Development of an Accident Risk Alert System for Agricultural Vehicles Using Artificial Intelligence

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K22579
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0602:Agricultural and environmental biology and related fields
• Research Institution: University of the Ryukyus (2022); Shinshu University (2020-2021)
• Principal Investigator: Aoyagi Yuya 琉球大学, 農学部, 助教 (20882195)
• Project Period (FY): 2020-09-11 – 2023-03-31
• Keywords: 農作業安全 / 農用車両 / トラクタ / リスク評価 / 転倒防止 / 人工知能

Outline of Final Research Achievements

In this study, we developed an autonomous driving algorithm that enables obstacle detection and obstacle avoidance by autonomous vehicles using artificial intelligence, aiming to construct an A.I. that assists operators of agricultural vehicles in selecting appropriate driving conditions to prevent accidents under various conditions. Although we were able to develop an effective countermeasure algorithm for a specific case by using artificial intelligence, further accumulation of risk assessment is needed to construct a universal artificial intelligence model that can be applied to all situations. The academic significance of the results of this research is that the various risk data necessary for the construction of the A.I. were clarified based on risk assessment using accident factor analysis and behavior simulation.

Free Research Field

農業機械学

Academic Significance and Societal Importance of the Research Achievements

本研究成果は，A.I.の構築に必要な様々なリスクデータを事故要因分析的なリスク評価と挙動シミュレーションを用いたリスク評価に基づいて明らかにできた点に学術的な意義がある。これらは，従来の農業機械および自動化された農業機械における農用車両転倒事故を低減する技術の提示を通して，人命尊重および労働環境の改善と健全な農業発展に寄与する。また，本手法を応用することで，国内のみならず，世界の様々な環境条件下で使用される農用車両の転倒事故解消に貢献し，世界の安全で快適な農業の実現に資する。