VEHICLE ACCIDENT PREDICTION SYSTEM, VEHICLE ACCIDENT PREDICTION METHOD, VEHICLE ACCIDENT PREDICTION PROGRAM, AND TRAINED MODEL GENERATION SYSTEM

• Main Authors: KUBOTA MAKI, TANAKA JUNJI, HAGIYA KENICHI, UTSUGI TAKUMI, MUKAIDA YUKINOBU, ZUSHI HIDEYUKI, MATSUI YUTAKA, TAKAHASHI NAOYA, SHIMATANI HAJIME, NAKAHATA RYOSUKE
• Format: Patent
• Language: English; Japanese
• Published: 10.02.2022
• Subjects: PHYSICS; SIGNALLING; TRAFFIC CONTROL SYSTEMS

To provide a vehicle accident prediction system, a vehicle accident prediction method, a vehicle accident prediction program, and a trained model generation system, which are capable of appropriately predicting an accident.SOLUTION: A vehicle accident prediction system, a vehicle accident prediction method, a vehicle accident prediction program, and a trained model generation system, acquire a learning data set D3 consisting of feature amount group data D1 and accident data D2 related to an accident of a vehicle, the feature amount group data including a first feature amount D11 representing an attribute of a driver of the vehicle, a second feature amount D12 representing the state of the vehicle, and a third feature amount D13 combining a plurality of second feature amounts D12; use the acquired plurality of learning data sets D3 to generate a trained model M for predicting the accident of the vehicle from the feature amount group data D1 by learning; and input the feature amount group data D1 to be predicted and use the generated trained model M so as to predict the vehicle accident from the input feature amount group data D1.SELECTED DRAWING: Figure 2 【課題】適正に事故予測を行うことができる車両事故予測システム、車両事故予測方法、車両事故予測プログラム、及び、学習済みモデル生成システムを提供することを目的とする。【解決手段】車両事故予測システム、車両事故予測方法、車両事故予測プログラム、及び、学習済みモデル生成システムは、車両のドライバの属性を表す第１特徴量Ｄ１１、車両の状態を表す第２特徴量Ｄ１２、及び、複数の第２特徴量Ｄ１２を組み合わせた第３特徴量Ｄ１３を含む特徴量群データＤ１と車両の事故に関する事故データＤ２とからなる学習用データセットＤ３を取得し、取得された複数の学習用データセットＤ３を用いて、特徴量群データＤ１から車両の事故を予測する学習済みモデルＭを学習により生成し、予測対象となる特徴量群データＤ１を入力し、生成された学習済みモデルＭを用いて、入力された特徴量群データＤ１から車両の事故を予測する。【選択図】図２