Automated vehicle communications system

• US 10,036,642 B2
• Filed: 12/08/2015
• Issued: 07/31/2018
• Est. Priority Date: 12/08/2015
• Status: Active Grant

• Current Assignee: Aurora Operations Incorporated (Aurora Innovation, Inc.)
• Original Assignee: Uber Technologies, Inc.
• Inventors: Ross, William, Aitken, Michael
• Primary Examiner(s): Berona, Kimberly S
• Assistant Examiner(s): Whalen, Michael F
• Application Number:
  US14/963,007
• Publication Number:
  US 20170162057A1
• Time in Patent Office: 966 Days
• 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 30/18 Propelling the vehicle
• CPC Class Codes: G01C 21/3438 Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
• CPC Class Codes: G01S 13/89 for mapping or imaging
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching
• CPC Class Codes: H01Q 1/3216 where the road or rail vehicle is only used as transportation means
• CPC Class Codes: H01Q 1/364 using a particular conducting material, e.g. superconductor
• CPC Class Codes: H01Q 3/01 varying the shape of the antenna or antenna system
• CPC Class Codes: H04B 7/04 using two or more spaced independent antennas
• CPC Class Codes: H04B 7/0617 for beam forming
• CPC Class Codes: H04W 16/28 using beam steering
• CPC Class Codes: H04W 4/24 Accounting or billing
• CPC Class Codes: H04W 48/06 based on traffic conditions
• CPC Class Codes: H04W 48/18 Selecting a network or a communication service
• CPC Class Codes: H04W 64/003 locating network equipment

Abstract

An automated vehicle (AV) can be managed by a backend system and include an acceleration, braking, and steering system, an AV control system to maneuver the AV through road traffic throughout a given region, a memory to store a network resource map indicating locations of base stations and available network types providing coverage from the base stations throughout the given region, a communications array to transmit and receive communications from the backend system, and a communications system. The communications system can utilize the network resource map to dynamically select optimal network types from proximate base stations to communicate data with the backend system, and dynamically configure the communications array to connect with the optimal network types to transmit and receive data with the backend system.

Claims

1. An autonomous vehicle (AV) managed by a backend system, the AV comprising:

an acceleration, braking, and steering system;

a memory to store a spectrum heat map indicating locations of base stations, available network types providing coverage from the base stations, and network quality data of each of the available network types throughout a given region;

a communications array to transmit and receive communications from the backend system; and

an AV control system to;

operate the acceleration, braking, and steering system of the AV to maneuver the AV through road traffic within the given region;

perform a localization operation to determine a location and an orientation of the AV relative to proximate base stations within the given region;

receive, from the backend system, update data to update at least the network quality data in the spectrum heat map;

based on the location and the orientation of the AV relative to the proximate base stations, utilize the updated spectrum heat map, to dynamically select optimal network types from the proximate base stations to connect with the backend system; and

dynamically configure the communications array to connect with the optimal network types to transmit and receive the communications with the backend system.

2. The AV of claim 1, wherein the update data for the spectrum heat map comprises updated cost data associated with transmitting data using each of the available network types for each of the base stations, and wherein the AV control system dynamically selects the optimal network types based on the updated cost data.

3. The AV of claim 2, wherein the update data further comprises updated network latency data for each of the available network types, and wherein the AV control system further dynamically selects the optimal network types based on the updated network latency data.

4. The AV of claim 1, wherein the optimal network types comprise a plurality of a 3G, a 4G, a long-term evolution (LTE), a WiFi, a WiMax, a 900 MHz unlicensed, a dedicated short-range communication (DSRC), or a WiGig network type.

5. The AV of claim 1, wherein the AV control system is further configured to:

receive a transport command from the backend system to travel to a destination; and

forward the transport command to the AV control system.

6. The AV of claim 1, wherein the communications array comprises a phased array, and wherein the AV control system dynamically configures the phased array to connect with the optimal network types by dynamically beam steering a radiation pattern of the phased array towards the proximate base stations.

7. The AV of claim 1, wherein the communications array comprises a liquid metal tunable antenna, and wherein the AV control system dynamically configures the liquid metal tunable antenna to connect with the optimal network types by dynamically beam steering a radiation pattern of the liquid metal tunable antenna to towards the proximate base stations.

8. The AV of claim 1, wherein the memory further includes LiDAR sub-maps for the given region that provide ground-based, three-dimensional (3D) environment data along various routes throughout the given region.

9. The AV of claim 8, further comprising:

a sensor array to continuously collect sensor data representing an operational environment of the AV;

an on-board data processing system to process the sensor data by (i) dynamically comparing the sensor data to the LiDAR sub-maps as the AV travels throughout the given region, and (ii) based on dynamically comparing the sensor data to the LiDAR sub-maps, dynamically perform a localization of the AV within the given region; and

wherein the AV control system utilizes the processed sensor data to operate the acceleration, braking, and steering system of the AV in order to maneuver the AV through road traffic in the given region.

10. The AV of claim 9, wherein the AV control system is further configured to:

receive a transport command from the backend system to maneuver the AV to a destination; and

utilize the processed sensor data to operate the acceleration, braking, and steering system in order to maneuver the AV to the destination.

11. The AV of claim 9, wherein the AV control system is further configured to:

utilize a current location and a current orientation of the AV to dynamically perform ray tracing operations to identify the proximate base stations.

12. The AV of claim 1, wherein the backend system manages routing of a fleet of AVs, the fleet of AVs including the AV, and wherein the fleet of AVs transmit localized update data to the backend system to enable the backend system to update the spectrum heat map.

13. The AV of claim 12, wherein the localized update data comprises at least one of average bandwidth data, average latency data, average packet loss data, or network jitter data.

14. An autonomous vehicle (AV) comprising:

a sensor array to continuously collect sensor data representing an operational environment of the AV;

a communications system operable to communicate with other AVs and a backend system using a plurality of communication protocols;

an on-board data processing system to process the sensor data; and

an AV control system to;

perform a localization operation to determine a location and an orientation of the AV relative to proximate base stations;

while operating the AV along a current route, receive network configuration commands from the backend system to configure the AV control system to connect with a plurality of active networks, the network configuration commands being based on a spectrum heat map and the location and the orientation of the AV relative to the proximate base stations;

in response to the network configuration commands along the current route, configure the AV control system to connect with the plurality of active networks;

identify network latency data and cost data for each of the plurality of active networks, the cost data indicating a connection and transmission cost; and

transmit the network latency data and the cost data to the backend system to enable the backend system to update the spectrum heat map.

15. The AV of claim 14, wherein the AV control system is further configured to:

receive a transport command from the backend system to facilitate a pick-up request to transport a requesting user to a specified destination;

maneuver the AV through road traffic using the processed sensor data to pick up the requesting user; and

receive route data from the backend system indicating the current route to the specified destination.

16. The AV of claim 14, wherein the AV control system includes a phased array, and wherein the communication system configures the phased array to connect with the plurality of active networks by dynamically beam steering a radiation pattern of the phased array towards one or more base stations that provide the plurality of active networks.

17. The AV of claim 14, wherein the plurality of active networks comprise a plurality of a 3G, a 4G, a long-term evolution (LTE), a WiFi, a WiMax, a 900 MHz unlicensed, a dedicated short-range communication (DSRC), or a WiGig network.

18. The AV of claim 14, wherein the determined location and orientation of the AV relative to the proximate base stations is based on sensor data to LiDAR sub-maps for a given region, the LiDAR sub-maps provide ground-based, three-dimensional (3D) environment data along various routes throughout the given region.

19. An AV control system for an autonomous vehicle (AV), the AV control system comprising:

a communications array to transmit and receive communications from a backend system;

a memory to store a spectrum heat map indicating locations of base stations, available network types providing coverage from the base stations, and a network quality data of each of the available network types throughout a given region; and

one or more processors to;

perform localization operation to determine a location and an orientation of the AV relative to proximate base stations;

receive, from the backend system, update data to update at least the network quality data in the spectrum heat map;

based on the location and the orientation of the AV relative to the proximate base stations, utilize the updated spectrum heat map, dynamically select optimal network types from the proximate base stations to transmit and receive the communications with the backend system; and

dynamically configure the communications array to connect with the optimal network types to transmit and receive the communications with the backend system.

20. The AV control system of claim 19, wherein the update data comprises updated cost data associated with transmitting data using each of the available network types for each of the base stations, and wherein the AV control system dynamically selects the optimal network types based on the updated cost data.