IP Library › Granted Patent US 12,626,592
Granted Patent B2
US 12,626,592 · App. 17/943,665 · Granted May 12, 2026

Cloud-based stop-and-go mitigation system with multi-lane sensing

Inventors: Yashar Zeiynali Farid (Mountain View, CA); Kentaro Oguchi (Mountain View, CA)
Assignees: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.; TOYOTA JIDOSHA KABUSHIKI KAISHA
G08G1/096725G08G1/0112G08G1/0129G08G1/0133G08G1/0145G08G1/052G08G1/096775
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Quick Facts
Patent No.
US 12,626,592
App. No.
17/943,665
Granted
May 12, 2026
Kind
B2
Abstract

Systems and methods are provided for activating mitigation strategies through a cloud-based system. Embodiments of the systems and methods disclosed herein can provide mitigation strategies to reduce or eliminate the stop-and-go traffic. A control vehicle can activate a mitigation strategy and operate the vehicle in accordance with the mitigation strategy based on stop-and-go waves. The mitigation strategy may comprise maintaining the vehicle at a reference speed.

Claims (41)

1 . A method comprising:

identifying trajectories of a plurality of vehicles traveling in a same direction on a same road, the plurality of vehicles comprising a control vehicle;

based on the trajectories, generating a plurality of stop-and-go waves representing predicted future velocities of traversing vehicles within different positions of a bottleneck at different times, the traversing vehicles comprising at least a subset of the vehicles or different vehicles, wherein at least one stop-and-go wave of the plurality of stop-and-go waves comprises an acceleration region and a deceleration region;

determining one or more cyclical characteristics of the at least one stop-and-go wave of the plurality of the stop-and-go waves, wherein the one or more cyclical characteristics comprise a period or a wavelength;

defining a control zone based on the bottleneck and based on the one or more cyclical characteristics of the at least one stop-and-go wave; and

operating the control vehicle by programming one or more operating characteristics of the control vehicle at the different times based on the one or more cyclical characteristics, a current position of the control vehicle, and the predicted future velocities, wherein programming one or more operating characteristics comprises:

in response to determining that the bottleneck comprises a fixed waiting time attribute:

applying a prediction model to predict a waiting time duration based on historical trajectory data or historical infrastructure data; and

regulating one or more velocities of the control vehicle based on the predicted waiting time duration.

2 . The method of claim 1 ,

wherein the determining of the one or more cyclical characteristics comprises determining the at least one stop-and-go wave of the plurality of stop-and-go waves has a highest wavelength relative to other stop-and-go waves of the plurality of stop-and-go waves; and the method further comprises:

setting an entrance boundary for the control zone based on the highest wavelength.

3 . The method of claim 1 , wherein the programming of the one or more operating characteristics comprises:

in response to determining that the bottleneck comprises a fixed cycle time duration attribute:

selecting a stop-and-go wave of the plurality of stop-and-go waves; and

regulating the one or more velocities of the control vehicle based on the fixed cycle time duration and the selected stop-and-go wave.

4 . The method of claim 1 , wherein the programming of the one or more operating characteristics comprises setting an initial velocity and updating the initial velocity after a stop-and-go wave.

5 . The method of claim 1 , wherein the programming of the one or more operating characteristics is based on historical stop-and-go waves corresponding to previous occurrences of the bottleneck.

6 . The method of claim 1 , wherein each stop-and-go wave of the plurality of stop-and-go waves comprises a deceleration region, a stopping region and a cruising region.

7 . A cloud-based system, comprising:

a processor; and

a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to:

identify trajectories of a plurality of vehicles traveling in a same direction on a same road, the plurality of vehicles comprising a control vehicle;

based on the trajectories, generate a plurality of stop-and-go waves representing predicted future velocities of traversing vehicles within different positions of a bottleneck at different times, the traversing vehicles comprising at least a subset of the vehicles or different vehicles, wherein at least one stop-and-go wave of the plurality of stop-and-go waves comprises an acceleration region and a deceleration region;

determining one or more cyclical characteristics of the at least one stop-and-go wave of the plurality of the stop-and-go waves, wherein the one or more cyclical characteristics comprise a period or a wavelength;

define a control zone based on the bottleneck and based on the one or more cyclical characteristics of the at least one stop-and-go wave; and

operate the control vehicle by programming one or more operating characteristics of the control vehicle at the different times based on the one or more cyclical characteristics, a current position of the control vehicle, and the predicted future velocities, wherein programming one or more operating characteristics comprises:

in response to determining that the bottleneck comprises a fixed waiting time attribute:

applying a prediction model to predict a waiting time duration based on historical trajectory data or historical infrastructure data; and

regulating one or more velocities of the control vehicle based on the predicted waiting time duration.

8 . The cloud-based system of claim 7 , wherein the programming of the one or more operating characteristics comprises:

in response to determining that the bottleneck comprises a fixed cycle time duration attribute:

selecting a stop-and-go wave of the plurality of stop-and-go waves; and

regulating the one or more velocities of the control vehicle based on the fixed cycle time duration and the selected stop-and-go wave.

9 . The cloud-based system of claim 7 , wherein the programming of the one or more operating characteristics comprises setting an initial velocity and updating the initial velocity after a stop-and-go wave.

10 . The cloud-based system of claim 7 , wherein the programming of the one or more operating characteristics is based on historical stop-and-go waves corresponding to previous occurrences of the bottleneck.

11 . The cloud-based system of claim 7 , wherein the programming of the one or more operating characteristics is based on an average speed of the plurality of vehicles.

12 . The method of claim 2 , wherein the setting of the entrance boundary comprises determining a position of a rear bumper of a last vehicle of the plurality of vehicles within the bottleneck, and setting the entrance boundary as an offset by the highest wavelength from the position of the rear bumper of the last vehicle to thereby provide a buffering distance to program the one or more operating characteristics before encountering a stop-and-go wave.

13 . The method of claim 1 , wherein the at least one stop-and-go wave comprises a first stop-and-go wave having a first deceleration region, a first stopping region, and a first acceleration region and a second stop-and-go wave adjacent to the first stop-and-go wave, the second stop-and-go wave comprising a second deceleration region immediately adjacent to the first acceleration region of the first stop-and-go wave.

14 . The method of claim 13 , wherein the one or more operating characteristics comprises a velocity, and the first stop-and-go wave has a first wavelength different from a second wavelength of the second stop-and-go wave.

15 . The method of claim 1 , wherein the programming of the one or more operating characteristics is based on a jerk of the control vehicle, a traffic oscillation caused by the programming of the one or more operating characteristics, and predicted braking forces corresponding to the control vehicle and one or more other vehicles within a threshold distance of the control vehicle resulting from the programming of the one or more operating characteristics.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 18, 2026
From: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
To: TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 075009/0967 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 13, 2022
From: ZEIYNALI FARID, YASHAR; OGUCHI, KENTARO
To: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.; TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 061078/0749 →
Continuity (1)
Related Publication 20240087452A1 · Mar 14, 2024
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