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    政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 >  Item 140.119/150170
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/150170


    Title: 基於深度和梯度角變化的交通違規偵測與車速預測
    Traffic Violation Detection based on Depth and Gradient Angle Change and Speed Prediction
    Authors: 劉宸羽
    Liu, Chen-Yu
    Contributors: 彭彥璁
    Peng, Yan-Tsung
    劉宸羽
    Liu, Chen-Yu
    Keywords: 交通違規檢測
    智能交通系統
    車輛行為分析
    Vehicle action analysis
    Traffic violation detection system
    Date: 2024
    Issue Date: 2024-03-01 13:42:07 (UTC+8)
    Abstract: 近年來,民眾檢舉的車輛違規案例越來越多,缺乏自動判斷檢舉影片中的車輛是否違規的系統導致警方的業務繁重。為了解決科技執法的問題,我們設計了一個基於物件偵測和深度變化的判斷系統,並加入了物件追蹤的先驗演算法來輔助判斷,我們還建立了自己的交通違規數據集。本文中,基於物件偵測和深度變化判斷系統的目標是解決兩種類型的交通違規行為:(1) 紅燈直行 (2) 紅燈左右轉,所提出的交通違規檢測系統包括兩個主要部分:違規目標跟踪(VTT:Violation Target Tracking)和目標行為分析(TAA:Target Action Analysis),我們首先在VTT階段檢測紅綠燈和車輛的車牌,並獲得它們的軌跡位置和深度;接下來,我們對車輛深度和方位角的變化進行建模以判斷交通違規行為。實驗結果表明,我們的違規檢測系統對於所有違規案例平均可以達到 76\% 的真實準確度和 81\% 的條件準確度。另外我們應用道路線偵測模型和數學分析方法來預測拍攝者行車紀錄器的車速,進而檢測是否超越道路速限。
    In recent times, there's been a surge in public reports on vehicle violations, straining law enforcement due to the absence of an automated system to assess reported video evidence for potential traffic breaches. To overcome these challenges in technology-driven law enforcement, we designed a system based on object detection, depth variation assessment, and prior object tracking algorithms. Our unique traffic violation dataset supports this system, which targets two specific violations: running red lights and making turns at red lights. It consists of Violation Target Tracking (VTT) and Target Action Analysis (TAA). The VTT phase identifies traffic lights and license plates, tracking their trajectory and depth. Modeling changes in vehicle depth and azimuth enables us to determine violations. Our system achieves an average accuracy of 0.76 for true positives and 0.81 for conditional accuracy in detecting violations. Furthermore, employing road line detection models and mathematical analysis enables us to predict vehicle speeds from dashcam footage, aiding in identifying speeding violations beyond road limits.
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    Description: 碩士
    國立政治大學
    資訊科學系
    110753129
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0110753129
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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