Toyota Jidosha Kabushiki Kaisha

Naoyuki Saka

Toshiyuki Kawai

Takayuki Akaishi

Tsukasa Kato

Hiroyuki Tokita

Shugen Yamamura

Katsuhisa Yoshikawa

Ryosuke Fukaya

Yusuke Ikenoue

Hiroki Takeuchi

Atsushi Miyagawa

Ayumu Shiomi

A method includes, by a processor, acquiring number of persons information that indicates a number of users, including users who ride in vehicles, who depart from a facility at each of a predetermined time period, weather information for each predetermined time period, and vehicle information relating to vehicles traveling in a periphery of the facility, determining traffic jam status that indicates absence/presence of a traffic jam on a road located in a vicinity of the facility in the predetermined time period, by using the vehicle information; and generating a learned model for predicting a traffic jam of a road by machine learning using, as teaching data, the number of persons information, the weather information, and the traffic jam status that is associated with the number of persons information and the weather information.

Method for generating learned model, non-transitory storage medium, and traffic jam predicting device

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Toyota, Japan

Naoyuki Saka