GB2569774A - Method for virtual testing of real environments with pedestrian interaction and drones - Google Patents
Method for virtual testing of real environments with pedestrian interaction and drones Download PDFInfo
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- GB2569774A GB2569774A GB1717221.4A GB201717221A GB2569774A GB 2569774 A GB2569774 A GB 2569774A GB 201717221 A GB201717221 A GB 201717221A GB 2569774 A GB2569774 A GB 2569774A
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 230000003993 interaction Effects 0.000 title claims abstract description 8
- 238000012360 testing method Methods 0.000 claims abstract description 50
- 230000008447 perception Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 6
- 238000012546 transfer Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 238000005259 measurement Methods 0.000 claims description 4
- 238000010348 incorporation Methods 0.000 claims 2
- 230000004936 stimulating effect Effects 0.000 claims 1
- 230000004044 response Effects 0.000 abstract description 2
- 238000002474 experimental method Methods 0.000 description 4
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 230000004438 eyesight Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
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- 101000993469 Homo sapiens Beta-catenin-interacting protein 1 Proteins 0.000 description 1
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Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0011—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
- G05D1/0016—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement characterised by the operator's input device
-
- 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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0088—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0004—Transmission of traffic-related information to or from an aircraft
- G08G5/0013—Transmission of traffic-related information to or from an aircraft with a ground station
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/0047—Navigation or guidance aids for a single aircraft
- G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
- G09B9/02—Simulators for teaching or training purposes for teaching control of vehicles or other craft
- G09B9/04—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles
- G09B9/048—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles a model being viewed and manoeuvred from a remote point
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2101/00—UAVs specially adapted for particular uses or applications
- B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography
Abstract
A method for testing of self-driving or autonomous vehicles A and their algorithms in situations with pedestrian interactions comprises providing a drone B controlled by a test person C. The control of the drone B comprises applying motion capture techniques and providing a walking platform to the test person C. The drone B comprises a camera, the images being wirelessly transmitted to the test person C, and the movement of the test person in response to the images tracked and used to control the drone B. There may be traffic between the drone and the vehicle. The method may be carried out in real time.
Description
(57) A method for testing of self-driving or autonomous vehicles A and their algorithms in situations with pedestrian interactions comprises providing a drone B controlled by a test person C. The control of the drone B comprises applying motion capture techniques and providing a walking platform to the test person C. The drone B comprises a camera, the images being wirelessly transmitted to the test person C, and the movement of the test person in response to the images tracked and used to control the drone B. There may be traffic between the drone and the vehicle. The method may be carried out in real time.
Fig. 3
At least one drawing originally filed was informal and the print reproduced here is taken from a later filed formal copy.
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Figures
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Fig. 1 /--------------------------------------------------------------------------------------------------\
1. Wireless data Transfer stimuli unit of the test person and drone camera \>
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2. Wireless data transfer between motion capture system and walking platform k_________________________________________________________________________________________________________________________________________________________________________________>
Z--------------------------------------------------------------------------------------------\
3. Sending process of the information about the camera perspective of the drone to the stimuli unit
X_________________________________________________________________
Z...................................................................................................................................................
4. Measurement of the reaction of the test person
X______________________________________________________________________________
Z----------------------------------------------------------
5. Measurement of the joint states of the person ’X —
6. Sending process of the joint states to the drone
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7. Conversion of the Gesture in to flying control
I.__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
-Z
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Fig. 2.
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Fig. 3
Method for virtual testing of real environments with pedestrian interaction and drones
Background of the invention
Testing of autonomous vehicles for complex and uncertain environments has become one of the biggest challenges in the automotive industry. Automation and computational intelligence will increase abilities of the vehicle Okumura et al. (2016). The environment perception and situation understanding will be covered, by computer algorithms.
In addition to vehicle dynamics, the environmental states have to be incorporated into the test Eskandarian (2012). In order to ensure safety, it is required to test the intelligent vehicle in a reasonable way. It is also necessary to have prediction mechanisms to infer the consequences of decisions correctly. Conventional testing procedures are insufficient to ensure safety of increasingly complex future assistance functions involving machine perception and cognition Bengler et al. (2014). The paper is structured as follows:
The complexity of tests for autonomous vehicles is much higher, compared with conventional test procedures. Additional to vehicle states, information of the environment is incorporated in the decision making process of an autonomous vehicle. This leads to an increase of complexity, also because of predictions. General requirements of test procedures for autonomous vehicles include:
• Clear and reproducible statements.
• As easy as possible, as complex as necessary.
• Possible and adequate for all environments and situations Okumura et al. (2016) • Meaningful metrics (e.g. measures for the safety-risk-ratio) and suitable description forms • Measures for robustness and redundancy for safety reasons • Adequate for testing realistic driving scenarios Ziegler et al. (2014) • Comparison to human performance Aeberhard et al. (2015)
State of the Art
Many different aspects must be taken into account when a person moves. A human is an open, complex, biological system that interacts with its environment. Environmental influences are perceived by organs of perception and the movement is constrained by biomechanical prerequisites of the human body. In Chatziastros (2003) the visual perception of drivers is examined for dynamic environments, especially concerning psychological aspects. The Max-Planck institute for biological cybernetics. (2017) conducts basic research dealing with signal- and information processing of the human brain specifically in the perception of the environment and the resulting actions. Many research projects in the field of cybernetics use virtual reality technologies Chatziastros (2003).
Another example is Jovancevic et al. (2006) focused on attention and gaze analysis. Mathematical models for a theory of cognitive communication are described in Rupprecht (2014). In Sprague et al. (2007) models for vision and scene understanding are analysed with virtual reality environments.
Testing safety of dynamic systems can be divided in different strategies Althoff (2010). To classify a system as a safe system, it is necessary to make sure that trajectories never reach unsafe states.
The validation of technical systems is often done by simulation and experiments. If the trajectory hits the unsafe state during a simulation, the system can be declared as an unsafe dynamical system (falsification). As long as a counterexample has not been found, there is no direct way to declare the system safe. There are some exploring techniques for the state space to find the counterexample systematically Althoff (2010).
In conventional driving tests (e.g. testing vehicle dynamics), internal vehicle states have to be examined at specified manoeuvres. For autonomous driving functions, there are no standardized tests, because states of the environment are essential. It is not trivial to determine the external states and conditions that have to be used for tests in order to ensure a clear statement for the safety of the vehicle. Also, due to the diversity of situations, the number of tests for demonstrating safety is tremendous. For the reproducibility of real-world tests, some strategies are known. Steering robots are already used in experimental settings. Another strategy is to collect a large amount of data during long-term studies to ensure that the system is tested for all possible situations Winner et al. (2015). Hereby the problem of missing trajectories plays an essential role.
Soft-crash-targets and passable target robots can be used to model accident scenarios. These crash target robots are already used because they can be precisely coordinated Winner et al. (2015).
The decision making process is influenced by the interaction with other road users. The intention estimation and the prediction for the future movement of road users is vital for the motion planning of the ego-vehicle Eskandarian (2012).
Description of the Invention
The invention presents a method to virtually test traffic situations with real pedestrian interaction in real environments and dangerous driving maneuvers. The problem of testing safety critical driving scenarios with scenarios is that real persons cannot be incorporated. The idea of this invention is to use drones as pedestrians. The drones can be controlled by a test person. The test person see's what the drone sees. The drone has a camera which shows the oncoming vehicle. The flying route can be controlled by a test person, which is walking on a non-movable walking platform
In a first step, there is a wireless data transfer between the stimuli of the test person and the drone. For example a simple Skype connection with good internet conditions is adequate for this purpose. In a second step there is also a wireless data transfer between the flying drone, the motion capture system and the walking platform. The camera perspective of the drone is sent to the stimuli unit of the test person in real-time. The reaction of the test person is measured in real time in a fourth step. In a fifth step the joint states of the test person are measured. The joint states are sent to the drone. In experiments it is shown that it is enough also to have a cap with visual markers on the test person, measuring the head position, instead of measuring the whole posture. In the seventh step the gesture of the test person is converted into flying control actions.
The experiment offers a lot of advantages. Real persons are incorporated in safety critical situations with cars to increase the safety of autonomous vehicles. The interaction, real environments and the personality of the test person can be integrated in a safe experiment for testing real-life dangerous situations.
In conventional state of the art testing procedures crash target robots are used, which follow predefined trajectories and are not suited to react as real persons.
Figure Description
Fig. 1 shows an example flow-chart for a sequential procedure
Fig. 2 shows an example of the testing environment.
Fig. 3 shows the concept of the invention (see following legend)
Legend of Figure 3 • Block A: Vehicle driving in the test area with collision avoidance maneuver • Block B: Flying Drone as a pedestrian follows the movements of the test person (Block C) • Block C: Test person controls the drone and sees what the camera of the drone shows • Arrow A: Block B and Block C are connected by visual informations and information provided by physical displacements.
• Arrow B: Block A and Block B are visually connected.
• Test area: Area where vehicle and drone make safety critical driving maneuvers.
• Control area: Test person walks on a non-movable walking platform.
References • Bengler, K., Dietmayer, K., Farber, B., Maurer, M., Stiller, C., and Winner, H. (2014). Three decades of driver assistance systems: Review and future perspectives. IEEE Intelligent Transportation Systems Magazine, 6(4), 6-22.
• Chatziastros, A. (2003). Visuelle Kontrolle der Lokomotion. Ph.D. thesis, Universitatsbibliothek Giessen.
• Eskandarian, A. (2012). Handbook of intelligent vehicles. Springer London.
• Hartmann, M., Viehweger, M., Stolz, M., and Watzenig, D. (2017). Pedestrian in the Loop: An approach using virtual reality. ICAT 2017 -XXVI International Conference on Information, Communication and Automation Technologies.
• Jovancevic, J., Sullivan, B., and Hayhoe, M. (2006). Control of attention and gaze in complex environments. Journal of Vision, 6(12), 9-9.
• Okumura, B., James, M.R., Kanzawa, Y., Derry, M., Sakai, K., Nishi, T., and Prokhorov, D. (2016). Challenges in perception and decision making for intelligent automotive vehicles: A case study. IEEE Transactions on Intelligent Vehicles, 1(1), 20-32.
• Pearl, J., Glymour, M., and Jewell, N.P. (2016). Causal inference in statistics: a primer. John Wiley & Sons.
• Rupprecht, W. (2014). Einfiihrung in die Theorie der kognitiven Kommunikation: wie Sprache, Information, Energie, Internet, Gehirn und Geist zusammenhangen. Springer-Verlag.
• Sprague, N., Ballard, D., and Robinson, A. (2007). Modeling embodied visual behaviors. ACM Transactions on Applied Perception (TAP), 4(2), 11.
• Winner, H., Hakuli, S., Lotz, F., and Singer, C. (eds.) (2015). Handbuch Fahrerassistenzsysteme. ATZ/MTZ Fachbuch. Springer Vieweg, Wiesbaden, 3 edition, doi: 10.1007/978-3-658-05734-3.
• Ziegler, J., Bender, P., Schreiber, M., Lategahn, H., Strauss, T., Stiller, C., Dang, T., Franke, U., Appenrodt, N., Keller, C.G., et al. (2014). Making bertha drive - An autonomous journey on a historic route. IEEE Intelligent Transportation Systems Magazine, 6(2), 8-20.
Claims
Claims (6)
1. Method for virtual testing of vehicles and their algorithms in situations with pedestrian interaction compromising, in a first step the wireless data transfer between the drone camera and the stimuli unit of the test person in a second step the wireless data transfer between the motion capture system and walking platform of the test person and the fly control unit of the drone, in a third step the sending process of information about the camera perspective of the drone to the stimuli unit to the test person, in a fourth step the measurement of the actions of the test person as a reaction to the real perspective of the drone, in a fifth step the measurement of the joint states of the person via a motion capture system and walking platform, in a sixth step the sending process of the information of gesture and actions to the drone, in a seventh the conversion of the gesture of the person in a flying control.
2. Method according to claim 1 compromising a traffic situation between the drone and the vehicle.
3. Method according to claim 1 and 2 compromising measuring the gesture of the test person, and incorporation of the behavior for real-life dangerous situations.
4. Method according to claim 1 to 3 compromising real-time perception of the perspective of the flying drone and stimulating the perception of the test person.
5. Method according to claim 1 to 4 compromising for controlling the flying drone by a test person and control of the drone to fly as the pedestrian.
6. Method according to claim 1 to 5 compromising for increasing the safety of collision avoidance algorithms in incorporation of engineers from technical aspects and psychologists for human related aspects.
Intellectual Property Office
Application No: GB1717221.4 Examiner: Dr Michael Collett
Claims searched: 1-6 Date of search: 5 February 2018
Patents Act 1977: Search Report under Section 17
Documents considered to be relevant:
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1-6
US2012/0283896 Al
(PERSAUD)
X
1-6
US2013/0253733 Al
(LEE)
X
1-6
WO2016/168117 A2
(DANIELS)
X
1-6
CN106094861 Al (ZERO UAV)
&
-
US2017/0351253 Al
(YANG)
X
1-6
US2013/0107027 Al
(MUELLHAEUSER)
Categories:
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A
Document indicating technological background and/or state of the art.
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Document published on or after the declared priority date but
combined with one or more other documents of
before the filing date of this invention.
same category.
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Field of Search:
Search of GB, EP, WO & US patent documents classified in the following areas of the UKCX :
Worldwide search of patent documents classified in the following areas of the IPC__________________
B60W; G05D; G08G_____________________________________________
The following online and other databases have been used in the preparation of this search report______
WPI, Epodoc, Patent Fulltext, INSPEC, NPL, TDB, XPAIP, XPI3E, XPIEE, XPIOP, XPIPCOM, XPMISC
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB1717221.4A GB2569774A (en) | 2017-10-20 | 2017-10-20 | Method for virtual testing of real environments with pedestrian interaction and drones |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| GB1717221.4A GB2569774A (en) | 2017-10-20 | 2017-10-20 | Method for virtual testing of real environments with pedestrian interaction and drones |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| GB201717221D0 GB201717221D0 (en) | 2017-12-06 |
| GB2569774A true GB2569774A (en) | 2019-07-03 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| GB1717221.4A Withdrawn GB2569774A (en) | 2017-10-20 | 2017-10-20 | Method for virtual testing of real environments with pedestrian interaction and drones |
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| GB (1) | GB2569774A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114296472A (en) * | 2021-11-19 | 2022-04-08 | 浙江中控技术股份有限公司 | Weighing process testing system and method based on unmanned aerial vehicle |
| US11505134B1 (en) | 2021-05-25 | 2022-11-22 | Motional Ad Llc | Automated moving platform |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20120283896A1 (en) * | 2011-05-04 | 2012-11-08 | Qualcomm Incorporated | Gesture recognition via an ad-hoc proximity sensor mesh for remotely controlling objects |
| US20130107027A1 (en) * | 2011-10-27 | 2013-05-02 | Deutsches Zentrum Fuer Luft- Und Raumfahrt E.V. | Control and monitoring device for vehicle |
| US20130253733A1 (en) * | 2012-03-26 | 2013-09-26 | Hon Hai Precision Industry Co., Ltd. | Computing device and method for controlling unmanned aerial vehicle in flight space |
| WO2016168117A2 (en) * | 2015-04-14 | 2016-10-20 | John James Daniels | Wearable electric, multi-sensory, human/machine, human/human interfaces |
| CN106094861A (en) * | 2016-06-02 | 2016-11-09 | 零度智控（北京）智能科技有限公司 | Unmanned plane, unmanned aerial vehicle (UAV) control method and device |
-
2017
- 2017-10-20 GB GB1717221.4A patent/GB2569774A/en not_active Withdrawn
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120283896A1 (en) * | 2011-05-04 | 2012-11-08 | Qualcomm Incorporated | Gesture recognition via an ad-hoc proximity sensor mesh for remotely controlling objects |
| US20130107027A1 (en) * | 2011-10-27 | 2013-05-02 | Deutsches Zentrum Fuer Luft- Und Raumfahrt E.V. | Control and monitoring device for vehicle |
| US20130253733A1 (en) * | 2012-03-26 | 2013-09-26 | Hon Hai Precision Industry Co., Ltd. | Computing device and method for controlling unmanned aerial vehicle in flight space |
| WO2016168117A2 (en) * | 2015-04-14 | 2016-10-20 | John James Daniels | Wearable electric, multi-sensory, human/machine, human/human interfaces |
| CN106094861A (en) * | 2016-06-02 | 2016-11-09 | 零度智控（北京）智能科技有限公司 | Unmanned plane, unmanned aerial vehicle (UAV) control method and device |
| US20170351253A1 (en) * | 2016-06-02 | 2017-12-07 | Zerotech (Shenzhen) Intelligence Robot Co., Ltd | Method for controlling an unmanned aerial vehicle |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11505134B1 (en) | 2021-05-25 | 2022-11-22 | Motional Ad Llc | Automated moving platform |
| GB2607130A (en) * | 2021-05-25 | 2022-11-30 | Motional Ad Llc | Automated moving platform |
| CN114296472A (en) * | 2021-11-19 | 2022-04-08 | 浙江中控技术股份有限公司 | Weighing process testing system and method based on unmanned aerial vehicle |
| CN114296472B (en) * | 2021-11-19 | 2024-02-27 | 中控技术股份有限公司 | Weighing flow test system and method based on unmanned aerial vehicle |
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| Publication number | Publication date |
|---|---|
| GB201717221D0 (en) | 2017-12-06 |
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