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An apparatus and method of providing portable and personalized infotainment via an in-vehicle system of a vehicle from an infotainment content provider is provided. The method includes registering at least one mobile device with the invehicle system of the vehicle upon the at least one mobile device entering a defined location about the vehicle, receiving infotainment content at the at least one registered mobile device via the in-vehicle system of the vehicle while the at least one registered mobile device is within the defined location about the vehicle, and receiving the infotainment content at the at least one registered mobile device via another network upon the at least one mobile device leaving the defined location about the vehicle.

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Patent
Dura, Llc | Date: 2017-01-25

A method for fusing sensor information detected by a host vehicle and at least one remote vehicle-to-vehicle ( V2V ) communication equipped vehicle includes collecting visual data from an optical sensor of a vision sub-system, and collecting V2V data from remote vehicles. The method further includes executing a control logic including a first control logic for generating a base lane model and a base confidence level, a second control logic that fuses together the V2V data, the base lane model, and the base confidence level, and a third control logic that generates from the fused lane model, the V2V data, the base lane model, and the base confidence level, a final lane model and final confidence level, and assigns a priority to the final lane model.

Claims which contain your search:

1. A method for fusing sensor information detected by a host vehicle and at least one remote vehicle-to-vehicle (V2V) communication equipped vehicle, the method comprising:collecting visual data from an optical sensor of a vision sub-system, and generating a base lane model and a base confidence level;collecting V2V data from a receiver of a V2V sub-system;generating a base lane model and a base confidence level from the visual data;fusing together the V2V data, the base lane model, and the base confidence level;generating a final lane model with a final confidence level from the fused together V2V data, the base lane model and the base confidence level; andassigning a priority to the final lane model.

3. The method of claim 2 wherein the base lane model and the final lane model comprise lane positioning, lane markings, lane curvature, speed, and trajectory data for the host vehicle and for any objects within a predefined area around the host vehicle.

4. The method of claim 3 wherein the V2V data comprises lane positioning, speed, and trajectory data for any remote V2V equipped vehicles in communication with the host vehicle and within a predefined area around the host vehicle, and for any objects sensed by any remote V2V vehicles in communication with the host vehicle and within a predefined area around the host vehicle

5. The method of claim 1, wherein the fusing together of the V2V data, the base lane model, and the base confidence level further comprises comparing the visual data to the V2V data and determining a relative accuracy and precision of the visual data and the V2V data.

6. The method of claim 5 wherein the assigning a priority to the final lane model further comprises determining a location of an object in the final lane model relative to the host vehicle and assigning a high priority to the object when the object is in a lane also occupied by the host vehicle.

7. The method of claim 6 further comprises sending a command to at least one advanced driver assistance system (ADAS), and wherein the at least one ADAS performs a function to avoid the object to which a high priority has been assigned.

8. A system for fusing sensor information detected by a host vehicle and at least one remote vehicle-to-vehicle (V2V) communication equipped vehicle, the system comprising:a vision sub-system having an optical sensor;a V2V sub-system having a receiver;a controller in communication with the vision sub-system and the V2V sub-system, the controller having memory for storing control logic and a processor configured to execute the control logic, the control logic including a first control logic for collecting visual data from the vision sub-system, and from the visual data generating a base lane model and a base confidence level;the processor including a second control logic for collecting V2V data from the V2V sub-system, and for fusing together the V2V data and the base lane model and base confidence level;the processor including a third control logic for generating, from the fused V2V data, base lane model and base confidence level, a final lane model with a final confidence level; andthe processor including a fourth logic for assigning a priority to the final lane model.

10. The system of claim 9 wherein the base and the final lane models comprise lane positioning, lane markings, lane curvature, speed, and trajectory data for the host vehicle and for any objects within a predefined area around the host vehicle.

11. The system of claim 10 wherein the V2V data comprises lane positioning, speed, and trajectory data for any remote V2V equipped vehicles in communication with the host vehicle and within a predefined area around the host vehicle, and for any objects sensed by any remote V2V vehicles in communication with the host vehicle and within a predefined area around the host vehicle.

12. The system of claim 8, wherein the controller fuses together further comprises comparing the visual data to the V2V data and determining an accuracy and a precision of the visual data and the V2V data.

13. The system of claim 12 wherein the fourth logic further comprises determining a location of an object in the final lane model relative to the host vehicle and assigning a high priority to the object when the object is in a lane also occupied by the host vehicle.

14. The system of claim 13 wherein information about the object that has been assigned a high priority is passed to the at least one ADAS, and the at least one ADAS performs a function to avoid the object.

...
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Organizations compared on records for related keywords
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Evolution of record type per year
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Weight of records per source
Name Score Publications Conferences Grants Patents Trademarks News Webs
488.4 10 10 10 10 10 10 10
258.8 10 10 10 10 10 10 10
144.9 10 10 10 10 10 10 10
143.3 10 10 10 10 10 10 10
123.2 10 10 10 10 10 10 10
104.8 10 10 10 10 10 10 10
V2X
100.8 10 10 10 10 10 10 10
100.1 10 10 10 10 10 10 10
88.8 10 10 10 10 10 10 10
84.9 10 10 10 10 10 10 10
79.3 10 10 10 10 10 10 10
76.2 10 10 10 10 10 10 10
75.3 10 10 10 10 10 10 10
74.0 10 10 10 10 10 10 10
67.0 10 10 10 10 10 10 10
66.0 10 10 10 10 10 10 10
62.3 10 10 10 10 10 10 10
57.9 10 10 10 10 10 10 10
IBM
54.9 10 10 10 10 10 10 10
51.6 10 10 10 10 10 10 10
51.5 10 10 10 10 10 10 10
51.4 10 10 10 10 10 10 10
50.1 10 10 10 10 10 10 10
49.1 10 10 10 10 10 10 10
49.0 10 10 10 10 10 10 10
46.4 10 10 10 10 10 10 10
43.8 10 10 10 10 10 10 10
43.8 10 10 10 10 10 10 10
IVI
41.4 10 10 10 10 10 10 10
40.3 10 10 10 10 10 10 10
40.1 10 10 10 10 10 10 10
39.0 10 10 10 10 10 10 10
37.3 10 10 10 10 10 10 10
CCE
34.1 10 10 10 10 10 10 10
33.3 10 10 10 10 10 10 10
32.9 10 10 10 10 10 10 10
32.6 10 10 10 10 10 10 10
32.2 10 10 10 10 10 10 10
31.8 10 10 10 10 10 10 10
30.9 10 10 10 10 10 10 10
29.6 10 10 10 10 10 10 10
29.6 10 10 10 10 10 10 10
29.5 10 10 10 10 10 10 10
29.4 10 10 10 10 10 10 10
27.5 10 10 10 10 10 10 10
27.1 10 10 10 10 10 10 10
26.9 10 10 10 10 10 10 10
26.6 10 10 10 10 10 10 10
26.1 10 10 10 10 10 10 10
26.1 10 10 10 10 10 10 10
26.0 10 10 10 10 10 10 10
25.5 10 10 10 10 10 10 10
25.4 10 10 10 10 10 10 10
24.5 10 10 10 10 10 10 10
24.2 10 10 10 10 10 10 10
24.1 10 10 10 10 10 10 10
JBL
24.1 10 10 10 10 10 10 10
24.0 10 10 10 10 10 10 10
23.8 10 10 10 10 10 10 10
23.4 10 10 10 10 10 10 10
Argus Cyber Security
23.3 - - - 10 10 10 10
University of Waterloo
22.6 12 7 - 10 10 10 10
KPMG
22.2 - - - 10 10 10 10
University of Michigan
22.2 9 19 2 10 10 10 10
Robert Bosch GmbH
22.2 1 7 - 10 10 10 10
Telenav Inc.
22.1 - - - 10 10 10 10
Best Buy
22.0 - - - 10 10 10 10
Cadillac
21.1 - - - 10 10 10 10
QNX Software Systems
20.9 - - - 10 10 10 10
Continental AG
20.7 - 4 1 10 10 10 10
HAR
20.5 - - - 10 10 10 10
T-Mobile
20.4 - - - 10 10 10 10
ZTE
20.4 - - - 10 10 10 10
About Harman
20.3 - - - 10 10 10 10
Verizon Telematics
20.0 - - - 10 10 10 10
Intel Corporation
19.4 2 4 2 10 10 10 10
TomTom
19.3 - - - 10 10 10 10
Cisco Systems
19.1 2 - 1 10 10 10 10
Ericsson AB
18.8 1 4 - 10 10 10 10
Reportbuyer
18.7 - - - 10 10 10 10
Hyundai America Technical Center Inc.
18.7 - - - 10 10 10 10
Technavio
17.9 - - - 10 10 10 10
Nuance Communications
17.9 - - - 10 10 10 10
Tencent
17.5 - - - 10 10 10 10
Zetta Research And Development Llc Forc Series
17.3 - - - 10 10 10 10
Harman International
17.2 - - - 10 10 10 10
Chalmers University of Technology
16.6 5 16 - 10 10 10 10
Tesla Motors
16.5 - - - 10 10 10 10
MWC
16.2 - - - 10 10 10 10
Cinemo Inc.
16.2 - - - 10 10 10 10
Lidar
16.0 - - - 10 10 10 10
Beijing Jiaotong University
16.0 29 22 - 10 10 10 10
Smart Home
15.8 - - - 10 10 10 10
Automatic Labs Inc.
15.7 - - - 10 10 10 10
Walmart
15.7 - - - 10 10 10 10
YouTube
15.6 - - - 10 10 10 10
Renesas Electronics Corporation
15.5 - - - 10 10 10 10
Harman
15.5 - - - 10 10 10 10
SK Telecom
15.4 - - - 10 10 10 10
Kawasaki Heavy Industries
15.3 - - - 10 10 10 10

An apparatus and method of providing portable and personalized infotainment via an in-vehicle system of a vehicle from an infotainment content provider is provided. The method includes registering at least one mobile device with the invehicle system of the vehicle upon the at least one mobile device entering a defined location about the vehicle, receiving infotainment content at the at least one registered mobile device via the in-vehicle system of the vehicle while the at least one registered mobile device is within the defined location about the vehicle, and receiving the infotainment content at the at least one registered mobile device via another network upon the at least one mobile device leaving the defined location about the vehicle.


Patent
Dura, Llc | Date: 2017-01-25

A method for fusing sensor information detected by a host vehicle and at least one remote vehicle-to-vehicle ( V2V ) communication equipped vehicle includes collecting visual data from an optical sensor of a vision sub-system, and collecting V2V data from remote vehicles. The method further includes executing a control logic including a first control logic for generating a base lane model and a base confidence level, a second control logic that fuses together the V2V data, the base lane model, and the base confidence level, and a third control logic that generates from the fused lane model, the V2V data, the base lane model, and the base confidence level, a final lane model and final confidence level, and assigns a priority to the final lane model.

Claims which contain your search:

1. A method for fusing sensor information detected by a host vehicle and at least one remote vehicle-to-vehicle (V2V) communication equipped vehicle, the method comprising:collecting visual data from an optical sensor of a vision sub-system, and generating a base lane model and a base confidence level;collecting V2V data from a receiver of a V2V sub-system;generating a base lane model and a base confidence level from the visual data;fusing together the V2V data, the base lane model, and the base confidence level;generating a final lane model with a final confidence level from the fused together V2V data, the base lane model and the base confidence level; andassigning a priority to the final lane model.

3. The method of claim 2 wherein the base lane model and the final lane model comprise lane positioning, lane markings, lane curvature, speed, and trajectory data for the host vehicle and for any objects within a predefined area around the host vehicle.

4. The method of claim 3 wherein the V2V data comprises lane positioning, speed, and trajectory data for any remote V2V equipped vehicles in communication with the host vehicle and within a predefined area around the host vehicle, and for any objects sensed by any remote V2V vehicles in communication with the host vehicle and within a predefined area around the host vehicle

5. The method of claim 1, wherein the fusing together of the V2V data, the base lane model, and the base confidence level further comprises comparing the visual data to the V2V data and determining a relative accuracy and precision of the visual data and the V2V data.

6. The method of claim 5 wherein the assigning a priority to the final lane model further comprises determining a location of an object in the final lane model relative to the host vehicle and assigning a high priority to the object when the object is in a lane also occupied by the host vehicle.

7. The method of claim 6 further comprises sending a command to at least one advanced driver assistance system (ADAS), and wherein the at least one ADAS performs a function to avoid the object to which a high priority has been assigned.

8. A system for fusing sensor information detected by a host vehicle and at least one remote vehicle-to-vehicle (V2V) communication equipped vehicle, the system comprising:a vision sub-system having an optical sensor;a V2V sub-system having a receiver;a controller in communication with the vision sub-system and the V2V sub-system, the controller having memory for storing control logic and a processor configured to execute the control logic, the control logic including a first control logic for collecting visual data from the vision sub-system, and from the visual data generating a base lane model and a base confidence level;the processor including a second control logic for collecting V2V data from the V2V sub-system, and for fusing together the V2V data and the base lane model and base confidence level;the processor including a third control logic for generating, from the fused V2V data, base lane model and base confidence level, a final lane model with a final confidence level; andthe processor including a fourth logic for assigning a priority to the final lane model.

10. The system of claim 9 wherein the base and the final lane models comprise lane positioning, lane markings, lane curvature, speed, and trajectory data for the host vehicle and for any objects within a predefined area around the host vehicle.

11. The system of claim 10 wherein the V2V data comprises lane positioning, speed, and trajectory data for any remote V2V equipped vehicles in communication with the host vehicle and within a predefined area around the host vehicle, and for any objects sensed by any remote V2V vehicles in communication with the host vehicle and within a predefined area around the host vehicle.

12. The system of claim 8, wherein the controller fuses together further comprises comparing the visual data to the V2V data and determining an accuracy and a precision of the visual data and the V2V data.

13. The system of claim 12 wherein the fourth logic further comprises determining a location of an object in the final lane model relative to the host vehicle and assigning a high priority to the object when the object is in a lane also occupied by the host vehicle.

14. The system of claim 13 wherein information about the object that has been assigned a high priority is passed to the at least one ADAS, and the at least one ADAS performs a function to avoid the object.


A method of generating and communicating lane information from a host vehicle to a vehicle-to-vehicle ( V2V ) network includes collecting visual data from a camera, detecting a lane within the visual data, generating a lane classification for the lane based on the visual data, assigning a confidence level to the lane classification, generating a lane distance estimate from the visual data, generating a lane model from the lane classification and the lane distance estimate, and transmitting the lane model and the confidence level to the V2V network.

Claims which contain your search:

1. A method of generating and communicating lane information from a host vehicle to a vehicle-to-vehicle ( V2V ) network, the method comprising:collecting visual data from a camera;detecting a lane within the visual data;generating a lane classification for the lane based on the visual data;assigning a confidence level to the lane classification;generating a lane distance estimate from the visual data;generating a lane model from the lane classification and the lane distance estimate; andtransmitting the lane model and the confidence level to the V2V network.

2. The method of claim 1 wherein the camera comprises a front camera mounted to a front-facing surface of the host vehicle.

3. The method of claim 1 wherein the detecting a plurality of lanes further comprises determining a position, a width, a curvature, a topography, a distance of each of the plurality of lanes relative to a reference position on the host vehicle, and a color and a shape of a plurality of lane markers for the plurality of lanes.

4. The method of claim 3 wherein the generating a lane classification further comprises comparing the color and the shape of the plurality of lane markers to a library of colors and shapes of known lane markers.

5. The method of claim 1 wherein the generating a lane distance estimate further comprises mathematically interpolating from the visual data the distance from a lane edge relative to a reference position on the host vehicle.

6. The method of claim 1 wherein the V2V network includes at least one remote V2V equipped vehicle.

7. The method of claim 6 further comprising scanning a predetermined area for remote V2V equipped vehicles within a predefined range of the host vehicle.

8. The method of claim 7 wherein transmitting the lane model and confidence level further comprises periodically transmitting the lane model and confidence level over the V2V network.

9. The method of claim 8 wherein transmitting the lane model and confidence level further comprises transmitting the lane model and confidence level immediately upon determining that the remote V2V equipped vehicle is within the predefined range of the host vehicle.

10. A system for generating and communicating lane information from a host vehicle to a vehicle-to-vehicle ( V2V ) network, the system comprising:a camera;a V2V sub-system having a receiver and a transmitter;a controller in communication with the camera and the V2V sub-system, the controller having memory for storing control logic and a processor configured to execute the control logic, the control logic including a first control logic for collecting visual data from the camera, a second control logic for detecting a lane within the visual data, a third control logic for generating a lane classification for the lanes based on the visual data, a fourth control logic for assigning a base confidence level to the lane classification, a fifth control logic for generating a lane distance estimate from the visual data, a sixth control logic for generating a base lane model from the lane classification and the lane distance estimate, a seventh control logic for generating a formatted lane model and a formatted confidence level, and an eighth control logic for selectively transmitting the formatted lane model and the confidence level to the V2V network.

11. The system of claim 10 wherein the camera comprises a plurality of cameras attached to the host vehicle.

12. The system of claim 11 wherein the base and formatted lane models comprise lane positioning, lane markings, lane curvature, speed, and trajectory data for the host vehicle.

13. The system of claim 12 wherein the seventh control logic further comprises aligning the base lane model and base confidence level to a standardized communications protocol.

14. The system of claim 10 wherein the selectively transmitting further comprises periodically transmitting the formatted lane model and formatted confidence level over the V2V communications network and when a V2V equipped vehicle appears within a predefined range of the host vehicle, automatically transmitting the formatted lane model and formatted confidence level over the V2V communications network.


Patent
Qualcomm | Date: 2015-08-10

A method, an apparatus, and a computer program product for wireless communication are provided. The apparatus receives information indicating a number of physical resource blocks (PRBs) from a base station. Additionally, the apparatus determines a discovery resource of a plurality of discovery resources for device-to-device (D2D) discovery. In some examples, a size of the discovery resource being based on the received information indicating the number of PRBs. The apparatus also transmits a discovery signal on the discovery resource. In another example, the apparatus receives information indicating a number of physical resource blocks (PRBs) from a base station. Additionally, the apparatus also determines a plurality of discovery resources for device-to-device (D2D) discovery. In some examples, a size of each of the plurality of discovery resources being based on the received information indicating the number of PRBs. The apparatus also receives at least one discovery signal on the plurality of discovery resources.

Claims which contain your search:

2. The method of claim 1, further comprising receiving information indicating an MCS index to be used for transmitting a discovery signal.

9. An apparatus for wireless communication at a transmitting user equipment (UE), comprising: a memory; and at least one processor coupled to the memory and configured to:receive information indicating a number of physical resource blocks (PRBs) from a base station;determine a discovery resource of a plurality of discovery resources for device-to-device (D2D) discovery, a size of the discovery resource being based on the received information indicating the number of PRBs; andtransmit a discovery signal on the discovery resource.

10. The apparatus of claim 9, wherein the at least one processor is further configured to receive information indicating an MCS index to be used for transmitting a discovery signal.

12. The apparatus of claim 11, wherein the at least one processor is further configured to determine a second transport block size for transmitting a discovery signal based on the first transport block size for D2D discovery.

14. The apparatus of claim 13, wherein the at least one processor is further configured to transmit information indicating the second transport block size through a demodulation reference signal (DMRS) of the discovery signal by selecting a cyclic shift, or base sequence or an orthogonal cover code of DMRS.

18. The apparatus of claim 17, further comprising means for receiving information indicating an MCS index to be used for transmitting a discovery signal.

26. The computer-readable medium of claim 25, further comprising code for receiving information indicating an MCS index to be used for transmitting a discovery signal.


Patent
Ibm | Date: 2015-08-25

Contextualizing vehicle data and predicting real-time driver actions. By unsiloing collected data relating to a driver, the actions of the driver can be predicted and the reasons for variations from the predicted actions can be determined based on the contextualized data.

Claims which contain your search:

1. A method comprising: determining a driver of a vehicle based, at least in part, on a set of data collected from a set of vehicle data sensors; gathering a set of context data from the set of vehicle data sensors and a set of external data sensors; and predicting a set of actions to be taken by the driver based, at least in part, on the set of context data; wherein:the set of vehicle data sensors captures data within the vehicle;the set of external sensors captures data external to the vehicle; andat least determining the driver is performed by computer software running on computer hardware.

3. The method of claim 1, further comprising: determining that the driver did not take at least one action in the predicted set of actions; and taking a preventative action; wherein:a preventative action is one of: communicating with the driver, communicating with a second vehicle, or communicating with a public safety system.

4. The method of claim 1, wherein the set of data collected from a set of vehicle data sensors includes a set of biometric data identifying the driver.

5. The method of claim 1, wherein predicting a set of actions to be taken by the driver occurs in real-time.

6. The method of claim 1, wherein determining the driver of the vehicle includes: comparing the set of data collected from the set of vehicle data sensors to a set of stored driver profiles; and determining a driver profile that corresponds to the driver.

7. The method of claim 6, wherein predicting the set of actions to be taken by the driver includes: analyzing the set of context data; analyzing the driver profile that corresponds to the driver; and determining the set of actions to be taken by the driver, based on the set of context data and the driver profile that corresponds to the driver; wherein:the driver profile that corresponds to the driver includes a set of historical driver data based, at least in part, on a set of previous driving events.

8. A computer program product comprising: a computer readable storage medium having stored thereon:first instructions executable by a device to cause the device to determine a driver of a vehicle based, at least in part, on a set of data collected from a set of vehicle data sensors;second instructions executable by a device to cause the device to gather a set of context data from the set of vehicle data sensors and a set of external data sensors; andthird instructions executable by a device to cause the device to predict a set of actions to be taken by the driver based, at least in part, on the set of context data;wherein:

10. The computer program product of claim 8, further comprising: fourth instructions executable by a device to cause the device to determine that the driver did not take at least one action in the predicted set of actions; and fifth instructions executable by a device to cause the device to take a preventative action; wherein:a preventative action is one of: communicating with the driver, communicating with a second vehicle, or communicating with a public safety system.

11. The computer program product of claim 8, wherein the set of data collected from a set of vehicle data sensors includes a set of biometric data identifying the driver.

12. The computer program product of claim 8, wherein the third instructions to predict a set of actions to be taken by the driver occurs in real-time.

13. The computer program product of claim 8, wherein first instructions to determine the driver of the vehicle include: fourth instructions executable by a device to cause the device to compare the set of data collected from the set of vehicle data sensors to a set of stored driver profiles; and fifth instructions executable by a device to cause the device to determine a driver profile that corresponds to the driver.

14. A computer system comprising: a processor set; and a computer readable storage medium; wherein:the processor set is structured, located, connected, and/or programmed to run instructions stored on the computer readable storage medium; andthe instructions include:

16. The computer system of claim 14, further comprising: fourth instructions executable by a device to cause the device to determine that the driver did not take at least one action in the predicted set of actions; and fifth instructions executable by a device to cause the device to take a preventative action; wherein:a preventative action is one of: communicating with the driver, communicating with a second vehicle, or communicating with a public safety system.

17. The computer system of claim 14, wherein the set of data collected from a set of vehicle data sensors includes a set of biometric data identifying the driver.

18. The computer system of claim 14, wherein the third instructions to predict a set of actions to be taken by the driver occurs in real-time.

19. The computer system of claim 14, wherein first instructions to determine the driver of the vehicle include: fourth instructions executable by a device to cause the device to compare the set of data collected from the set of vehicle data sensors to a set of stored driver profiles; and fifth instructions executable by a device to cause the device to determine a driver profile that corresponds to the driver.

20. The computer system of claim 19, wherein predicting the set of actions to be taken by the driver includes: sixth instructions executable by a device to cause the device to analyze the set of context data; seventh instructions executable by a device to cause the device to analyze the driver profile that corresponds to the driver; and eighth instructions executable by a device to cause the device to determine the set of actions to be taken by the driver, based on the set of context data and the driver profile that corresponds to the driver; wherein:the driver profile that corresponds to the driver includes a set of historical driver data based, at least in part, on a set of previous driving events.


A method for classifying a target using path history data during vehicle to vehicle ( V2V ) communication of a V2V communication system includes receiving the path history data from a relative vehicle, calculating a longitudinal distance from a self vehicle to the relative vehicle in relation to a heading direction of the self vehicle using the path history data, and classifying a target position of the relative vehicle using the path history data depending on the calculated longitudinal distance.

Claims which contain your search:

1. A method for classifying a target using path history data during vehicle to vehicle ( V2V ) communication of a V2V communication system, the method comprising: receiving the path history data from a relative vehicle; calculating a longitudinal distance from a self vehicle to the relative vehicle in relation to a heading direction of the self vehicle using the path history data; and classifying a target position of the relative vehicle using the path history data depending on the calculated longitudinal distance.

2. The method according to claim 1, wherein the step of calculating of the longitudinal distance from the self vehicle to the relative vehicle in relation to the heading direction of the self vehicle using the path history data includes: converting global positioning system (GPS) coordinate values of the self vehicle and the relative vehicle into an earth-centered earth-fixed (ECEF) coordinate value; converting the ECEF coordinate value into an east, north, up (ENU) coordinate value of the relative vehicle in relation to the self vehicle; converting the ENU coordinate value of the relative vehicle into a coordinate value based on the heading direction of the self vehicle in relation to the self vehicle; and calculating longitudinal and lateral distances from the self vehicle to the relative vehicle in relation to the heading direction of the self vehicle from the converted coordinate values.

3. The method according to claim 1, wherein the step of classifying of the target position of the relative vehicle using the path history data depending on the calculated longitudinal distance includes: when the calculated longitudinal distance is a positive number, determining that the relative vehicle is positioned at the front of the self vehicle and classifying the target position of the relative vehicle using the path history data of the relative vehicle; and when the calculated longitudinal distance is a negative number, determining that the relative vehicle is positioned at the rear of the self vehicle and classifying the target position of the relative vehicle using the path history data of the self vehicle.

4. The method according to claim 3, wherein when the calculated longitudinal distance is a positive number, the step of determining that the relative vehicle is positioned at the front of the self vehicle and classifying the target position of the relative vehicle using the path history data of the relative vehicle includes: calculating a straight distance (a) from a position of the self vehicle to a first path using the path history data of the relative vehicle; comparing the straight distance (a) from the position of the self vehicle to the first path with a half () value of a length of a lane width; when the straight distance (a) from the position of the self vehicle to the first path is less than the half value of the length of the lane width, calculating a position (a) of a point projected to the first path or an extension line of the first path from the position of the self vehicle; determining whether or not the position (A) of the point exists on the first path; when the position (A) of the point exists on the first path, comparing a heading value of the self vehicle with a gradient of the first path; and comparing a difference value between the heading value of the self vehicle and the gradient of the first path with a set angle, and ascertaining whether or not the position of the self vehicle is positioned at the left or right in relation to the first path when the difference value between the heading value of the self vehicle and the gradient of the first path is less than the set angle.

5. The method according to claim 4, further comprising: when the position (A) of the point does not exist on the first path, determining whether or not the position (A) of the point is positioned on a second path or a third path; and determining whether or not the self vehicle exists in a region between a path (M) perpendicular to the first path and a path (N) perpendicular to the second path, and projecting a coordinate of the self vehicle to a path history point of the relative vehicle and calculating a projected distance when the self vehicle exists in the region between the path (M) perpendicular to the first path and the path (N) perpendicular to the second path.

6. The method according to claim 4, further comprising: when the self vehicle exists in the region between the path (M) perpendicular to the first path and the path (N) perpendicular to the second path, calculating gradients of the path (M) perpendicular to the first path and the path (N) perpendicular to the second path, and calculating a gradient of a distance (c) connecting the path history point on a path of the relative vehicle and the coordinate of the self vehicle; determining whether or not the gradient of the distance (c) is a value between the gradients of the path (M) perpendicular to the first path and the path (N) perpendicular to the second path; comparing the distance (c) with the half value of the length of the lane width; and when the distance (c) is less than the half value of the length of the lane width, comparing the heading value of the self vehicle and the gradients of the first path and the second path.

7. The method according to claim 3, wherein when the calculated longitudinal distance is a negative number, the step of determining that the relative vehicle is positioned at the rear of the self vehicle and classifying the target position of the relative vehicle using the path history data of the self vehicle includes: calculating a distance (a) from a position of the relative vehicle to a first path using the path history data of the self vehicle; comparing the distance (a) from the position of the relative vehicle to the first path with a half () value of a length of a lane width; when the distance (a) from the position of the relative vehicle to the first path is less than the half value of the length of the lane width, calculating a position (a) of a point projected to an extension line of the first path from the position of the relative vehicle; determining whether or not the position (A) of the point exists on the first path; when the position (A) of the point exists on the first path, comparing a heading value of the relative vehicle with a gradient of the first path; and comparing a difference value between the heading value of the relative vehicle and the gradient of the first path with a set angle, and ascertaining whether or not the position of the relative vehicle is positioned at the left or right in relation to the first path when the difference value between the heading value of the relative vehicle and the first path is less than the set angle.

8. The method according to claim 7, further comprising: when the position (A) of the point does not exist on the first path, determining whether or not the position (A) of the point is positioned on a second path or a third path; and determining whether or not the relative vehicle exists in a region between a path (M) perpendicular to the first path and a path (N) perpendicular to the second path, and projecting a coordinate of the relative vehicle to a path history point of the self vehicle and calculating a projected distance when the relative vehicle exists in the region between the path (M) perpendicular to the first path and the path (N) perpendicular to the second path.

9. The method according to claim 8, further comprising: when the relative vehicle exists in the region between the path (M) perpendicular to the first path and the path (N) perpendicular to the second path, calculating gradients of the path (M) perpendicular to the first path and the path (N) perpendicular to the second path, and calculating a gradient of a distance (c) connecting the path history point on a path of the self vehicle and the coordinate of the self vehicle; determining whether or not the gradient of the distance (c) is a value between the gradients of the path (M) perpendicular to the first path and the path (N) perpendicular to the second path; comparing the distance (c) with the half value of the length of the lane width; and when the distance (c) is less than the half value of the length of the lane width, comparing the heading value of the relative vehicle and the gradients of the first path and the second path.


Apparatus for use in a vehicle equipped with a vehicle-to-vehicle communication system. A remote keyless entry fob is provided for remote control of vehicle access. The fob includes a receiver for receiving a message broadcast by the vehicle-to-vehicle communication system and a memory for storing at least some elements of the message.

Claims which contain your search:

1. A vehicle safety system comprising: a vehicle-based vehicle-to-vehicle ( V2V ) system adapted to transmit and receive wireless V2V communication signals; a vehicle-based remote keyless entry (RKE) system adapted to transmit and/or receive wireless RKE signals; and a fob adapted to transmit wireless RKE signals to the vehicle-based RKE system and/or receive wireless RKE signals from the vehicle-based RKE system, wherein the fob is further adapted to receive wireless signals from the vehicle-based V2V communication system.

2. The vehicle safety system recited in claim 1, wherein the fob comprises: at least one of an RKE transmitter, an RKE receiver, and an RKE transceiver for communicating with the vehicle-based RKE system; and at least one of a V2V transmitter, a V2V receiver, and a V2V transceiver for communicating with the vehicle-based V2V communication system.

3. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system comprises at least one of a V2V transmitter, a V2V receiver, and a V2V transceiver for communicating with V2V communication systems of other vehicles within a predetermined vicinity of the V2V communication system.

4. The vehicle safety system recited in claim 1, wherein the fob comprises at least one of a transmitter, a receiver, and a transceiver adapted to communicate with both the vehicle-based V2V communication system and the vehicle-based RKE system.

5. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system and the vehicle-based RKE system are adapted to communicate with the fob via a shared communication frequency.

6. The vehicle safety system recited in claim 5, wherein the shared communication frequency is a frequency within or above the high frequency radio frequency spectrum.

7. The vehicle safety system recited in claim 5, wherein the shared communication frequency is a 5.8 GHz frequency.

8. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system collects information comprising at least one of GPS information related to the location of the vehicle and vehicle condition information related to the condition of the vehicle.

9. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system is adapted to broadcast the wireless V2V communication signals to vehicles within a predetermined vicinity.

10. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system is further adapted to receive V2V communication signals from other vehicles within a predetermined vicinity and provide the recorded messages to onboard vehicle systems and subsystems for display or responsive action.

11. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system is adapted to operate while the vehicle is operating, the V2V communication system being adapted to notify nearby vehicles of safety data comprising at least one of velocity, direction, location, linear acceleration, and rotational acceleration.

12. The vehicle safety system recited in claim 1, wherein the vehicle-based V2V communication system is adapted to remain powered and active for a predetermined period of time after the vehicle ignition is switched off in order to broadcast one or more final V2V communication signals.

13. The vehicle safety system recited in claim 13, wherein the final V2V communication signals comprise at least one of vehicle stationary status information, location information, and vehicle safety information.

14. The vehicle safety system recited in claim 1, wherein the fob is adapted to store at least a portion of the information received in the final V2V communication signals in memory.

15. The vehicle safety system recited in claim 15, wherein the fob is adapted to receive and store only the information in the one or more final V2V communication signals.

16. The vehicle safety system recited in claim 1, wherein the fob is adapted to receive and verify a vehicle ID portion of the V2V communication signal to verify that the signal is from the vehicle associated with the fob.

17. The vehicle safety system recited in claim 17, wherein the fob is adapted to ignore V2V communication signals from other vehicles based on the vehicle ID portion.

18. The vehicle safety system recited in claim 1, wherein the fob is adapted to store the information received in the V2V communication signal in the memory within the fob.

19. The vehicle safety system recited in claim 1, wherein the fob is adapted to permit a user to access the vehicle location information and other V2V communications signal elements including information regarding vehicle malfunctions associated with vehicle safety.

20. The vehicle safety system recited in claim 1, wherein the fob is adapted to provide selected elements of the V2V communication signal to the owner via an indicator comprising at least one of a display on the fob, a cell phone, a tablet computer, a personal or notebook computer, a television via at least one of a near field communication link, a low-power RF communication protocol, and a USB connection.

21. The vehicle safety system recited in claim 1, wherein the fob is adapted to utilize GPS location information from the V2V communication signal stored on the fob to determine the location of the vehicle relative to the fob.

22. The vehicle safety system recited in claim 1, wherein the fob comprises an embedded GPS receiver and is adapted to compare current GPS location of the fob with stored GPS location of the vehicle to determine the location of the vehicle relative to the fob.

23. The vehicle safety system recited in claim 1, wherein the fob is adapted to cooperate with an external device having GPS capabilities to determine the location of the vehicle relative to the fob.

24. The vehicle safety system recited in claim 1, wherein the fob and the V2V communication system are adapted to communicate on the same frequency, the fob being adapted to obtain safety information and location information from the V2V communication system and provide the safety and location information to an external system for at least one of vehicle diagnosis, vehicle locating, and vehicle information recordation and/or display.

25. The vehicle safety system recited in claim 1, wherein the fob is adapted to periodically ping the V2V communication system for information related to vehicle security systems, comprising glass breakage information, door lock information, vehicle ignition information, vehicle impact information, and vehicle security system information.


Grant
Agency: European Commission | Branch: H2020 | Program: SME-2 | Phase: IT-1-2014 | Award Amount: 1.92M | Year: 2015

Demand for data in cars has grown at a rapid rate. Connected cars now want to communicate between the different areas of the car to understand the status of the car, the environment around it and then communicate this information to the driver. Many Advanced Driver Assisted System applications wish to make use of this data to support the driver to drive safely and to save lives. However, current in-car data communications networks cannot supply this day in a fast, reliable way so that it can be used. The physical environment of the car is challenging, with vibrations, heat and Electro Magnetic interference all meaning that traditional communications networks are unsuitable. They are also not capable of reaching above speeds of 150Mbps, meaning all information is too slow to be useful. KDPOF has developed and patented a breakthrough low-cost technology which allows data transmission at rates of up to 1Gbps. Furthermore, as this technology uses Plastic Optical Fiber, it overcomes all the challenges of the in-car environment. KDPOF have recently launched this product for the consumer and professional markets. The CarNet project aims to support KDPOF to adjust, test and demonstrate the benefits of KDPOFs Giga technology to the Automotive market. As this market is complex, with a long product development process, the CarNet project will also look to understand fully the business strategy to ensure that the products commercial potential is maximized and to ensure that KDPOF is at the forefront of developing the standards that will shape the future in-car data communications market. As a result of this project, KDPOF will grow considerably, doubling their employees by five years after the project and earning a return on investment of over 80%. It will also reduce the costs of in-car data communication networks and improve the competitiveness of the European Automobile sector in general, and the in-car data and ADAS sector in particular.


An apparatus and method of providing portable and personalized infotainment via an in-vehicle system of a vehicle from an infotainment content provider is provided. The method includes registering at least one mobile device with the in-vehicle system of the vehicle upon the at least one mobile device entering a defined location about the vehicle, receiving infotainment content at the at least one registered mobile device via the in-vehicle system of the vehicle while the at least one registered mobile device is within the defined location about the vehicle, and receiving the infotainment content at the at least one registered mobile device via another network upon the at least one mobile device leaving the defined location about the vehicle.

Claims which contain your search:

1. A method of providing portable and personalized infotainment via an in-vehicle system of a vehicle from an infotainment content provider, the method comprising: registering at least one mobile device with the in-vehicle system of the vehicle upon the at least one mobile device entering a defined location about the vehicle; receiving infotainment content at the at least one registered mobile device via the local system of the vehicle while the at least one registered mobile device is within the defined location about the vehicle; and receiving the infotainment content at the at least one registered mobile device via another network upon the at least one mobile device leaving the defined location about the vehicle.

2. The method of claim 1, wherein each of the at least one registered mobile devices receives individualized broadcast content via the in-vehicle system of the vehicle.

3. The method of claim 1, wherein each of the at least one registered mobile devices receives a same broadcast content as every other of the at least one registered mobile devices via the in-vehicle system of the vehicle.

4. The method of claim 1, wherein the registering of the at least one registered mobile device with the 1 in-vehicle system of the vehicle further comprises: uniquely identifying the at least one mobile device; and transmitting information uniquely identifying the at least one registered mobile device to the infotainment content provider.

6. The method of claim 5, wherein each of the at least one registered mobile devices provides the monitored received content as a recommendation to another of the at least one registered mobile devices.

9. The method of claim 1, wherein the defined location about the vehicle is determined by at least one of a sensor or a range of an in-vehicle communications device.

10. A system for providing portable and personalized infotainment, the system comprising: an in-vehicle system comprising a processor and sensor, the in-vehicle system configured to determine an entry of at least one of a passenger and a driver of a vehicle and to identify a mobile device of the at least one of the passenger and the driver; and an infotainment server configured to receive information of the mobile device and register the mobile device and to transmit infotainment content to the mobile device, a type of infotainment content transmitted to the mobile device determined based upon whether the user of the mobile device is one of a passenger and a driver of the vehicle, wherein the mobile device receives the infotainment content via the in-vehicle system while the mobile device is within the vehicle, and wherein the mobile device receives the infotainment content via another network when the mobile device is outside of the vehicle.

12. The system of claim 10, wherein the infotainment server is further configured to monitor the received infotainment content of the mobile device.

13. The system of claim 12, wherein the infotainment server is further configured to provide a recommendation to another mobile device based upon the monitored infotainment content of the mobile device.

16. The system of claim 10, wherein, the entry of the at least one passenger into the vehicle is determined by at least one of a sensor or a range of an in-vehicle communications device.

17. The system of claim 16, wherein least one of a sensor is attached to one of a door of the vehicle and a seat of the vehicle.


Patent
Hyundai America Technical Center Inc, Hyundai Motor Company and Kia Motors | Date: 2015-05-15

A method includes: receiving, at a host vehicle, a plurality of messages transmitted using Vehicle-to-Vehicle (V2V) communications indicating a heading angle and a speed of a remote vehicle; calculating an expected change in frequency of the plurality of messages received at the host vehicle based on the heading angle and the speed of the remote vehicle; measuring an actual change in frequency of the plurality of messages received at the host vehicle due to the Doppler effect; comparing the expected change in frequency to the actual change in frequency; and determining that the plurality of messages were not transmitted from the remote vehicle when a difference between the expected change in frequency and the actual change in frequency exceeds a predefined frequency change threshold.

Claims which contain your search:

1. A method comprising: receiving, at a host vehicle, a plurality of messages transmitted using Vehicle-to-Vehicle (V2V) communications indicating a heading angle and a speed of a remote vehicle; calculating an expected change in frequency of the plurality of messages received at the host vehicle based on the heading angle and the speed of the remote vehicle; measuring an actual change in frequency of the plurality of messages received at the host vehicle due to the Doppler effect; comparing the expected change in frequency to the actual change in frequency; and determining that the plurality of messages were not transmitted from the remote vehicle when a difference between the expected change in frequency and the actual change in frequency exceeds a predefined frequency change threshold.

4. The method of claim 1, further comprising: determining a heading angle and a speed of the host vehicle.

5. The method of claim 4, wherein the expected change in frequency is calculated based on the heading angle and the speed of the remote vehicle and the heading angle and the speed of the host vehicle.

6. The method of claim 5, wherein the expected change in frequency is calculated according to the following formula:

7. The method of claim 1, further comprising: reporting that the plurality of messages were not transmitted from the remote vehicle.

8. The method of claim 1, further comprising: determining that the remote vehicle is a virtual vehicle emulated by a remote attacker.

10. A method comprising: receiving, at a host vehicle, a plurality of messages transmitted using Vehicle-to-Vehicle (V2V) communications indicating a heading angle and a speed of a remote vehicle; calculating an expected angular offset of the plurality of messages received at the host vehicle based on the heading angle of the remote vehicle; measuring an actual angular offset of the plurality of messages received at the host vehicle; comparing the expected angular offset to the actual angular offset; and determining that the plurality of messages were not transmitted from the remote vehicle when a difference between the expected angular offset and the actual angular offset exceeds a predefined angular offset threshold.

13. The method of claim 10, further comprising: determining a heading angle and a speed of the host vehicle.

14. The method of claim 13, wherein: the expected angular offset is calculated based on the heading angle of the remote vehicle and the heading angle of the host vehicle, and the actual angular offset is measured based on based on a change in frequency of the plurality of messages received at the host vehicle due to the Doppler effect, the speed of the remote vehicle, and the speed of the host vehicle.

15. The method of claim 14, wherein: the expected angular offset is calculated according to the following formula: where _(calculated )is the calculated expected angular offset, H_(RV )is the heading angle of the remote vehicle, and H_(HV )is the heading angle of the host vehicle, and the actual angular offset is measured according to the following formula:

16. The method of claim 10, further comprising: reporting that the plurality of messages were not transmitted from the remote vehicle.

17. The method of claim 10, further comprising: determining that the remote vehicle is a virtual vehicle emulated by a remote attacker.

19. A non-transitory computer readable medium containing program instructions for performing a method, the computer readable medium comprising: program instructions that receive, at a host vehicle, a plurality of messages transmitted using Vehicle-to-Vehicle (V2V) communications indicating a heading angle and a speed of the remote vehicle; program instructions that calculate an expected change in frequency of the plurality of messages received at the host vehicle based on the heading angle and the speed of the remote vehicle; program instructions that measure an actual change in frequency of the plurality of messages received at the host vehicle due to the Doppler effect; program instructions that compare the expected change in frequency to the actual change in frequency; and program instructions that determine that the plurality of messages were not transmitted from the remote vehicle when a difference between the expected change in frequency and the actual change in frequency exceeds a predefined frequency change threshold.

20. A non-transitory computer readable medium containing program instructions for performing a method, the computer readable medium comprising: program instructions that receive, at a host vehicle, a plurality of messages transmitted using Vehicle-to-Vehicle (V2V) communications indicating a heading angle and a speed of the remote vehicle; program instructions that calculate an expected angular offset of the plurality of messages received at the host vehicle based on the heading angle of the remote vehicle; program instructions that measure an actual angular offset of the plurality of messages received at the host vehicle; program instructions that compare the expected angular offset to the actual angular offset; and program instructions that determine that the plurality of messages were not transmitted from the remote vehicle when a difference between the expected angular offset and the actual angular offset exceeds a predefined angular offset threshold.