System and method for predicting tire traction capabilities and active safety applications

Patent metadata

Field	Value
Publication number	US-2022017090-A1
Application number	US-202117449391-A
Country	US
Kind code	A1
Filing date	Sep 29, 2021
Priority date	Apr 1, 2019
Publication date	Jan 20, 2022
Grant date	—

Abstract

A system and method are provided for estimating and applying vehicle tire traction. Vehicle data (e.g., movement and location-based data) and tire sensor data are collected at a vehicle and transmitted to a remote computing system (e.g., cloud server). A wear status is determined, and traction characteristics determined for at least one tire, based at least on the vehicle data and the determined tire wear status. The predicted tire traction characteristics are transmitted from the remote computing system to an active safety unit associated with the vehicle, or a fleet management system, wherein the recipient is configured to modify vehicle operation settings based on at least the predicted tire traction characteristics. A maximum speed for the vehicle may be defined by the recipient, or a minimum following distance where, e.g., the vehicle is one of multiple vehicles in a defined platoon.

First claim

What is claimed is:

1 . A method for automatically estimating and selectively applying vehicle tire traction characteristics, the method comprising:
collecting vehicle data comprising movement data and location data in association with a vehicle; determining a tire wear status for at least one tire associated with the vehicle; predicting one or more tire traction characteristics for the at least one tire, based at least on the transmitted vehicle data and the determined tire wear status; and selectively modifying one or more vehicle operation settings based on at least the predicted one or more tire traction characteristics.

2 . The method of claim 1 , wherein the one or more tire traction characteristics comprise one or more parameters of a predicted mu-slip curve associated with a respective tire.

3 . The method of claim 1 , further comprising:
determining a maximum speed for the vehicle based on at least on the transmitted vehicle data and a determined tire wear status for each tire associated with the vehicle.

4 . The method of claim 3 , further comprising:
providing the maximum speed to an autonomous vehicle control system associated with the vehicle.

5 . The method of claim 3 , further comprising:
providing the maximum speed to a driver assistance interface associated with the vehicle.

6 . The method of claim 1 , wherein the step of determining the tire wear status comprises:
receiving one or more tire wear input values from a user via a user interface.

7 . The method of claim 1 , wherein the step of determining the tire wear status comprises:
receiving one or more tire wear input values generated by one or more sensors mounted in or on a respective tire of the at least one tire.

8 . The method of claim 1 , wherein the step of determining the tire wear status comprises:
receiving one or more tire wear input values generated by a sensor external to the vehicle.

9 . The method of claim 1 , wherein the step of determining the tire wear status comprises:
predicting one or more tire wear input values based on at least the transmitted vehicle data and on tire data generated by one or more sensors mounted in or on a respective tire of the at least one tire.

10 . A system for automatically estimating and selectively applying vehicle tire traction characteristics, the system comprising:
a computing device or network functionally linked to a vehicle via a communications network, wherein vehicle data collected via an onboard device and/or one or more sensors and comprising movement data and location data in association with the vehicle is transmitted from the vehicle to the computing device or network, and wherein the computing device or network is configured to:
determine a tire wear status for at least one tire associated with the vehicle;
predict one or more tire traction characteristics for the at least one tire, based at least on the transmitted vehicle data and the determined tire wear status; and
provide the one or more predicted tire traction characteristics to an active safety unit associated with the vehicle,
wherein the active safety unit is configured to selectively modify one or more vehicle operation settings based on at least the predicted one or more tire traction characteristics.

11 . The system of claim 10 , wherein:
the active safety unit comprises an automated braking system associated with the vehicle, and the computing device or network is configured to provide one or more parameters of a predicted mu-slip curve associated with a respective tire to the automated braking system.

12 . The system of claim 10 , further comprising:
a user interface associated with the computing device or network and configured to receive one or more tire wear input values from a user.

13 . The system of claim 10 , wherein the computing device or network is configured to:
determine a maximum speed for the vehicle based on at least on the transmitted vehicle data and a determined tire wear status for each tire associated with the vehicle; and provide the maximum speed to a driver assistance interface associated with the vehicle.

14 . The system of claim 10 , wherein the active safety unit comprises an autonomous vehicle control system.

15 . A system for automatically estimating and selectively applying vehicle tire traction characteristics, the system comprising:
a first computing device or network functionally linked to each of a plurality of vehicles via a communications network; a fleet management device or network functionally linked to the first computing device or network; and a vehicle control system associated with each of the plurality of vehicles, wherein, for each of the plurality of vehicles:
vehicle data collected via an onboard device and/or one or more sensors and comprising movement data and location data in association with the vehicle is transmitted from the respective vehicle to the first computing device or network;
the first computing device or network is configured to
determine a tire wear status for at least one tire associated with the vehicle;
predict one or more tire traction characteristics for the at least one tire, based at least on the transmitted vehicle data and the determined tire wear status; and
provide the one or more predicted tire traction characteristics to the fleet management computing device or network; and

the fleet management computing device or network is configured to interact with the respective vehicle control system for modifying the one or more vehicle operation settings based on at least the predicted one or more tire traction characteristics.

16 . The system of claim 15 , wherein the predicted one or more tire traction characteristics comprise one or more parameters of a predicted mu-slip curve associated with a respective tire.

17 . The system of claim 15 , wherein:
a user interface associated with one or more of first computing device or network, the fleet management computing device or network, and the vehicle control system is configured to receive one or more tire wear input values from a user.

18 . The system of claim 15 , wherein the fleet management computing device or network is configured to:
determine a maximum speed and/or stopping distance potential for a given vehicle based on at least on the transmitted vehicle data and a determined tire wear status for each tire associated with the respective vehicle; and provide the determined maximum speed and/or stopping distance potential to the vehicle control system associated with the vehicle.

19 . The system of claim 18 , wherein the fleet management computing device or network is further configured to:
determine an optimal following distance for each of a plurality of vehicles associated with a platoon of vehicles travelling in sequence, and transmit the determined optimal following distance for each one of the plurality of vehicles to the respective vehicle control system.

20 . The system of claim 15 , wherein the fleet management computing device or network is configured to:
determine a maximum speed and/or stopping distance potential for a given vehicle based on at least on the transmitted vehicle data and a determined tire wear status for each tire associated with the respective vehicle; determine whether the vehicle satisfies threshold traction characteristics; and interact with the vehicle control system to prevent deployment of, or otherwise remove from use, the respective vehicle if the vehicle doe

Assignees

• Bridgestone Americas Tire Operations Llc

Inventors

• Sams Thomas A
• Barr Jason R
• Doraiswamy Srikrishna

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• H04L2012/40273

  the transportation system being a vehicle · CPC title

• H04L2012/40215

  Controller Area Network CAN · CPC title

• H04L12/40

  Bus networks · CPC title

• G07C5/0808

  Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005) · CPC title