@article{ref1,
title="Distance estimation models between vehicle and stop lines using inclusion-exclusion integral",
journal="Journal of Japan Society for Fuzzy Theory and Intelligent Informatics",
year="2021",
author="Hirano, Yuki and Matsuki, Ryosuke and Hayase, Mitsuhiro and Kanoh, Masayoshi and Jimenez, Felix and Yoshikawa, Tomohiro and Tanaka, Takahiro and Kanamori, Hitoshi",
volume="33",
number="4",
pages="839-844",
abstract="In recent years, the percentage of traffic accidents involving elderly drivers has been increasing, and it is becoming a social problem. To prevent the traffic accidents, it is important for elderly drivers to improve own driving by reviewing it. We have been developing a system that allows to review driving situations at home, in order to improve driving behavior. In this paper, we propose models for estimating the distance between a vehicle and stop lines by using the inclusion-exclusion integral regression model from dashboard camera for the system. First, we extract an image where the markers are placed with known distance to the car in order to build a model. Second, we build six models by varying t-norm of the inclusion-exclusion integral regression model. Then, we compare estimated distances with each obtained model.   ===  近年，交通事故全体に占める高齢運転者の事故割合の増加が問題となっている．高齢者が交通事故を未然に防ぐためには，自身の運転を振り返り，運転行動を改善することが重要である．我々は，運転行動を改善するために，自宅で運転を振り返るためのシステムを構築している．本稿では，同システムのための，運転記録動画から自動車と停止線間の距離を推定するための包除積分を用いた距離推定モデルを提案する．まず，モデルを構築するために，自動車までの距離が既知のマーカーを配置した画像を取得する．次に，包除積分のtノルムを変化させた複数のモデルを構築する．そして，得られたモデルによる推定距離を比較する．<p /> <p>Language: ja</p>",
language="ja",
issn="1347-7986",
doi="10.3156/jsoft.33.4_839",
url="http://dx.doi.org/10.3156/jsoft.33.4_839"
}