IP Library › Granted Patent US 12,204,332
Granted Patent B2
US 12,204,332 · App. 17/839,640 · Granted Jan 21, 2025

Method for performing a vehicle assist operation

Inventors: Vijaysai Patnaik (San Francisco, CA); William Grossman (East Palo Alto, CA)
Assignee: Waymo LLC
G05D1/0088B60W30/06G05D1/0214G05D1/0231G05D1/0295G05D1/249G05D1/617G05D1/695G05D1/81G06V20/584G08G1/096725G08G1/096791B60W2554/00G08G1/22
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Quick Facts
Patent No.
US 12,204,332
App. No.
17/839,640
Granted
Jan 21, 2025
Kind
B2
Abstract

The technology relates to assisting large self-driving vehicles, such as cargo vehicles, as they maneuver towards and/or park at a destination facility. This may include a given vehicle transitioning between different autonomous driving modes. Such a vehicles may be permitted to drive in a fully autonomous mode on certain roadways for the majority of a trip, but may need to change to a partially autonomous mode on other roadways or when entering or leaving a destination facility such as a warehouse, depot or service center. Large vehicles such as cargo truck may have limited room to maneuver in and park at the destination, which may also prevent operation in a fully autonomous mode. Here, information from the destination facility and/or a remote assistance service can be employed to aid in real-time semi-autonomous maneuvering.

Claims (42)

1. A method of performing a vehicle assist operation for an autonomous cargo vehicle, the method comprising:

receiving at one or more computing devices of the autonomous cargo vehicle, map information usable to navigate the autonomous cargo vehicle;

receiving, by the one or more computing devices of the autonomous cargo vehicle, sensor information from a perception system of the autonomous cargo vehicle;

generating, by the one or more computing devices of the autonomous cargo vehicle, an initial trajectory to a parking location of a parking facility using the map information and the sensor information;

applying, by the one or more computing devices of the autonomous cargo vehicle, a modified trajectory to the parking location of the parking facility based on real time sensor data from one or more sensors of the parking facility; and

using the modified trajectory to enable a driving system of the autonomous cargo vehicle to drive to the parking location in an autonomous driving mode.

2. The method of claim 1 , further comprising providing the modified trajectory to the driving system to enable the driving system to drive to the parking location in the autonomous driving mode.

3. The method of claim 1 , wherein:

the modified trajectory to the parking location is further based on a roadgraph of the parking facility, the roadgraph including a set of paths for backing the autonomous cargo vehicle into the parking location.

4. The method of claim 1 , further comprising:

detecting an obstruction at the parking facility between the autonomous cargo vehicle and the parking location; and

modifying either the initial trajectory or the modified trajectory to avoid the obstruction.

5. The method of claim 1 , wherein the parking location is assigned to the autonomous cargo vehicle by the parking facility.

6. The method of claim 5 , wherein the parking location is assigned based on an ambient temperature at the parking facility.

7. The method of claim 5 , wherein the parking location is assigned based on whether the parking location is locating in direct sunlight or in shade.

8. The method of claim 5 , wherein assignment of the parking location is based on an evaluation of at least one of a time of day, position of the parking location relative to an entrance or exit of the parking facility, a speed limit at the parking facility, or a vehicle type.

9. The method of claim 1 , wherein the parking location is selected by the autonomous cargo vehicle based on at least one of an availability of parking spaces, a size of a maneuvering area at the parking facility, a size of the vehicle, sensor visibility of the perception system of the autonomous cargo vehicle, or a detailed map of the parking facility.

10. The method of claim 1 , wherein the modified trajectory is further based on a perception analysis on the real time sensor data to detect one or more objects in an apron space of the parking facility.

11. The method of claim 10 , wherein the perception analysis includes categorizing the detected one or more objects.

12. The method of claim 11 , the method further comprising instructing the driving system of the autonomous cargo vehicle to take a corrective action in response to categorization of at least one of the detected one or more objects.

13. A system configured to perform a vehicle assist operation for an autonomous cargo vehicle, the system comprising:

one or more computing devices of the autonomous cargo vehicle including a memory configured to store map information usable to navigate the autonomous cargo vehicle, the one or more computing devices of the autonomous cargo vehicle being configured to,

receive the map information usable to navigate the vehicle;

receive sensor information from a perception system of the autonomous cargo vehicle;

generate an initial trajectory to a parking location of a parking facility using the map information and the sensor information;

apply a modified trajectory to the parking location of the parking facility based on real time sensor data from one or more sensors of the parking facility; and

use the modified trajectory to enable a driving system of the autonomous cargo vehicle to drive to the parking location in an autonomous driving mode.

14. The system of claim 13 , wherein:

the modified trajectory to the parking location is further based on a roadgraph of the parking facility, the roadgraph including a set of paths for backing the autonomous cargo vehicle into the parking location.

15. The system of claim 13 , wherein the one or more computing devices are further configured to:

identify an obstruction at the parking facility between the autonomous cargo vehicle and the parking location; and

modify either the initial trajectory or the modifyied trajectory to avoid the obstruction.

16. The system of claim 13 , wherein the parking location is assigned to the autonomous cargo vehicle by the parking facility based on either:

an ambient temperature at the parking facility; or

whether the parking location is locating in direct sunlight or in shade.

17. The system of claim 13 , wherein the parking location is selected by the autonomous cargo vehicle based on at least one of an availability of parking spaces, a size of a maneuvering area at the parking facility, a size of the vehicle, sensor visibility of the perception system of the autonomous cargo vehicle, or a detailed map of the parking facility.

18. The system of claim 13 , wherein the modified trajectory is further based on a perception analysis on the real time sensor data to detect one or more objects in an apron space of the parking facility.

19. The method of claim 1 , wherein at least one of the initial trajectory and the modified trajectory includes a reversing maneuver to back the autonomous cargo vehicle into the parking location.

20. An autonomous cargo vehicle comprising:

the system of claim 13 ; and

the perception system of the autonomous cargo vehicle, wherein the perception system includes one or more sensors disposed on a cab of the autonomous cargo vehicle.

21. The autonomous cargo vehicle of claim 20 , wherein the one or more sensors are not disposed on a trailer of the autonomous cargo vehicle.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 7, 2022
From: PATNAIK, VIJAYSAI; GROSSMAN, WILLIAM
To: WAYMO LLC
Reel/Frame 060432/0296 →
Continuity (3)
Continuation 16548980 · Aug 23, 2019
Provisional Application 62879571 · Jul 29, 2019
Related Publication 20220308583A1 · Sep 29, 2022
References Cited (68)
US 2879350A · Andrew · 1959 [cited by applicant]
US 4184655A · Anderberg · 1980 [cited by applicant]
US 8963704B2 · Adami · 2015 [cited by applicant]
US 9079587B1 · Rupp et al. · 2015 [cited by applicant]
US 9486921B1 · Straszheim et al. · 2016 [cited by applicant]
US 9581997B1 · Penilla · 2017 [cited by examiner]
US 9582006B2 · Switkes et al. · 2017 [cited by applicant]
US 9720410B2 · Fairfield et al. · 2017 [cited by applicant]
US 9830825B2 · Anstett · 2017 [cited by applicant]
US 10078338B2 · Smartt et al. · 2018 [cited by applicant]
US 10310087B2 · Laddha et al. · 2019 [cited by applicant]
US 10339815B1 · Sin · 2019 [cited by applicant]
US 10948927B1 · Harris et al. · 2021 [cited by applicant]
US 11004344B2 · Bergquist et al. · 2021 [cited by applicant]
US 11010907B1 · Bagwell · 2021 [cited by examiner]
US 11011064B2 · Zhou et al. · 2021 [cited by applicant]
US 20060179671A1 · Ghatak · 2006 [cited by applicant]
US 20070233337A1 · Plishner · 2007 [cited by applicant]
US 20100256852A1 · Mudalige · 2010 [cited by applicant]
US 20150088373A1 · Wilkins · 2015 [cited by applicant]
US 20150203156A1 · Hafner · 2015 [cited by examiner]
US 20150370255A1 · Harvey · 2015 [cited by examiner]
US 20160071418A1 · Oshida et al. · 2016 [cited by applicant]
US 20160223350A1 · Lewis · 2016 [cited by examiner]
US 20160318510A1 · Hess · 2016 [cited by applicant]
US 20170003687A1 · Kojo · 2017 [cited by examiner]
US 20170168503A1 · Amla et al. · 2017 [cited by applicant]
US 20170212511A1 · Paiva Ferreira · 2017 [cited by examiner]
US 20170313306A1 · Nordbruch · 2017 [cited by examiner]
US 20170341516A1 · Brooks et al. · 2017 [cited by applicant]
US 20180113477A1 · Rodriguez et al. · 2018 [cited by applicant]
US 20180137454A1 · Kulkarni · 2018 [cited by examiner]
US 20190019407A1 · Nakhjavani · 2019 [cited by applicant]
US 20190094858A1 · Radosavljevic et al. · 2019 [cited by applicant]
US 20190138024A1 · Liang et al. · 2019 [cited by applicant]
US 20190147320A1 · Mattyus et al. · 2019 [cited by applicant]
US 20190204853A1 · Miller et al. · 2019 [cited by applicant]
US 20190206262A1 · Sin · 2019 [cited by applicant]
US 20190213889A1 · Calleja Alvarez et al. · 2019 [cited by applicant]
US 20190235506A1 · Bardapurkar et al. · 2019 [cited by applicant]
US 20190286921A1 · Liang et al. · 2019 [cited by applicant]
US 20190306680A1 · Doggart et al. · 2019 [cited by applicant]
US 20190310651A1 · Vallespi-Gonzalez et al. · 2019 [cited by applicant]
US 20200001863A1 · Li · 2020 [cited by examiner]
US 20200057453A1 · Laws et al. · 2020 [cited by applicant]
US 20200183383A1 · Stent · 2020 [cited by examiner]
US 20200290482A1 · Jones · 2020 [cited by applicant]
US 20200393847A1 · Govindan et al. · 2020 [cited by applicant]
US 20210163021A1 · Frazzoli et al. · 2021 [cited by applicant]
US 20210323537A1 · Fan · 2021 [cited by examiner]
US 20210398432A1 · Bae et al. · 2021 [cited by applicant]
CN 107850895A · 2018 [cited by applicant]
CN 109941282A · 2019 [cited by applicant]
JP 2019046034A · 2019 [cited by applicant]
KR 101102408B1 · 2012 [cited by applicant]
WO 2004077378A1 · 2004 [cited by applicant]
WO WO2018004542A1 · 2018 [cited by examiner]
WO 2018147041A1 · 2018 [cited by applicant]
City of Waco, Texas, Parking and Access Design Standards for Site Development, From the Waco Development Guide, Revised Jan. 2010, pp. 1-25. [cited by applicant]
Dock Planning Standards, www.novalocks.com, 2013 Nova Technology International, pp. 1-30. [cited by applicant]
Dock System Guide Planning and Designs, www.BlueGiant.com, Jul. 4, 2008, pp. 1-38. [cited by applicant]
International Search Report and Written Opinion for Application No. PCT/US2020/041927 dated Oct. 23, 2020. [cited by applicant]
Mora, et al, Management and Transport Automation in Warehouses Based on Auto-Guided Vehicles, Department of Systems Engineering and Control Technical University of Valencia, Spain, 2006, pp. 1-6. [cited by applicant]
Neuweiler, et al, Autonomous Driving in the Logistics Industry, A multi-perspective view on self-driving trucks, changes in competitive advantages and their implications, Jönköping University, International Business Sch… [cited by applicant]
Peloton Announces its Vision for the Trucking Industry: Drivers Lead, and Technology Follows, https://peloton-tech.com/peloton-announces-its-vision-for-the-trucking-industry-drivers-lead-and-technology-follows/, copyrig… [cited by applicant]
Shankwitz, Long-haul Truck Freight, Transport and the Role of Automation: Collaborative Human-Automated Platooned Trucks Alliance, Western Transportation Institute Montana State University, Apr. 11, 2017, pp. 1-14. [cited by applicant]
Chinese Office Action for Application No. CN20208006795.9 dated Jun. 29, 2023. [cited by applicant]
The Extended European Search Report for European Patent Application No. 20846500.5, May 30, 2023, 9 Pages. [cited by applicant]