IP Library Granted Patent US 12704855
Granted Patent B2
US 12704855 · App. 18/830,146 · Granted Aug 11, 2026

Control systems for autonomous vehicle deployment and vehicle cooling priority

Inventors: Shawn Mcgrady (Holly, MI); Susan A. Dombrowski (Milford, MI); Aaron B. Bloom (Royal Oak, MI)
Assignee: GM GLOBAL TECHNOLOGY OPERATIONS LLC
G05D1/646B60L58/13G05D1/69G06Q10/06393G05D2105/20G05D2109/10
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 12704855
App. No.
18/830,146
Granted
Aug 11, 2026
Kind
B2
Abstract

An example method for automated deployment of autonomous vehicles includes identifying multiple autonomous vehicles available for deployment to execute a requested automated driving route, obtaining vehicle status parameters for each of the multiple autonomous vehicles, wherein the vehicle status parameters include at least a thermal cooling priority status of each vehicle, receiving a target vehicle route associated with an autonomous vehicle service request, determining route parameters associated with the target vehicle route, wherein the route parameters include at least a vehicle thermal load value associated with the target vehicle route, selecting one of the multiple autonomous vehicles according to the route parameters and the thermal cooling priority status of said autonomous vehicle, and deploying the selected one of the multiple autonomous vehicles to execute the target vehicle route using automated driving.

Claims (49)

1 . A method for automated deployment of autonomous vehicles, the method comprising:

identifying, by at least one processor, multiple autonomous vehicles available for deployment to execute a requested automated driving route;

obtaining, by the at least one processor, vehicle status parameters for each of the multiple autonomous vehicles, wherein the vehicle status parameters include at least a thermal cooling priority status of each vehicle;

receiving, by the at least one processor, a target vehicle route associated with an autonomous vehicle service request;

determining, by the at least one processor, route parameters associated with the target vehicle route, wherein the route parameters include at least a vehicle thermal load value associated with the target vehicle route;

selecting, by the at least one processor, one of the multiple autonomous vehicles according to the route parameters and the thermal cooling priority status of said autonomous vehicle, by obtaining a state of charge of a vehicle battery module of the selected one of the multiple autonomous vehicles, comparing the state of charge to a specified state of charge threshold value, and charging the vehicle battery module and delaying deployment of the selected one of the multiple autonomous vehicles in response to the state of charge being less than the specified state of charge threshold value; and

deploying, by the at least one processor, the selected one of the multiple autonomous vehicles to execute the target vehicle route using automated driving.

2 . The method of claim 1 , wherein the automated driving includes automated acceleration control of the selected one of the multiple autonomous vehicles, automated braking control of the selected one of the multiple autonomous vehicles, and automated steering control of the selected one of the multiple autonomous vehicles based on the target vehicle route.

3 . The method of claim 1 , wherein the autonomous vehicle service request includes at least one of an autonomous vehicle ride hail request or an autonomous vehicle package delivery request.

4 . The method of claim 1 , wherein the vehicle status parameters include at least one of a sensed passenger cabin temperature, a sensed passenger cabin humidity, and a state of charge of a vehicle battery module.

5 . The method of claim 1 , wherein the route parameters include at least one of an outside air temperature value, a solar load associated with the target vehicle route, an incline grade along the target vehicle route, a vehicle front end air flow (FEAF) value, and a degree of expected vehicle stops along the target vehicle route.

6 . The method of claim 1 , wherein the specified state of charge threshold value is a twenty-five percent state of charge.

7 . The method of claim 1 , wherein selecting one of the multiple autonomous vehicles includes:

identifying the thermal cooling priority status of the selected one of the multiple autonomous vehicles;

selecting route criteria corresponding to the thermal cooling priority status; and

deploying the selected one of the multiple autonomous vehicles to execute the target vehicle route in response to the route parameters associated with the target vehicle route satisfying the route criteria.

8 . The method of claim 7 , wherein selecting route criteria includes selecting a high front end air flow (FEAF) route criteria in response to the thermal cooling priority status having a medium or high value.

9 . The method of claim 7 , wherein selecting route criteria includes excluding deployment for ride hail route requests in response to the thermal cooling priority status having a high value.

10 . The method of claim 7 , wherein selecting route criteria includes deployment for all route requests in response to the thermal cooling priority status having a low value.

11 . The method of claim 7 , further comprising delaying deployment of the selected one of the multiple autonomous vehicles in response to the route parameters associated with the target vehicle route failing to satisfying the route criteria, and assigning the selected one of multiple autonomous vehicles for further vehicle battery module cooling.

12 . The method of claim 1 , wherein selecting one of the multiple autonomous vehicles includes selecting an autonomous vehicle having a highest battery module state of charge among multiple vehicles having a same thermal cooling priority status.

13 . A method of for automated deployment autonomous vehicles, the method comprising:

identifying, by at least one processor, multiple autonomous vehicles available for deployment to execute a requested automated driving route;

obtaining, by the at least one processor, vehicle status parameters for each of the multiple autonomous vehicles, wherein the vehicle status parameters include at least a thermal cooling priority status of each vehicle;

receiving, by the at least one processor, a target vehicle route associated with an autonomous vehicle service request;

determining, by the at least one processor, route parameters associated with the target vehicle route, wherein the route parameters include at least a vehicle thermal load value associated with the target vehicle route;

selecting, by the at least one processor, one of the multiple autonomous vehicles according to the route parameters and the thermal cooling priority status of said autonomous vehicle;

deploying, by the at least one processor, the selected one of the multiple autonomous vehicles to execute the target vehicle route using automated driving;

obtaining, by the at least one processor, key performance indicator values after completion of the target vehicle route by the selected one of the multiple autonomous vehicles;

receiving, by the at least one processor, feedback input from a rider in the selected one of the multiple autonomous vehicles after completion of the target vehicle route; and

updating, by the at least one processor, an autonomous vehicle deployment selection model based on the key performance indicator values and the feedback input.

14 . The method of claim 13 , wherein selecting one of the multiple autonomous vehicles includes selecting an autonomous vehicle having a highest battery module state of charge among multiple vehicles having a same thermal cooling priority status.

15 . A system for automated deployment of autonomous vehicles, the system including:

memory configured to store computer-executable instructions; and

at least one processor configured to execute the computer-executable instructions to:

identify multiple autonomous vehicles available for deployment to execute a requested automated driving route;

obtain vehicle status parameters for each of the multiple autonomous vehicles, wherein the vehicle status parameters include at least a thermal cooling priority status of each vehicle;

receive a target vehicle route associated with an autonomous vehicle service request;

determine route parameters associated with the target vehicle route, wherein the route parameters include at least a vehicle thermal load value associated with the target vehicle route;

select one of the multiple autonomous vehicles according to the route parameters and the thermal cooling priority status of said autonomous vehicle;

deploy the selected one of the multiple autonomous vehicles to execute the target vehicle route using automated driving;

obtain key performance indicator values after completion of the target vehicle route by the selected one of the multiple autonomous vehicles;

receive feedback input from a rider in the selected one of the multiple autonomous vehicles after completion of the target vehicle route; and

update an autonomous vehicle deployment selection model based on the key performance indicator values and the feedback input.

16 . The system of claim 15 , wherein the automated driving includes automated acceleration control of the selected one of the multiple autonomous vehicles, automated braking control of the selected one of the multiple autonomous vehicles, and automated steering control of the selected one of the multiple autonomous vehicles based on the target vehicle route.

17 . The system of claim 15 , wherein the autonomous vehicle service request includes at least one of an autonomous vehicle ride hail request or an autonomous vehicle package delivery request.

18 . The system of claim 15 , wherein the vehicle status parameters include at least one of a sensed passenger cabin temperature, a sensed passenger cabin humidity, and a state of charge of a vehicle battery module.

19 . The system of claim 15 , wherein the route parameters include at least one of an outside air temperature value, a solar load associated with the target vehicle route, an incline grade along the target vehicle route, a vehicle front end air flow (FEAF) value, and a degree of expected vehicle stops along the target vehicle route.

20 . The system of claim 15 , wherein selecting one of the multiple autonomous vehicles includes selecting an autonomous vehicle having a highest battery module state of charge among multiple vehicles having a same thermal cooling priority status.