EP3785192A1 - Verfahren und fahrzeugsystem zur passagiererkennung durch autonome fahrzeuge - Google Patents
Verfahren und fahrzeugsystem zur passagiererkennung durch autonome fahrzeugeInfo
- Publication number
- EP3785192A1 EP3785192A1 EP19703081.0A EP19703081A EP3785192A1 EP 3785192 A1 EP3785192 A1 EP 3785192A1 EP 19703081 A EP19703081 A EP 19703081A EP 3785192 A1 EP3785192 A1 EP 3785192A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- person
- transported
- vehicle
- autonomous vehicle
- passenger
- 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- Withdrawn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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/02—Reservations, e.g. for tickets, services or events
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0025—Planning or execution of driving tasks specially adapted for specific operations
- B60W60/00253—Taxi operations
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0024—Planning or execution of driving tasks with mediation between passenger and vehicle requirements, e.g. decision between dropping off a passenger or urgent vehicle service
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0025—Planning or execution of driving tasks specially adapted for specific operations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B15/00—Systems controlled by a computer
- G05B15/02—Systems controlled by a computer electric
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W2040/0809—Driver authorisation; Driver identity check
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0002—Automatic control, details of type of controller or control system architecture
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
- B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
- B60W2420/403—Image sensing, e.g. optical camera
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
- B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
- B60W2420/408—Radar; Laser, e.g. lidar
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2556/00—Input parameters relating to data
- B60W2556/45—External transmission of data to or from the vehicle
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2556/00—Input parameters relating to data
- B60W2556/45—External transmission of data to or from the vehicle
- B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q2240/00—Transportation facility access, e.g. fares, tolls or parking
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
- G06T2207/30201—Face
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
- G06T2207/30252—Vehicle exterior; Vicinity of vehicle
Definitions
- the invention relates to a method for passenger detection by a
- Vehicles are taken while the driver is in the interior.
- the autonomous vehicle can travel a defined distance even without a driver or occupant, for example to pick up occupants at a defined starting point, such as a holding area, and bring them to a defined destination, such as another holding area.
- a defined starting point such as a holding area
- a defined destination such as another holding area.
- the parking situation in big cities is problematic in many places, so that sometimes long distances between a parking lot and the actual destination on foot have to be mastered.
- the object underlying the invention can be seen to propose a method and a vehicle system for the precise identification and picking up of a passenger by autonomous vehicles.
- a method for passenger detection by an autonomous vehicle is provided.
- at least one photo of the person to be transported is transmitted to a central server.
- the autonomous vehicle is controlled or approximated to the previously determined approximate position of the person to be transported.
- the identity of the ascertained person to be transported is checked in a further step.
- the autonomous vehicle is positioned in an entry area of the person to be transported.
- the passenger or driver (hereinafter, the driver also as a passenger considered) get on or off, stop on open spaces and wait for the completed passenger transfer.
- the driver In the case of boarding, it is customary to wait for previously agreed stop positions. In this case, either the passenger first arrives at the agreed place and waits for the vehicle or the vehicle arrives in front of the passenger at the agreed place and waits for the arrival of the passengers.
- the autonomous driving opens up new dynamic possibility to determine the passenger transfer location, where the driver is also transferred as a passenger or
- the method according to the invention is a photo of the male passenger, for example, using a smartphone and an app
- the system then knows who needs to be recovered or picked up and what it looks like.
- the initial recording by smartphone can also be achieved by any other camera systems.
- the passenger initiates a pickup, he can tell the system his rough position.
- the GPS signal of his smartphone can be used to approximate the approximate position of the smartphone
- the autonomous vehicle can roughly approach the passenger at the specified time.
- the on-board sensors such as cameras, but also
- Off-board cameras which are also networked with the cloud, can be used to find the person around the roughly predetermined position.
- a dynamic stop positions for a quick and uncomplicated passenger exchange or a passenger reception by an autonomous vehicle can be determined and implemented.
- the autonomous vehicle can visit and transfer passengers everywhere without parking.
- the autonomous vehicle only has to hold for this. Since the autonomous vehicle the passenger or passengers after gross
- Search area default alone, passengers no longer have to wait at predetermined parking spaces for the vehicles. For example, a passenger may walk along a road previously announced to the system and the autonomous vehicle would find the passenger alone and stop beside him to facilitate passenger transfer.
- a function may be implemented in an autonomous vehicle or system by which the driver and / or passengers are detected, retrieved, and located from an image of the scene to communicate the exact position for passenger communication to the autonomous vehicle , The precise
- Localization of the person to be transported can be done on the basis of color and / or texture features and / or based on a gait of the person.
- a video of the person can be evaluated by an in-vehicle or external control unit, and the identity of the person can thus be determined on the basis of movement patterns.
- the person to be transported can thereby be identified within an environment or a large number of persons and thus also be located.
- machine learning, computer vision, deep learning, and the like can be used to recognize people by gait.
- the in-vehicle sensor system has at least one camera, a LIDAR sensor and / or at least one radar sensor.
- the in-vehicle sensor technology can also provide a 360 ° all-round view.
- the environment can be scanned or searched with regard to the color and texture characteristics of the passenger sought.
- This can be used to tell the system which person needs to be found again and what it looks like.
- the initial recording by smartphone can also be achieved by other camera systems with high integrity.
- the approximate position can be sent to the autonomous vehicle through text messages, such as SMS, e-mail or through
- Voice messages of the passenger to be transported are communicated.
- the passenger can thus communicate an address, a road, an environment, distinctive points or landmarks and the like to the autonomous vehicle as an approximate position.
- a detailed search for example by the vehicle sensor system, can be initiated and thus an exact position of the passenger by the autonomous vehicle can be determined.
- the GPS signal of a portable device of the passenger can be used to obtain the rough localization.
- a plannable pick-up of the passenger can be realized by reading an electronic calendar, in which the passenger is automatically expected from the autonomous vehicle at a desired location depending on defined deadlines.
- the approximate determination of the position of the person to be transported is carried out by an internal control unit or an external server unit.
- This allows the vehicle itself to do the necessary calculations through controllers or outsource compute-intensive tasks to the external server unit.
- This can be for example a face recognition by complex algorithms or an evaluation of extensive vehicle-external determined image data.
- files are accessed by the autonomous vehicle of at least one vehicle-external sensor system. Through networked infrastructure sensors and vehicle sensors from other vehicles, other autonomous vehicles could continue to do so
- passenger-receiving vehicle are informed and early on the plan trajectory adjusted so that a smooth flow of traffic is made possible. Furthermore, based on such a networking and fusion of the sensors, a data exchange can be realized, which enables a faster and / or more precise identification and location of the passenger.
- Person identification and personalization for the autonomous vehicle provides access to stored in a cloud files.
- the autonomous vehicle can access collected data of other road users or traffic units and perform, for example, the identification or location of the passenger.
- the person recognition on the basis of color and texture features and a
- Person identification and personal location for the autonomous vehicle provides access to sensors and search functions and / or data exchange with stored data of other vehicles.
- sensors for the detection recognition and localization of the person primarily onboard cameras of the vehicle can be used.
- external video surveillance cameras eg on light poles or on house walls
- various networked collaborative vehicles can jointly send their sensor data to a cloud to recognize people for whom you each have no driving assignments and thus contribute to an optimized stability of the system.
- the person to be transported when not finding by the autonomous
- a notification may preferably be communicated to the passenger. Subsequently, a renewed approximate position can be transmitted to the vehicle by the passenger, as a result of which the method can again be performed at least partially by the vehicle.
- a vehicle system for carrying out the method according to the invention is provided.
- Vehicle system has at least one autonomous vehicle with a
- the vehicle system may also have an optional usable
- Fig. 1 is a schematic flow diagram for illustrating a
- Fig. 2 is a schematic plan view of an inventive
- FIG. 1 shows a schematic flowchart for illustrating a method 1 according to the invention according to an embodiment.
- the structural features relate to a vehicle system 10 according to the invention, which is shown in FIG.
- a step 2 at least one photo of a person to be transported is transmitted to a central server 12 of a vehicle system 10.
- a central server 12 of a vehicle system 10. This can be for example a so-called selfie of a passenger 14, which is transmitted to a cloud 12 or a vehicle-external server unit 12.
- Detection data of the person 14 can be generated in the external server unit 12.
- an approximate position of the person to be transported 14 It is determined in a further step 3, an approximate position of the person to be transported 14.
- the approximate position may be, for example, a road or an environment of the person 14 at which it is to be picked up by an autonomous vehicle 16.
- Approximate position can be determined, for example, by using a GPS signal of a portable device of the passenger 14.
- a GPS signal of a portable device of the passenger 14 In a civilian use of GPS sensors, however, an inaccuracy of at least several meters remain, which may be more pronounced by local circumstances.
- the autonomous vehicle 16 is controlled or approximated to the previously determined approximate position of the person 14 to be transported.
- the sensor 18 is with a
- In-vehicle control unit 20 is coupled and can be evaluated by the control unit 20.
- the control unit 20 further includes a communication device, not shown, through which a wireless Communication link with the external server unit 12 can be made.
- the server unit 12 communicates with a sensor of the
- the identity of the ascertained person 14 to be transported is checked in a further step 6.
- the autonomous vehicle 16 is positioned in an entry area of the person 14 to be transported.
- the procedure is divided into two areas: a short-range and a long-range.
- the near range is the area in which the face of the passenger 14 is so close to the camera or a vehicle sensor system 18 that a face re-recognition method can be used. Within this range, the probability of not being confused with person 14 is very high.
- the far-end area is the area in which the face of the passenger 14 is so far away from the camera 18 that no face recognition methods can be used. In the far range, color and texture features from the images are used to recognize the person.
- the system 10 must consider several potential passengers in the far-end area, depending on the density of people in the scene, until recognition in
- the autonomous vehicle may adjust its desired trajectory to travel alongside the passenger 14 hold that the door provided for him comes to stand next to him 14 and the passenger 14 can effortlessly get into the vehicle 16.
- Passenger's smartphone 14 requesting that he look towards the street, whereby his face can be recognized.
- the vehicle 16 continues to drive so as not to block traffic unnecessarily long.
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Human Computer Interaction (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Mathematical Physics (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Human Resources & Organizations (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Multimedia (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Engineering & Computer Science (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Primary Health Care (AREA)
- Traffic Control Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Electromagnetism (AREA)
- Aviation & Aerospace Engineering (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102018206344.3A DE102018206344A1 (de) | 2018-04-25 | 2018-04-25 | Verfahren und Fahrzeugsystem zur Passagiererkennung durch autonome Fahrzeuge |
| PCT/EP2019/052603 WO2019206478A1 (de) | 2018-04-25 | 2019-02-04 | Verfahren und fahrzeugsystem zur passagiererkennung durch autonome fahrzeuge |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP3785192A1 true EP3785192A1 (de) | 2021-03-03 |
Family
ID=65278377
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP19703081.0A Withdrawn EP3785192A1 (de) | 2018-04-25 | 2019-02-04 | Verfahren und fahrzeugsystem zur passagiererkennung durch autonome fahrzeuge |
Country Status (7)
| Country | Link |
|---|---|
| US (1) | US20210171046A1 (de) |
| EP (1) | EP3785192A1 (de) |
| JP (1) | JP7145971B2 (de) |
| KR (1) | KR20210003851A (de) |
| CN (1) | CN112041862A (de) |
| DE (1) | DE102018206344A1 (de) |
| WO (1) | WO2019206478A1 (de) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102019212998B4 (de) | 2019-08-29 | 2022-08-04 | Volkswagen Aktiengesellschaft | Fortbewegungsmittel, Vorrichtung und Verfahren zum Positionieren eines automatisiert fahrfähigen Fortbewegungsmittels |
| DE102020204147A1 (de) | 2020-03-31 | 2021-09-30 | Faurecia Innenraum Systeme Gmbh | Fahrgastinformationssystem und Verfahren zum Anzeigen von personalisierten Sitzplatzinformationen |
| WO2022093921A1 (en) | 2020-10-29 | 2022-05-05 | Waymo Llc | Holistic wayfinding |
| US11644322B2 (en) * | 2021-02-09 | 2023-05-09 | Gm Cruise Holdings Llc | Updating a pick-up or drop-off location for a passenger of an autonomous vehicle |
| US12026542B2 (en) | 2021-07-15 | 2024-07-02 | International Business Machines Corporation | Optimizing deployment of machine learning workloads |
| US20230098373A1 (en) * | 2021-09-27 | 2023-03-30 | Toyota Motor North America, Inc. | Occupant mobility validation |
| KR20240092431A (ko) | 2022-12-14 | 2024-06-24 | 현대자동차주식회사 | 차량 제어 장치 및 방법 |
| US12545284B2 (en) | 2023-05-19 | 2026-02-10 | Torc Robotics, Inc. | Updating path based on information from CB radio |
| DE102023204891A1 (de) * | 2023-05-25 | 2024-11-28 | Zf Friedrichshafen Ag | Befördern von Personen mit besonderen Merkmalen |
| EP4575971A4 (de) * | 2023-07-31 | 2025-11-05 | Lg Electronics Inc | Fahrhilfedienstbereitstellungsverfahren, fahrhilfedienstbereitstellungssystem und damit zusammenarbeitende ar-dienstbereitstellungsvorrichtung |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104599287B (zh) * | 2013-11-01 | 2018-01-16 | 株式会社理光 | 对象跟踪方法和装置、对象识别方法和装置 |
| US10387825B1 (en) * | 2015-06-19 | 2019-08-20 | Amazon Technologies, Inc. | Delivery assistance using unmanned vehicles |
| US10088846B2 (en) * | 2016-03-03 | 2018-10-02 | GM Global Technology Operations LLC | System and method for intended passenger detection |
| US20180075565A1 (en) * | 2016-09-13 | 2018-03-15 | Ford Global Technologies, Llc | Passenger validation systems and methods |
| US20180074494A1 (en) * | 2016-09-13 | 2018-03-15 | Ford Global Technologies, Llc | Passenger tracking systems and methods |
| US20180196417A1 (en) * | 2017-01-09 | 2018-07-12 | nuTonomy Inc. | Location Signaling with Respect to an Autonomous Vehicle and a Rider |
| US20180210892A1 (en) * | 2017-01-25 | 2018-07-26 | Uber Technologies, Inc. | Object or image search within a geographic region by a network system |
| US20190228246A1 (en) * | 2018-01-25 | 2019-07-25 | Futurewei Technologies, Inc. | Pickup Service Based on Recognition Between Vehicle and Passenger |
| JP6881344B2 (ja) * | 2018-02-09 | 2021-06-02 | 株式会社デンソー | 出迎えシステム |
| US11474519B2 (en) * | 2018-02-26 | 2022-10-18 | Nvidia Corporation | Systems and methods for computer-assisted shuttles, buses, robo-taxis, ride-sharing and on-demand vehicles with situational awareness |
-
2018
- 2018-04-25 DE DE102018206344.3A patent/DE102018206344A1/de not_active Withdrawn
-
2019
- 2019-02-04 JP JP2020559395A patent/JP7145971B2/ja active Active
- 2019-02-04 US US17/045,924 patent/US20210171046A1/en not_active Abandoned
- 2019-02-04 CN CN201980028077.0A patent/CN112041862A/zh active Pending
- 2019-02-04 WO PCT/EP2019/052603 patent/WO2019206478A1/de not_active Ceased
- 2019-02-04 KR KR1020207033633A patent/KR20210003851A/ko not_active Withdrawn
- 2019-02-04 EP EP19703081.0A patent/EP3785192A1/de not_active Withdrawn
Also Published As
| Publication number | Publication date |
|---|---|
| CN112041862A (zh) | 2020-12-04 |
| JP7145971B2 (ja) | 2022-10-03 |
| JP2021519989A (ja) | 2021-08-12 |
| DE102018206344A1 (de) | 2019-10-31 |
| WO2019206478A1 (de) | 2019-10-31 |
| US20210171046A1 (en) | 2021-06-10 |
| KR20210003851A (ko) | 2021-01-12 |
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