パキスタンの弱い立場の道路利用者が関与する事故の重度に影響を与える要因の調査
Muhammad Junaid1, Chaozhe Jiang2, Saleh Alotaibi3
1School of Transportation and Logistics, Southwest Jiaotong University (SWJTU), Chengdu, China.
Scientific reports
|September 2, 2025
まとめ
55歳以上の脆弱な道路利用者 (VRU) は,衝突,バン,重型車両,雨,COVID-19のロックダウンにより,道路事故で重傷を負うリスクが著しく増加します. 分析に最も効果的であることが判明しました.
科学分野:
- 交通安全について
- 交通工学
- 機械学習アプリケーション
背景:
- 道路交通事故は全世界で119万人以上が死亡し,その半数以上は脆弱な道路利用者 (VRU) によるものです.
- パキスタンのすべてのVRUの集団的危険因子に関する研究は限られていますが,安全性の課題は独特です.
- この研究では,VRUの事故重度のリスク要因の組み合わせを分析することで,このギャップを埋めました.
研究 の 目的:
- 脆弱な道路使用者 (VRU) が関与する事故の重度に対する様々な危険因子の影響を調査する.
- VRUのクラッシュの重さを予測するための6つのブーストベースのアンサンブル機械学習分類器の性能を評価する.
- VRU の重傷の原因となる主要な要因を特定する.
主な方法:
- 脆弱な道路利用者 (VRU) が関与する道路交通事故の3年間のデータセット (2021-2023) を利用しました.
- エクストリーム・グラデント・ブースティング,ライト・グラデント・ブースティング,ディシジョン・ストンプを含む6つのブースティングベースのアンサンブル・マシン・ラーニングの分類器を使用した.
- モデル結果を解釈し,重要なリスク要因を特定するために,部分依存性グラフとSHAP相互作用グラフを適用した.
主要な成果:
- ディシジョンストンプによる増強は,他のテストされた分類器と比較して,リコール,F1スコア,および精度において優れたパフォーマンスを示した.
- 重度のVRU負傷の主要な危険因子:年齢 (55歳以上),他のVRUグループとの衝突,バン/重量車両の関与,雨天,COVID-19期間,塗装された中間値.
- SHAPの分析は,車両の種類,悪天候,COVID-19のロックダウン期間との相互作用が事故の重度のリスクを拡大することを確認した.
結論:
- 機械学習,特に意思決定ストンプの強化は,VRUのクラッシュの重さを分析するのに有効です.
- 特定の人口,環境,および車両の要因は,脆弱な道路利用者の重傷のリスクを大幅に高めます.
- 政策の推奨事項には,標的型教育,混合交通管理戦略,VRUの安全性を高めるためのインフラ改善が含まれています.
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