IP Library Granted Patent US 11,333,519
Granted Patent B2
US 11,333,519 · App. 16/662,994 · Granted May 17, 2022

Dynamic map generation with focus on construction and localization field of technology

Inventors: Stephen G. McGill (Cambridge, MA); Guy Rosman (Newton, MA); Luke S. Fletcher (Cambridge, MA)
Assignee: TOYOTA RESEARCH INSTITUTE, INC.
G01C21/3614G01C21/3415G01C21/3461G05D1/0088G06F16/29G05D2201/0213
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,333,519
App. No.
16/662,994
Granted
May 17, 2022
Kind
B2
Abstract

Systems and methods for generating efficient planning routes for vehicles, including autonomous and semi-autonomous vehicles are presented. A route planner may generate dynamic maps and routes that reduces the uncertainty of road-agent environmental and behavioral data in an efficient manner. Route planning may be accomplished using a statistical approach in which known data from one geographic or behavioral feature set may be used and relied upon by a vehicle in another geographical and behavioral context to estimate the environmental and behavioral data relevant to the vehicles current operation.

Claims (30)

1. A method for planning a route for a vehicle, the method comprising:

generating a first map based upon a first dataset of features in a database, wherein the first map is a heat map representative of an uncertainty level of the first dataset of features, the database comprising a plurality of datasets of features;

generating a first route based on the first map;

collecting vehicle operational data as a second dataset of features;

comparing the second dataset of features to the plurality of datasets of features in the database; and

updating the first map to a second map based on the similarity of the second dataset of features to a third dataset of features in the database.

2. The method of claim 1 wherein the plurality of datasets of features comprise environmental data features.

3. The method of claim 2 wherein the environmental data features are associated with a geographic area.

4. The method of claim 1 wherein the plurality of datasets of features comprise road agent behavioral data.

5. The method of claim 1 wherein the vehicle operational data comprises environmental data.

6. The method of claim 1 further comprising updating the first route to a second route based on the second map.

7. The method of claim 1 further comprising collecting the vehicle operational data until a threshold is met, wherein the step of updating of the first map to the second map is executed upon the collected vehicle operational data exceeding the threshold.

8. The method of claim 1 further comprising collecting the vehicle operational data until an uncertainty threshold is met, wherein the step of updating of the first map to the second map is executed upon the collected vehicle operational data exceeding the uncertainty threshold.

9. The method of claim 8 further comprising updating the first route to a second route based on the uncertainty level of second dataset of features.

10. A system for generating a vehicle route, the system comprising:

a database comprising a plurality of datasets of features;

a map generator processor generating a first map based upon a first dataset of features in the database, wherein the first map is a heat map representative of an uncertainty level of the first feature dataset;

a planning module generating a first route based on the first map, the planning module comprising one or more processors, and

at least one sensor configured to collect vehicle operational data as a second dataset of features;

the map generator processor configured to:

compare the second dataset of features to the plurality of datasets of features in the database; and

update the first map to a second map based on the similarity of the second dataset of features to a third dataset of features in the database.

11. The system of claim 10 , wherein the system comprises an autonomous vehicle.

12. The system of claim 10 wherein the plurality of datasets of features comprise environmental data features.

13. The system of claim 12 wherein the environmental data features are associated with at least one of a geographic area, time-of-day, and weather.

14. The system of claim 10 wherein the plurality of datasets of features comprise road agent behavioral data.

15. The system of claim 10 wherein the vehicle operational data comprises environmental data.

16. The system of claim 10 wherein the processor is further configured to update the first route to a second route based on the second map.

17. The system of claim 10 wherein the at least one sensor is configured to collect the vehicle operational data until a threshold is met, wherein the step of updating of the first map to the second map is executed upon the collected vehicle operational data exceeding the threshold.

18. The system of claim 10 wherein the at least one sensor is configured to collect the vehicle operational data until an uncertainty threshold is met, wherein the step of updating of the first map to the second map is executed upon the collected vehicle operational data exceeding the uncertainty threshold.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 7, 2022
From: TOYOTA RESEARCH INSTITUTE, INC.
To: TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 060127/0888 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 28, 2019
From: MCGILL, STEPHEN G.; ROSMAN, GUY; FLETCHER, LUKE S.
To: TOYOTA RESEARCH INSTITUTE, INC.
Reel/Frame 050846/0254 →
Continuity (1)
Related Publication 20210123764A1 · Apr 29, 2021
Cited By (1)
US 12,695,967