電腦視覺為基礎之交通辨識技術應用於車載駕駛輔助與交通監控研究

Computer Vision-Based Traffic Identification Technologies for On-board Driving Assistance and Traffic Monitoring

吳耀然(Yao-Jan Wu)

指導教授 ： 張堂賢

共同指導教授 ： 連豊力(Feng-Li Lian)

國立臺灣大學/工學院/土木工程學研究所/碩士(2004年)

https://doi.org/10.6342/NTU.2004.01506

摘要

本研究之目的係提出一個電腦視覺為基礎之公路安全系統架構。此架構主要包含三個部分：電腦視覺為基礎之行車駕駛輔助系統 (Computer Vision-based Driver Assistance System, CVDAS)、電腦視覺為基礎之交通監控系統 (Computer Vision-based Traffic Monitoring System, CVTMS)以及用路人。上述二系統將利用電腦視覺及影像處理技術達到資訊取得之目的，並驗證其效能及可行性。
本研究所發展之行車安全輔助系統主要利用架設於車上之CCD (Charge Couple Device, 光電耦合元件) 攝影機取得行車前方影像，再運用電腦視覺及影像處理技術，於一般公路系統中識別行車環境。系統運作主要包含兩個步驟，依序為車道線偵測 (lane detection) 以及前方多車偵測 (multiple vehicle detection)。首先，透過車道線偵測可取得車輛與車道線之相對關係及構建空間資訊，並有效利用 濾波器推估行車軌跡。之後，利用已取得之道路空間資訊，進而有效偵測前方行駛車輛，並取得其相對位置資訊。本研究結果顯示，車道線偵測可有效取得行車軌跡線，且車輛偵測的平均成必v可達97%以上。
本研究所發展之交通監控系統，乃利用架設於路側之CCD攝影機擷取車流影像並進行影像處理，其主要包含五步驟： (1) 前處理，(2)前景取出，(3) 陰影消除，(4)車輛追蹤，(5)交通參數之取得。於前處理中，採用自動或手動車道線偵測弁遄A對攝影機進行自動校正並構建空間資訊。系統運作時，在可視範圍內之移動車輛會被視為前景而取出，並同時進行陰影去除。於車輛追蹤時，本系統採用 濾波器加強車輛追蹤之強健性。最後，車流基本參數即可取得。根據實驗結果顯示，車輛追蹤及偵測區域車流量之偵測成必v高於96%。本研究結果證實，CCD攝影機搭配影像處理技術可以成巨

關鍵字

交通監控系統 ； 電腦視覺 ； 行車駕駛輔助系統 ； 車輛偵測 ； 車道線偵測

並列摘要

This study presents a conceptual architecture of computer vision based highway safety architecture that consists of three parts: Computer Vision-based Driver Assistance System (CVDAS), Computer Vision-based Traffic Monitoring System (CVTMS) and road users. In this study, CVTMS and CVDAS are developed and validated, respectively.
The CVDAS developed in this study is mainly to identify the driving environment for autonomous highway vehicles by employing image processing and computer vision techniques. The proposed approach is composed of two consecutive computational steps. The first step is the lane markings detection, used to identify the location of the equipped vehicle and road geometry. The driving trajectory of the equipped vehicle is estimated by a filter. The second step is the multiple vehicle detection that can provide relative position and speed between the equipped vehicle and its preceding vehicle. The experimental results revealed that the success rate of vehicle detection is higher than 97%.
The CVTMS developed in this study is mainly composed of five stages: (1) pre-processing, (2) foreground segmentation, (3) shadow removal, (4) tracking and (5) traffic parameters extraction. The pre-processing is developed to obtain the information of road geometry and calibrate the camera. After the preprocessing is done, the foreground segmentation and shadow removal continue to segment the moving vehicles from the input images. To make the system more robust, a filter is used in the multi-vehicle tracking. Subsequently, the traffic parameters are extracted at the end of each tracking. According to the results, the average success rate of vehicle counting is higher than 96 %. Moreover, it shows that this system is capable of successfully extracting the traffic parameters, including trajectory of the moving vehicle based on the image sequences captured by a CCD (Charge Couple Device) camera.

並列關鍵字

Traffic Monitoring System ； Computer Vision ； Driver Assistance System ； Lane Markings Detection ； Vehicle Detection

參考文獻

Malik, J., S. Russell, J. Weber, T. Huang, "A Machine Vision Based Surveillance System for California Roads," MOU-083 Final Report, November 1994.

Yen, P.S., "Motion Analysis of nearby Vehicles on a Freeway," Master thesis, Department of Information & Computer Education, National Taiwan Normal University, 2003.

Bas, E. K. and J.D. Crisman, “An Easy to Install Camera Calibration For Traffic Monitoring,” IEEE Conference on Intelligent Transportation System,pp.362-366, 1997.

Bensrhair, A., Bertozzi, M., Broggi, A., Miche, P., Mousset, S., Toulminet, G., "A cooperative approach to vision-based vehicle detection," Intelligent Transportation Systems, 2001. Proceedings. 2001 IEEE, 25-29 Aug. 2001, Pages: 207 – 212.

Berka, Stanislaw and B. Kent Lall, "New Perspectives for ATMS: Advanced Technologies in Traffic Detection," Journal of Transportation Engineering, Vol. 124, No. 1, January/February 1998, pp. 9-15.