Central operations center for autonomous vehicle enhancement system

Patent metadata

Field	Value
Publication number	US-12078495-B2
Application number	US-202217876648-A
Country	US
Kind code	B2
Filing date	Jul 29, 2022
Priority date	May 8, 2017
Publication date	Sep 3, 2024
Grant date	Sep 3, 2024

Abstract

The present application is directed to an Autonomous Vehicle Enhancement System (AVES) and method for monitoring and managing a virtual or existing fleet of autonomous vehicles in a transportation network and dispatching the autonomous vehicles to users. The AVES includes an AVES Central Operations Center (COC) that communicates with AVES vehicle equipment installed in the autonomous vehicles and AVES applications installed on computing devices accessible by the users. The AVES improves the operating efficiency of a transportation network by monitoring the condition of autonomous vehicles, optimizing the geographical distribution of the autonomous vehicles and optimizing assignment of the autonomous vehicles to users requesting services. The AVES COC monitors and controls the autonomous vehicles via the AVES vehicle equipment. The AVES COC communicates with the users via the AVES applications to provide services to the users. The AVES vehicle equipment and the AVES applications installed on the computing devices communicate with each other to fulfill user request for services.

First claim

What is claimed is:

1. An Autonomous Vehicle Enhancement System (AVES) Central Operations Center (COC) for managing a fleet of registered autonomous vehicles in a transportation network and dispatching the autonomous vehicles in the fleet to registered users of the transportation network, comprising:
a computer server in communication with AVES vehicle equipment installed on each autonomous vehicle in the fleet and with AVES applications installed on computing devices accessible by users, the computer server comprising an artificial intelligence system including a knowledge base;
wherein the computer server monitors the fleet of autonomous vehicles via the AVES vehicle equipment installed on each autonomous vehicle to determine real-time vehicle location, real-time vehicle availability, real-time vehicle operational state, real-time vehicle condition and real-time vehicle fuel/power-charge level of each autonomous vehicle in the fleet;
wherein the computer server assigns autonomous vehicles in the fleet to an active pool if the autonomous vehicles are available, are in acceptable operational state, are in acceptable condition and have acceptable fuel/power-charge level;
wherein the computer server receives trip requests from hailing users;
wherein the artificial intelligence system executes a matchmaking algorithm that uses the knowledge base to autonomously select autonomous vehicles from the active pool that are optimally suited to respond to the trip requests;
wherein the computer server guides the selected autonomous vehicles to the hailing users;
wherein the computer server guides autonomous vehicles in the fleet, which are not in acceptable operational state or condition, to service locations for maintenance service;
wherein the computer server guides autonomous vehicles in the fleet, which do not have acceptable fuel/power-charge level, to fueling/power-charging stations for fueling/power-charging;
wherein the computer server guides autonomous vehicles in the active pool, which are not assigned to respond to trip requests from hailing users, to standby locations throughout the transportation network's geographic area;
wherein the artificial intelligence system executes a vehicle distribution optimization algorithm that uses the knowledge base to dynamically determine the standby locations at any given moment for the autonomous vehicles in the transportation network's geographic area to achieve a vehicle distribution that is optimally suited for fulfilling potential trip requests;
wherein the real-time vehicle operational state of each autonomous vehicle in the fleet includes information regarding the operational state of mechanical and electrical systems of the autonomous vehicle, and the real-time vehicle condition of each autonomous vehicle in the fleet includes information regarding state of cleanliness of the autonomous vehicle; and
wherein the AVES vehicle equipment comprises an Interactive Voice Response (IVR) System configured to receive an indication from a user that a newly arrived vehicle is in an unacceptable condition, and wherein the computer server is configured to determine the real-time vehicle condition of each autonomous vehicle in the fleet based on one or more indications associated with the respective vehicle provided by the user of the respective vehicle via the IVR System.

2. The AVES COC according to claim 1 , wherein the computer server stores a vehicle profile for each registered autonomous vehicle in the fleet, the vehicle profile including a unique vehicle ID, vehicle owner specified restriction(s), license plate or other identifying markings, vehicle description information and billing or payment account.

3. The AVES COC according to claim 1 , wherein the computer server stores a user profile for each registered user of the transportation network, the user profile including a unique user ID, user preference(s), and billing or payment account.

4. The AVES COC according to claim 1 , wherein the knowledge base includes:
user preference(s) for each registered user of the transportation network;
historical information regarding trip requests, real-time information regarding trip requests, and information regarding scheduled events in the transportation network's geographic area; and
real-time vehicle location data, real-time vehicle availability data, real-time vehicle operational state, real-time vehicle condition data, real-time vehicle fuel/power-charge level indication, vehicle owner specified restriction(s) and vehicle description for each of the autonomous vehicles in the fleet.

5. The AVES COC according to claim 4 , wherein the vehicle distribution optimization algorithm uses from the knowledge base, at least one of the real-time vehicle location data for the autonomous vehicles in the active pool, the historical information regarding trip requests, the real-time information regarding trip requests and the information regarding scheduled events in the transportation network's geographic area, to dynamically determine the standby locations for the autonomous vehicles in the transportation network's geographic area.

6. The AVES COC according to claim 4 , wherein the matchmaking algorithm uses from the knowledge base, user preference(s) and at least one of the real-time vehicle location data, real-time vehicle availability data, the real-time vehicle operational state, the real-time vehicle condition data, the real-time vehicle fuel/power-charge level indication, the vehicle owner specified restriction(s) and the vehicle description for each of the autonomous vehicles in the fleet, to select autonomous vehicles from the active pool that are optimally suited to respond to the trip requests.

7. The AVES COC according to claim 4 , wherein the real-time information regarding trip requests and information regarding scheduled events in the transportation network's geographic area are received by the computer server from public messaging systems, the AVES applications installed on computing devices accessible by the users or the AVES vehicle equipment installed on the autonomous vehicles in the fleet.

8. The AVES COC according to claim 1 , wherein the real-time vehicle availability of each autonomous vehicle in the fleet includes information regarding whether the autonomous vehicle is in the active pool, has been assigned to respond a trip request from a hailing user, is waiting or en route to pickup a hailing user for an assigned trip request, has picked up a hailing user for an assigned trip request or has dropped off a hailing user after completion of an assigned trip request.

9. The AVES COC according to claim 1 , wherein the real-time vehicle fuel/power-charge level of each autonomous vehicle in the fleet includes information regarding at least one of a vehicle travel distance range, a percentage of fuel tank or electrical battery capacity available and units of available power or energy.

10. An Autonomous Vehicle Enhancement System (AVES) Central Operations Center (COC) for managing a fleet of registered autonomous vehicles in a transportation network and dispatching the registered autonomous vehicles in the fleet to registered users of the transportation network, comprising:
a computer server in communication with AVES vehicle equipment installed on each autonomous vehicle in the fleet and with AVES applications installed on computing devices accessible by the registered users, the computer server comprising an artificial intelligence system including a knowledge base;
wherein the computer server monitors the fleet of autonomous vehicles via the AVES vehicle equipment installed on each autonomous vehicle to determine real-time vehicle location, real-time vehicle availability, real-

Assignees

• Chase Arnold
• Chase William

Inventors

• Chase Arnold
• Chase William

Classifications

• H04L63/08

  for authentication of entities (cryptographic mechanisms or cryptographic arrangements for entity authentication H04L9/32) · CPC title

• G08G1/0175

  by photographing vehicles, e.g. when violating traffic rules · CPC title

• G08G1/012

  from other sources than vehicle or roadside beacons, e.g. mobile networks · CPC title

• H04W4/90

  Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS] · CPC title

• H04N7/188

  Capturing isolated or intermittent images triggered by the occurrence of a predetermined event, e.g. an object reaching a predetermined position (signal generation from motion picture films H04N5/253) · CPC title