基於特徵追蹤之多車道車輛偵測技術與前車防碰撞系統應用

Abstract

本論文提出前車防撞警示系統的設計以及驗證，所提出的演算法對於每一張畫面採用車輛偵測以及特徵追蹤，特徵追蹤可適應於多天候(如日間、夜間、雨天)的場景，當車輛偵測所需特徵較不明顯時，特徵追蹤能夠提升畫面中車輛定位的穩定性。本論文所提的系統不僅支援定位主車道車輛，也能定位畫面中左車道以及右車道最靠近的車輛，進而計算出偵測車輛與攝影機之距離，使得本論文提出的系統更能適用於前車防碰撞系統之應用。 本演算法研發並實作於個人電腦，用行車紀錄器拍攝的實車影片當作影像輸入，在D1解析度下，單車道前車防碰撞警示技術的處理效能可以達每秒327張，而三車道前車防碰撞警示技術的處理效能可以達每秒183張；本系統偵測結果與ground truth比對每一張畫面，單車道前車防碰撞警示技術在日間可達96.37%的偵測率，在夜間可達87.64%的偵測率；三車道前車防碰撞警示技術在日間可達94.05%的偵測率，在夜間可達86.90%的偵測率。本演算法也實作於Freescale i.MX6平台，並且用USB網路攝影機當作影像輸入，在D1解析度下，三車道前車防碰撞警示技術的處理效能可以達每秒29張。

This thesis proposes the design and verification of one popular Advanced Driver Assistance System (ADAS) function: Forward Collision Warning System (FCWS). The proposed method apply vehicle detection and feature tracking to each frame in the videos. Feature tracking, which is adopted to conquer the effect of some critical case like non-ideal shadow, raindrop and windshield wiper, can increase the stability of vehicle localization. The proposed system can be applied to the application of single-lane FCWS, which includes main lane and three-lane FCWS which includes left lane, main lane and right lane. In order to be more suitable for the application of FCWS, the proposed system also calculate the distance between located vehicles and camera. The proposed algorithm is implemented on the personal computer. The input video of the system is captured from driving recorders in D1 resolution (720x480). The performance of the proposed single-lane FCWS can achieve 327 fps and that of the proposed three-lane FCWS can achieve 183 fps in average. The test results are compared with ground truth frame by frame. Detection rate of the proposed single-lane FCWS can reach 96.37% at daytime and 87.64% at night. Moreover, detection rate of the proposed three-lane FCWS can reach 94.05% at daytime and 86.90% at night. The proposed system is also implemented on Freescale i.MX6 with a USB webcam to capture the video. Under the D1 (720x480) resolution, the performance of the proposed 3-lane FCWS can achieve 29 fps.