 JP JP2023560521A patent/JP2024512141A/ja active Pending
- 2022-03-18 KR KR1020237030145A patent/KR20230142579A/ko not_active Ceased
- 2022-03-18 WO PCT/DE2022/200048 patent/WO2022207045A1/de not_active Ceased
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9459625B1 (en) * | 2012-03-16 | 2016-10-04 | Google Inc. | Approach for consolidating observed vehicle trajectories into a single representative trajectory |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2024512141A (ja) | 2024-03-18 |
| CN117296085A (zh) | 2023-12-26 |
| DE102021203186A1 (de) | 2022-10-06 |
| KR20230142579A (ko) | 2023-10-11 |
| WO2022207045A1 (de) | 2022-10-06 |
| US20240242612A1 (en) | 2024-07-18 |
| BR112023017688A2 (pt) | 2023-09-26 |
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