Generating a location in a vehicle-to-vehicle communication system

• US 8,935,094 B2
• Filed: 07/26/2012
• Issued: 01/13/2015
• Est. Priority Date: 04/24/2012
• Status: Active Grant

• Current Assignee: Zetta Research and Development LLC (Zetta Research, LLC)
• Original Assignee: Zetta Research and Development LLC - FORC Series
• Inventors: Rubin, Kim T, Betts-Lacroix, Jonathan N.
• Primary Examiner(s): Badii, Behrang
• Application Number:
  US13/559,493
• Publication Number:
  US 20130282277A1
• Time in Patent Office: 901 Days
• Field of Search: 701/2, 701/41, 701/70, 701/31.4, 701/817, 701/117, 701/301, 701/115, 701/300, 701/532, 246/473.1, 707/E17.009, 707/758, 707/749, 340/436, 340/903, 180/168, 455/466, 370/328
• US Class Current: 701/517
• CPC Class Codes: B60R 2325/205 Mobile phones
• CPC Class Codes: B60R 25/33 of global position, e.g. by providing GPS coordinates
• CPC Class Codes: B60W 10/06 including control of combustion engines
• CPC Class Codes: B60W 10/18 including control of braking systems
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G01C 21/3658 Lane guidance
• CPC Class Codes: G01C 21/3822 Road feature data, e.g. slope data
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G08G 1/09 Arrangements for giving variable traffic instructions railroad crossing signals B61L; reflectors E01F, G08B; indicating arrangements for variable information by selection or combination of individual elements G09F9/00
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/0969 having a display in the form of a map
• CPC Class Codes: G08G 1/142 external to the vehicles
• CPC Class Codes: G08G 1/16 Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08
• CPC Class Codes: G08G 1/161 Decentralised systems, e.g. inter-vehicle communication
• CPC Class Codes: G08G 1/163 involving continuous checking
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: G08G 1/20 : Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• CPC Class Codes: G08G 9/02 : Anti-collision systems
• CPC Class Codes: H04J 3/1694 : Allocation of channels in TDM/TDMA networks, e.g. distributed multiplexers Passive Optical Networks H04Q11/0062
• CPC Class Codes: H04L 5/0091 : Signaling for the administration of the divided path
• CPC Class Codes: H04W 4/027 : using movement velocity, acceleration information
• CPC Class Codes: H04W 4/06 : Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
• CPC Class Codes: H04W 4/46 : for vehicle-to-vehicle communication [V2V]
• CPC Class Codes: H04W 4/48 : for in-vehicle communication
• CPC Class Codes: H04W 56/0035 : detecting errors in frequency or phase
• CPC Class Codes: H04W 64/006 : with additional information processing, e.g. for direction or speed determination
• CPC Class Codes: H04W 72/0446 : Resources in time domain, e.g. slots or frames
• CPC Class Codes: H04W 72/30 : Resource management for broadcast services
• CPC Class Codes: H04W 74/0816 : with collision avoidance
• CPC Class Codes: H04W 76/14 : Direct-mode setup
• CPC Class Codes: H04W 76/40 : for selective distribution or broadcast

Abstract

Device, system and method, in a vehicle communication system, of generating a location by the use of combining the rough locations of a “consensus set” of vehicles within wireless communication range to produce more accurate locations of the vehicles in the consensus set. Unique features of some embodiments include the continual re-computation and re-adjustment of both the vehicles in the consensus set and the more accurate locations. Embodiments use sensors on a first vehicle, such as cameras, sonar, radar and LIDAR to determine the relative location of the second vehicle to the first vehicle. Embodiments use this relative location in the computation of the more accurate locations. Algorithms are described for the computation, communication, convergence and updating of the more accurate locations. Algorithms are described for generation and update of the consensus set.

Claims

1. A method generating a vehicle-to-vehicle (V2V) location, comprising:

selecting a group of vehicles, the “

range set,”

within V2V wireless communication range of each other, wherein each vehicle in the range set comprises an operating V2V transceiver transmitting V2V messages comprising V2V location data and wherein the range set includes a self vehicle;

selecting at least two vehicles within the range set, “

the consensus set,”

wherein each non-self vehicle in the set is located, relative to the self vehicle, using one or more “

near vehicle sensors;

”

determining by use of the near vehicle sensor(s) the relative location of each non-self vehicle in the consensus set, the “

relative vehicle location;

”

receiving a V2V location messages from at least one non-self vehicle in the range set, wherein the location message comprises V2V location data;

comparing the received location data of the vehicles in the range set to the relative vehicle locations in the consensus set;

creating a “

match list”

of all vehicles in the consensus set where the relative location reasonably matches the V2V location data;

generating an “

error list,”

comprising the difference in location, in at least two distinct axes, between the relative vehicle location and the V2V location data for at least one vehicle in the match list;

averaging the values in the error list, for each of the distinct axes, generating at least two distinct “

average error values;

”

determining a “

geo-position location”

of the self vehicle for each of the distinct axes;

transmitting a V2V message comprising location data for the self vehicle wherein, for each of the distinct axes;

wherein the transmitted data comprises the sum of the geo-position location and at least a portion of the average error value;

repeating the prior steps;

such that at least two of the vehicles in the consensus set converge toward average error values for the consensus set.

2. The method generating a V2V location of claim 1 wherein:

at least one near vehicle sensor is a radar mounted on the self vehicle.

3. The method generating a V2V location of claim 1 wherein:

at least one near vehicle sensor is a sonar mounted on the self vehicle.

4. The method generating a V2V location of claim 1 wherein:

at least one near vehicle sensor is one or more cameras mounted on the self vehicle.

5. The method generating a V2V location of claim 4 wherein:

the mounting location for the one or more cameras is proximal to or part of at least one vehicle lamp assembly.

6. The method generating a V2V location of claim 4 wherein:

at least one axis of vehicle location of a selected vehicle in the consensus set is determined by comparing the image location of the selected vehicle in at least two camera images, wherein the camera images are from at least two of the cameras mounted on the self vehicle.

7. The method generating a V2V location of claim 4 wherein:

the number of cameras mounted on the self vehicle is sufficient such that a majority of nearby vehicles appear in the images of at least two cameras.

8. The method generating a V2V location of claim 1 wherein:

at least one axis of vehicle location of a selected vehicle in the consensus set is determined by a distance measurement using sonar, from a sonar sensor mounted on at least one of the locations on the self vehicle in the Markush group;

(front, side, back).

9. The method generating a V2V location of claim 1 comprising the further step:

for each axis of each vehicle in the consensus set, excluding that axis for that vehicle from the error list, when the accuracy of the relative vehicle location is less than the difference between the relative vehicle location and the V2V location data.

10. The method generating a V2V location of claim 1 comprising the further step:

limiting the rate of change of transmitted location data from the self vehicle to a predetermined maximum rate of change.

11. The method generating a V2V location of claim 10 wherein:

the maximum rate of change is 1 m/s per second for moving vehicles and 0.1 m/s for stopped vehicles.

12. The method generating a V2V location of claim 1 comprising the additional step:

excluding from altering its own V2V transmitted location are pre-calibrated, fixed location, V2V transceivers.

13. The method generating a V2V location of claim 1 comprising the additional steps:

mounting a visual target;

transmitting a V2V location message for the visual target location wherein the geoposition of the visual target location is calibrated and wherein the V2V transmitter is approximately in a horizontal plane coincident with the visual target;

wherein the visual target is cylindrically curved such that it is clearly visible from multiple directions.

14. The method generating a V2V location of claim 13 wherein:

the visual target comprises contrasting vertical lines.

15. The method generating a V2V location of claim 13 wherein:

the visual target is mounted on a signal light supporting structure.

16. A wireless V2V transceiver comprising:

one or more near vehicle sensors;

a V2V computation module operatively connected to the one or more near vehicle sensors;

wherein the V2V computation module is configured to perform the following steps;

selecting a group of vehicles, the “

range set,”

within V2V wireless communication range of each other, wherein each vehicle in the range set comprises an operating V2V transceiver transmitting V2V messages comprising V2V location data and wherein the range set includes a self vehicle;

selecting at least two vehicles within the range set, “

the consensus set,”

wherein each non-self vehicle in the set is located, relative to the self vehicle, using the one or more near vehicle sensors;

determining by use of the near vehicle sensor(s) the relative location of each non-self vehicle in the consensus set, the “

relative vehicle location;

”

receiving a V2V location messages from at least one non-self vehicle in the range set, wherein the location message comprises V2V location data;

comparing the received location data of the vehicles in the range set to the relative vehicle locations in the consensus set;

creating a “

match list”

of all vehicles in the consensus set where the relative location reasonably matches the V2V location data;

generating an “

error list,”

comprising the difference in location, in at least two distinct axes, between the relative vehicle location and the V2V location data for at least one vehicle in the match list;

averaging the values in the error list, for each of the distinct axes, generating at least two distinct “

average error values;

”

determining a “

geo-position location”

of the self vehicle for each of the distinct axes;

transmitting a V2V message comprising location data for the self vehicle wherein, for each of the distinct axes;

wherein the transmitted data comprises the sum of the geo-position location and at least a portion of the average error value;

repeating the prior steps;

such that at least two of the vehicles in the consensus set converge toward average error values for the consensus set.

17. A V2V anti-collision system comprising at least two transceivers in wireless communication wherein each transceiver is configured to implement the following steps:

selecting a group of vehicles, the “

range set,”

within V2V wireless communication range of each other, wherein each vehicle in the range set comprises an operating V2V transceiver transmitting V2V messages comprising V2V location data and wherein the range set includes a self vehicle;

selecting at least two vehicles within the range set, “

the consensus set,”

wherein each non-self vehicle in the set is located, relative to the self vehicle, using one or more “

near vehicle sensors;

”

determining by use of the near vehicle sensor(s) the relative location of each non-self vehicle in the consensus set, the “

relative vehicle location;

”

receiving a V2V location messages from at least one non-self vehicle in the range set, wherein the location message comprises V2V location data;

comparing the received location data of the vehicles in the range set to the relative vehicle locations in the consensus set;

creating a “

match list”

of all vehicles in the consensus set where the relative location reasonably matches the V2V location data;

generating an “

error list,”

comprising the difference in location, in at least two distinct axes, between the relative vehicle location and the V2V location data for at least one vehicle in the match list;

averaging the values in the error list, for each of the distinct axes, generating at least two distinct “

average error values;

”

determining a “

geo-position location”

of the self vehicle for each of the distinct axes;

transmitting a V2V message comprising location data for the self vehicle wherein, for each of the distinct axes;

wherein the transmitted data comprises the sum of the geo-position location and at least a portion of the average error value;

repeating the prior steps;

such that at least two of the vehicles in the consensus set converge toward average error values for the consensus set.