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題名 | Vision-Based Guidance for Autonomous Land Vehicle Navigation in Outdoor Road Environments with Static and Moving Cars=利用電腦視覺原理使自動車能安全行駛於路面有汽車的室外道路上 |
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作者 | 陳光雄; 蔡文祥; Chen, Kuang-hsiung; Tsai, Wen-hsiang; |
期刊 | Proceedings of the National Science Council : Part A, Physical Science and Engineering |
出版日期 | 19980900 |
卷期 | 22:5 1998.09[民87.09] |
頁次 | 頁691-702 |
分類號 | 448.94 |
語文 | eng |
關鍵詞 | 電腦視覺原理; 自動車; 路面; Autonomous land vehicle; Vision-based navigation; Guidance; Cars; Model matching; Color information clustering; Image processing; Computer vision; |
中文摘要 | 本文提出一種利用電腦視覺、模式比對、及彩色分群等技巧的新方法使自動車能 安全行駛於路面有汽車的室外道路上。本方法偵測道路上可以安全行駛的路面來達到避碰的 效果。我們使用路的邊界來建立模式並用路面的明亮度來當作視覺特徵。我們檢查左右兩條 邊界線附近的點來決定路的寬度是否因為路面上存在著靜止或行駛中的汽車而產生變化。如 果左右兩邊車道的寬度均未發生變化,我們執行模式比對來對自動車作定位。如果有任一車 道的寬度發生變化,我們則執行相關的程序來求出新路面的寬度。如果新路面的寬度不等於 舊路面的寬度,我們便重建模式,然後執行模式比對來找出自動車在路面上的位置。接著我 們計算出一個適當的車子轉角使自動車沿著新路面的中心線行駛。我們做了許多成功的航行 測試驗證出所提方法的有效性。 |
英文摘要 | A new effective approach to vision-based guidance for autonomous land vehicle (ALV) navigation in outdoor road environments with static and moving cars using model matching and color information clustering techniques is proposed. The conventional way of detecting obstacles and cars in the navigation route, which is in general difficult, is avoided; instead, collision-free road area detection, which is usually easier, is adopted. Road boundaries are used to construct the reference model, and road surface intensity is selected as the visual feature. The pixels in a road image near the two lines representing the road boundary shape, which are estimated at the beginning of each navigation cycle, are checked to judge whether the left or right lane width has changed due to occlusion caused by nearby static or moving cars on the road. If both lane widths have not chanbed, model matching is performed immediately to find the ALV location. If either or both lane widths have changed, corresponding processes are performed to find the width of the occluded road, and a model is recreated if the new road width is different from the old one in the previous navigation cycle. Mode matching is then performed to locate the ALV on the occluded road. To save computing time, only partial model matching is performed. A turn angle is then computed to guide the ALV to follow the central path line on the extracted road for safe navigation. Various color information on roads is used to extract road surfaces, and a clustering algorithm is used to solve the problem caused by great changes of intensity in navigation environments. Successful navigation tests show that the proposed approach is effective for ALV guidance on common roads with static and moving cars. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。