IP Library › Granted Patent US 11,453,399
Granted Patent B2
US 11,453,399 · App. 16/987,516 · Granted Sep 27, 2022

Flood sensing device, flood sensing system, and non-transitory computer readable medium

Inventors: Jun Hattori (Chofu, JP); Takayuki Yamabe (Nagoya, JP); Kenki Ueda (Edogawa-ku, JP); Tetsuya Hashimoto (Shinagawa-ku, JP); Hajime Tojiki (Musashino, JP); Naoki Ishihara (Shinagawa-ku, JP); Yuta Ochiai (Yokohama, JP); Hideki Kawai (Edogawa-ku, JP)
Assignee: TOYOTA JIDOSHA KABUSHIKI KAISHA
B60W40/06G05D1/0214G08G1/0112B60W2555/20
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Quick Facts
Patent No.
US 11,453,399
App. No.
16/987,516
Granted
Sep 27, 2022
Kind
B2
Abstract

A flood sensing device includes: an acquiring section that acquires plural types of traveling state data relating to traveling of a vehicle; and a sensing section that senses flooding of a road on which the vehicle travels by using (a) a physical quantity that is estimated on the basis of (i) a vehicle behavior model, which is configured by driving force of the vehicle and traveling resistance that includes air resistance applied to the vehicle, slope resistance applied to the vehicle and rolling resistance applied to the vehicle, and which determines the physical quantity that varies due to the vehicle traveling, and (ii) the plural types of traveling state data of the present time that are acquired by the acquiring section, and (b) the physical quantity that is obtained from the traveling state data of the present time that is acquired by the acquiring section.

Claims (11)

1. A flood sensing device comprising:

a memory: and

a processor coupled to the memory, the processor configured to:

acquire a plurality of types of traveling state data relating to traveling of a vehicle; and

sense flooding of a road on which the vehicle travels by using (a) a physical quantity that is estimated on the basis of (i) a vehicle behavior model derived by machine learning using a multiple regression formula, which is configured by a driving force of the vehicle and a traveling resistance that includes an air resistance applied to the vehicle, a slope resistance applied to the vehicle, and a rolling resistance applied to the vehicle, and which determines the physical quantity that varies due to the vehicle traveling, and (ii) the plurality of types of traveling state data of the present time that are acquired, and (b) the physical quantity that is obtained from the traveling state data of the present time that is acquired.

2. The flood sensing device of claim 1 , wherein the traveling resistance further includes acceleration resistance that is applied to the vehicle.

3. The flood sensing device of claim 1 , wherein the processor is further configured to, in a case in which a difference between the estimated physical quantity and the physical quantity obtained from the traveling state data is greater than or equal to a predetermined threshold value, determine that there is flooding and sense flooding.

4. The flood sensing device of claim 1 , wherein the vehicle behavior model is derived by using an equation of motion, by using speed, acceleration, or rate of change in acceleration of the vehicle, as the physical quantity.

5. A non-transitory computer readable medium storing a flood sensing program executed by a computer to perform a process comprising:

acquiring a plurality of types of traveling state data relating to traveling of a vehicle; and

sensing flooding of a road on which the vehicle travels by using (a) a physical quantity that is estimated on the basis of (i) a vehicle behavior model derived by machine learning using a multiple regression formula, which is configured by a driving force of the vehicle and a traveling resistance that includes an air resistance applied to the vehicle, a slope resistance applied to the vehicle, and a rolling resistance applied to the vehicle, and which determines the physical quantity that varies due to the vehicle traveling, and (ii) the plurality of types of traveling state data of the present time that are acquired, and (b) the physical quantity that is obtained from the traveling state data of the present time that is acquired.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 7, 2020
From: HATTORI, JUN; YAMABE, TAKAYUKI; UEDA, KENKI; HASHIMOTO, TETSUYA; TOJIKI, HAJIME; ISHIHARA, NAOKI; OCHIAI, YUTA; KAWAI, HIDEKI
To: TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 053428/0486 →
Priority Claims (1)
JP JP2019-148408 · Aug 13, 2019 · national
Continuity (1)
Related Publication 20210046937A1 · Feb 18, 2021