Systems and methods for computer-assisted shuttles, buses, robo-taxis, ride-sharing and on-demand vehicles with situational awareness

Patent metadata

Field	Value
Publication number	US-11874663-B2
Application number	US-202217896825-A
Country	US
Kind code	B2
Filing date	Aug 26, 2022
Priority date	Feb 26, 2018
Publication date	Jan 16, 2024
Grant date	Jan 16, 2024

Abstract

A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.

First claim

The invention claimed is:

1. A vehicle comprising:
a propulsion system delivering power to propel the vehicle;
a passenger space to accommodate at least one passenger;
one or more first sensors to monitor at least a portion of an environment outside the vehicle;
one or more second sensors to monitor at least a portion of the passenger space; and
a controller operatively coupled to the one or more first sensors, the one or more second sensors, and the propulsion system, the controller including at least one graphics processing unit (GPU) and at least one deep learning accelerator, the controller to, without intervention by a human driver, is configured:
identify a passenger to ride in the vehicle;
control the vehicle to take on the identified passenger;
navigate the vehicle including planning a route to a destination; and
control the vehicle to arrange for the identified passenger to leave the passenger space at the destination,

wherein the controller provides massively parallel processing and the vehicle achieves an ISO 26262 level 4 or higher certification.

2. The vehicle of claim 1 , wherein the passenger is identified based at least on the controller processing data generated using the one or more first sensors to recognize at least one of a gesture or a pose of the passenger that indicates that an intent of the passenger is to use the vehicle.

3. The vehicle of claim 1 , wherein the identifying is based on the passenger operating a mobile user device.

4. The vehicle of claim 1 , wherein the controller is further to receive the destination specified by the passenger or another passenger, and plan a route to the specified destination.

5. The vehicle of claim 4 , wherein the controller is further to use artificial intelligence to dynamically plan the route and navigate to the specified destination.

6. The vehicle of claim 1 , wherein the one or more first sensors include one or more LIDAR sensors, and the controller is configured further to dynamically map at least a portion of the environment around the vehicle using the one or more LIDAR sensors.

7. The vehicle of claim 1 , further including a signaling device associated with the vehicle, the signaling device to signal an indication of an intention to pick up the passenger.

8. The vehicle of claim 1 , further including a passenger information display disposed in the passenger compartment, the passenger information display to display one or more visualizations corresponding to one or more operations of the vehicle.

9. The vehicle of claim 1 , wherein at least a subset of the one or more second sensors are to simultaneously sense concurrent activities of multiple passengers within the passenger space.

10. A system comprising:
a passenger space that can accommodate at least one passenger;
one or more first sensors to monitor at least a portion of an environment outside a vehicle;
one or more second sensors to monitor at least a portion of the passenger space; and
a controller including at least one graphics processing unit (GPU) and at least one deep learning accelerator, the controller to, without intervention by a human driver, perform operations comprising:
identifying a passenger;
controlling the vehicle to an origin location to onboard the identified passenger;
navigating the vehicle to a destination location; and
controlling the vehicle to a drop off location at the destination location to offload the passenger,

wherein the system provides massively parallel processing and achieves an ISO 26262 level 4 or higher certification.

11. The system of claim 10 , wherein the identifying includes using the one or more first sensors and artificial intelligence to recognize at least one of a gesture or a pose of a prospective passenger.

12. The system of claim 10 , wherein the identifying is based on the passenger operating a mobile user device.

13. The system of claim 10 , wherein the operations further comprise the passenger specifying the destination location, and the controller planning a route to the destination location.

14. The system of claim 13 , further comprising using artificial intelligence to dynamically plan the route and navigate to the specified destination.

15. The system of claim 10 , wherein the one or more first sensors include one or more LIDAR sensors, and the operations further include dynamically mapping at least a portion of the environment around the vehicle using the one or more LIDAR sensors.

16. The system of claim 10 , further including signaling, with a signaling device associated with the vehicle, an indication of
an intention to onboard the passenger.

17. The system of claim 10 , wherein the system further includes a passenger information display disposed in the passenger compartment, and the operations further include displaying an indication of one or more operations of the vehicle to the passenger on the display.

18. The system of claim 10 , wherein the operations further comprise simultaneously sensing concurrent activities of multiple passengers within at least a portion of the passenger space.

19. A system comprising:
one or more processors, including one or more graphics processing units (GPUs) that are used to perform massively parallel processing, the processors configured to perform operations comprising:
identifying a passenger using one or more external facing sensors of a vehicle;
controlling the vehicle to a pickup location to onboard the passenger;
navigating the vehicle to a destination location;
monitoring the passenger during at least a portion of the navigating using one or more internal facing sensors; and
controlling the vehicle to a drop off location at the destination location to drop off the passenger.

20. The system of claim 19 , wherein the system achieves an ISO 26262 level 4 or higher certification.

Assignees

• Nvidia Corp

Inventors

• Hicok Gary
• Cox Michael
• Sainz Miguel
• Hempel Martin
• Kumar Ratin
• Roman Timo
• Grigor Gordon
• Nister David
• Ebert Justin
• Shih Chin-Hsien
• Tam Tony
• Bhargava Ruchi

Classifications

• B60Q1/543

  for indicating other states or conditions of the vehicle (indicating taxis' state of hire or fare G07B13/045) · CPC title

• B60Q1/547

  for issuing requests to other traffic participants; for confirming to other traffic participants they can proceed, e.g. they can overtake · CPC title

• B60Q1/507

  specific to autonomous vehicles · CPC title

• G01C21/3617

  using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement · CPC title

• G01C21/3438

  Rendezvous; Ride sharing · CPC title