US 12,454,271 B2
Operation management aid system and operation management aid method
Nao Ito, Tokyo (JP); Takeshi Tanaka, Tokyo (JP); Shunsuke Minusa, Tokyo (JP); Hiroyuki Kuriyama, Tokyo (JP); and Kiminori Sato, Tokyo (JP)
Assigned to LOGISTEED, LTD., Tokyo (JP)
Appl. No. 18/566,244
Filed by LOGISTEED, LTD., Tokyo (JP)
PCT Filed May 26, 2022, PCT No. PCT/JP2022/021596
§ 371(c)(1), (2) Date Dec. 1, 2023,
PCT Pub. No. WO2022/259881, PCT Pub. Date Dec. 15, 2022.
Claims priority of application No. 2021-095970 (JP), filed on Jun. 8, 2021.
Prior Publication US 2024/0286620 A1, Aug. 29, 2024
Int. Cl. B60W 40/08 (2012.01); B60W 50/00 (2006.01); B60W 50/14 (2020.01)
CPC B60W 40/08 (2013.01) [B60W 50/0097 (2013.01); B60W 50/14 (2013.01); B60W 2050/0083 (2013.01); B60W 2050/146 (2013.01); B60W 2540/221 (2020.02); B60W 2556/20 (2020.02)] 11 Claims
OG exemplary drawing
 
1. An operation management aid system for reducing driver accident risk, the operation management aid system comprising:
a memory that stores a first group of associated data in which biological measurement data pertaining to a biology of a driver is associated with task state data pertaining to a respective task state among a plurality of task states of the driver, and a second group of danger determination results indicating a degree of danger of driving by the driver; and
a processor that is communicatively coupled to the memory, wherein the processor is configure to:
perform a first acquisition process that acquires for each of the plurality of task states, the associated data pertaining to a specific task state of the driver from the first group, and acquiring a specific danger determination result group in the specific task state of the driver from the second group,
perform a generation process, using an associated data group pertaining to the specific task state and a specific danger determination result group for the specific task state, which were acquired during the first acquisition process, to generate, for each of the specific task states, an estimation model that estimates an accident risk of the driver during the specific task state, and saving the estimation model in a third group,
execute an association process of associating the biological measurement data with the task state of the task state data during a same time period and for a same driver, and saving the associated data in the first group, and
executes a detection process of detecting invalid data indicating behavior irrelevant to the association process, from among the biological measurement data groups split into time segments,
wherein, during the association process, the processor does not perform association for the invalid data detected during the detection process
wherein the first acquisition process includes:
acquiring an associated data group pertaining to the specific task state of the driver from the first group in which the associated data that was associated by the association process is saved, and
wherein association process includes
splitting the biological measurement data into time segments,
for each biological measurement data group split into time segments, associating therewith the task state of the task state data during the same time period and for the same driver, and
saving the associated biological measurement data group and task state in the first group.