IP Library Granted Patent US 12,499,753
Granted Patent B2
US 12,499,753 · App. 17/476,144 · Granted Dec 16, 2025

Systems and methods for leveraging evasive maneuvers to classify anomalies

Inventors: Seyhan Ucar (Mountain View, CA); Ryan Mercer (Colton, CA)
Assignee: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
G08G1/0133G06V10/751G06V20/54G06V40/20
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Quick Facts
Patent No.
US 12,499,753
App. No.
17/476,144
Granted
Dec 16, 2025
Kind
B2
Abstract

Systems and methods are provided for the classification of anomalies present in road regions. Anomalies may be extrinsic or intrinsic. Intrinsic anomalies may pose a greater safety risk to drivers than extrinsic anomalies. Intrinsic anomalies may be identified by detection of an evasive maneuver of a vehicle in a road region, measurement of the properties of other vehicles and the surrounding environment in the road region, determination of a vehicle behavior pattern in a road region, and comparison of the determined vehicle behavior pattern in the road region to other vehicle behavior patterns stored in a database.

Claims (31)

1 . A road safety system comprising:

one or more processors; and

memory operatively connected to the one or more processors, the memory including computer code that when executed by the one or more processors causes the road safety system to:

collect sensor data of vehicles in a road region, the vehicles comprising a network of connected vehicles sharing respective sensor data with the road safety system;

determine, based on the collected sensor data, a collective vehicle behavior pattern for the vehicles;

compare the collective vehicle behavior pattern for the vehicles to other collective vehicle behavior patterns stored in a database;

based on the comparison, classify an anomaly present in the road region using a binary classification between an extrinsic anomaly or intrinsic anomaly, wherein:

an extrinsic anomaly comprises a physical condition present in the road region that does not depend on real-time or ongoing human behavior and decision making, and

an intrinsic anomaly comprises a dynamic condition in the road region that is a result of irregular driving behavior by a human driver that is determined to exceed a driving behavior threshold; and

responsive to classifying the anomaly present in the road region as an intrinsic anomaly, transmit an alert to at least one of vehicles in the road region and connected authorities.

2 . The road safety system of claim 1 , wherein the memory includes further computer code that when executed by the one or more processors causes the road safety system to detect an evasive maneuver performed by a first vehicle of the vehicles and identify secondary vehicles of the vehicles.

3 . The road safety system of claim 1 , wherein the memory includes further computer code that when executed by the one or more processors causes the road safety system to:

when a collective vehicle behavior pattern consistent with the collective vehicle behavior pattern for the vehicles is not present in the database, employ human observation techniques to classify the anomaly present in the road region as an extrinsic or intrinsic anomaly.

4 . The road safety system of claim 1 , wherein the memory includes further computer code that when executed by the one or more processors causes the road safety system to:

when the anomaly present in the road region is classified as an intrinsic anomaly, determine, based on the comparison of the collective vehicle behavior pattern for the vehicles and other collective vehicle behavior patterns, a level of risk posed by the intrinsic anomaly.

5 . The road safety system of claim 1 , wherein the database comprises collective vehicle behavior patterns for a selected geographic region.

6 . A road safety system comprising:

one or more processors; and

memory operatively connected to the one or more processors, the memory including computer code that when executed by the one or more processors causes the road safety system to:

collect sensor data from vehicles and environmental entities,

determine a collective vehicle behavior pattern for the vehicles based on the sensor data;

compare the collective vehicle behavior pattern to other collective vehicle behavior patterns;

based on the comparison, classify an anomaly present in a road region using a binary classification between an extrinsic anomaly or intrinsic anomaly, wherein:

an extrinsic anomaly comprises a physical condition present in the road region that does not depend on real-time or ongoing human behavior and decision making, and

an intrinsic anomaly comprises a dynamic condition in the road region that is a result of irregular driving behavior by a human driver that is determined to exceed a driving behavior threshold; and

transmit control instructions to at least one of the vehicles in the road region to perform evasive maneuvers based on the classification of the anomaly as an extrinsic or intrinsic anomaly.

7 . The road safety system of claim 6 , further comprising an anomaly database, wherein the anomaly database stores collective vehicle behavior patterns consistent with classification of anomalies.

8 . The road safety system of claim 7 , wherein the anomaly database further comprises efficient collective vehicle behavior patterns of the collective vehicle behavior patterns that are transmitted as instructions to vehicles in response to a detected and classified anomaly.

9 . The road safety system of claim 7 , wherein the anomaly database further comprises responsive resource deployment plans that are transmitted as instructions to connected authorities in response to a detected and classified anomaly.

10 . The road safety system of claim 9 , wherein connected authorities are selected from the group consisting of: law enforcement bodies, traffic control authorities, policymakers, and emergency services providers.

11 . The road safety system of claim 9 , wherein the determined collective vehicle behavior pattern is consistent with the irregular driving by the human driver and avoidance of the irregularly driving human driver.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 11, 2025
From: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
To: TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 073195/0571 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 15, 2021
From: UCAR, SEYHAN; MERCER, RYAN
To: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
Reel/Frame 057491/0329 →
Continuity (1)
Related Publication 20230083625A1 · Mar 16, 2023
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