This paper takes Wuhan’s traffic signs as the research object,and collects the Chinese and English traffic signs in large quantities to build a small corpus.According to the text type theory proposed by German functi...This paper takes Wuhan’s traffic signs as the research object,and collects the Chinese and English traffic signs in large quantities to build a small corpus.According to the text type theory proposed by German functionalist school Katarina Rice,in this article the traffic signs are classified into three categories:information type text identifier,expression type text identifier and opera⁃tion type text identifier according to six functions including indication,prompt,restriction,compulsory,persuasion and publicity.It attempts to reveal the characteristics of Chinese signs and English translations of different text types,and to explore the translation and semantic rhyme of the word"forbidden"in the English translation of high-frequency vocabulary in traffic signs.It aims to pro⁃vide reference for the English translation of traffic signs,create a good language environment,shape a good city image,and increase the degree of China's internationalization.展开更多
The correct identification of traffic signs plays an important role in automatic driving technology and road safety driving.Therefore,to address the problems of misdetection and omission in traffic sign detection due ...The correct identification of traffic signs plays an important role in automatic driving technology and road safety driving.Therefore,to address the problems of misdetection and omission in traffic sign detection due to the variety of sign types,significant size differences and complex background information,an improved traffic sign detection model for RT-DETR was proposed in this study.Firstly,the HiLo attention mechanism was added to the Attention-based Intra-scale Feature Interaction,which further enhanced the feature extraction capability of the network and improved the detection efficiency on high-resolution images.Secondly,the CAFMFusion feature fusion mechanism was designed,which enabled the network to pay attention to the features in different regions in each channel.Based on this,the model could better capture the remote dependencies and neighborhood feature correlation,improving the feature fusion capability of the model.Finally,the MPDIoU was used as the loss function of the improved model to achieve faster convergence and more accurate regression results.The experimental results on the TT100k-2021 traffic sign dataset showed that the improved model achieves the performance with a precision value of 90.2%,recall value of 88.1%and mAP@0.5 value of 91.6%,which are 4.6%,5.8%,and 4.4%better than the original RT-DETR model respectively.The model effectively improves the problem of poor traffic sign detection and has greater practical value.展开更多
An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation d...An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation duration, variations of fixation points, and the distribution of glance zone. It was found that driving experience had a significant effect on driver eye movement behavior. The percentage of fixation duration to total glance time for inexperienced drivers was 61.5%, while the percentage for experienced drivers was 50.2%. Moreover, the majority of drivers paid attention to the left region of the field of view more frequently than the central and the right regions. This study indicates that it takes inexperienced drivers more time to recognize traffic signs. The findings from this study will assist traffic engineers in designing and installing the traffic signs in an optimal way.展开更多
Recognizing various traffic signs,especially the popular circular traffic signs,is an essential task for implementing advanced driver assistance system.To recognize circular traffic signs with high accuracy and robust...Recognizing various traffic signs,especially the popular circular traffic signs,is an essential task for implementing advanced driver assistance system.To recognize circular traffic signs with high accuracy and robustness,a novel approach which uses the so-called improved constrained binary fast radial symmetry（ICBFRS） detector and pseudo-zernike moments based support vector machine（PZM-SVM） classifier is proposed.In the detection stage,the scene image containing the traffic signs will be converted into Lab color space for color segmentation.Then the ICBFRS detector can efficiently capture the position and scale of sign candidates within the scene by detecting the centers of circles.In the classification stage,once the candidates are cropped out of the image,pseudo-zernike moments are adopted to represent the features of extracted pictogram,which are then fed into a support vector machine to classify different traffic signs.Experimental results under different lighting conditions indicate that the proposed method has robust detection effect and high classification accuracy.展开更多
The features extracted by principle component analysis(PCA) are the best descriptive and the features extracted by linear discriminant analysis(LDA) are the most classifiable. In this paper, these two methods are comb...The features extracted by principle component analysis(PCA) are the best descriptive and the features extracted by linear discriminant analysis(LDA) are the most classifiable. In this paper, these two methods are combined and a PC-LDA approach is used to extract the features of traffic signs. After obtaining the binary images of the traffic signs through normalization and binarization, PC-LDA can extract the feature subspace of the traffic sign images with the best description and classification. The extracted features are recognized by using the minimum distance classifier. The approach is verified by using MPEG7 CE Shape-1 Part-B computer shape library and traffic sign image library which includes both standard and natural traffic signs. The results show that under the condition that the traffic sign is in a nature scene, PC-LDA approach applied to binary images in which shape features are extracted can obtain better results.展开更多
文摘This paper takes Wuhan’s traffic signs as the research object,and collects the Chinese and English traffic signs in large quantities to build a small corpus.According to the text type theory proposed by German functionalist school Katarina Rice,in this article the traffic signs are classified into three categories:information type text identifier,expression type text identifier and opera⁃tion type text identifier according to six functions including indication,prompt,restriction,compulsory,persuasion and publicity.It attempts to reveal the characteristics of Chinese signs and English translations of different text types,and to explore the translation and semantic rhyme of the word"forbidden"in the English translation of high-frequency vocabulary in traffic signs.It aims to pro⁃vide reference for the English translation of traffic signs,create a good language environment,shape a good city image,and increase the degree of China's internationalization.
文摘The correct identification of traffic signs plays an important role in automatic driving technology and road safety driving.Therefore,to address the problems of misdetection and omission in traffic sign detection due to the variety of sign types,significant size differences and complex background information,an improved traffic sign detection model for RT-DETR was proposed in this study.Firstly,the HiLo attention mechanism was added to the Attention-based Intra-scale Feature Interaction,which further enhanced the feature extraction capability of the network and improved the detection efficiency on high-resolution images.Secondly,the CAFMFusion feature fusion mechanism was designed,which enabled the network to pay attention to the features in different regions in each channel.Based on this,the model could better capture the remote dependencies and neighborhood feature correlation,improving the feature fusion capability of the model.Finally,the MPDIoU was used as the loss function of the improved model to achieve faster convergence and more accurate regression results.The experimental results on the TT100k-2021 traffic sign dataset showed that the improved model achieves the performance with a precision value of 90.2%,recall value of 88.1%and mAP@0.5 value of 91.6%,which are 4.6%,5.8%,and 4.4%better than the original RT-DETR model respectively.The model effectively improves the problem of poor traffic sign detection and has greater practical value.
文摘An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation duration, variations of fixation points, and the distribution of glance zone. It was found that driving experience had a significant effect on driver eye movement behavior. The percentage of fixation duration to total glance time for inexperienced drivers was 61.5%, while the percentage for experienced drivers was 50.2%. Moreover, the majority of drivers paid attention to the left region of the field of view more frequently than the central and the right regions. This study indicates that it takes inexperienced drivers more time to recognize traffic signs. The findings from this study will assist traffic engineers in designing and installing the traffic signs in an optimal way.
基金Supported by the Program for Changjiang Scholars and Innovative Research Team (2008)Program for New Centoury Excellent Talents in University(NCET-09-0045)+1 种基金the National Nat-ural Science Foundation of China (60773044,61004059)the Natural Science Foundation of Beijing(4101001)
文摘Recognizing various traffic signs,especially the popular circular traffic signs,is an essential task for implementing advanced driver assistance system.To recognize circular traffic signs with high accuracy and robustness,a novel approach which uses the so-called improved constrained binary fast radial symmetry（ICBFRS） detector and pseudo-zernike moments based support vector machine（PZM-SVM） classifier is proposed.In the detection stage,the scene image containing the traffic signs will be converted into Lab color space for color segmentation.Then the ICBFRS detector can efficiently capture the position and scale of sign candidates within the scene by detecting the centers of circles.In the classification stage,once the candidates are cropped out of the image,pseudo-zernike moments are adopted to represent the features of extracted pictogram,which are then fed into a support vector machine to classify different traffic signs.Experimental results under different lighting conditions indicate that the proposed method has robust detection effect and high classification accuracy.
基金Supported by National Natural Science Foundation of China(No.61540069)
文摘The features extracted by principle component analysis(PCA) are the best descriptive and the features extracted by linear discriminant analysis(LDA) are the most classifiable. In this paper, these two methods are combined and a PC-LDA approach is used to extract the features of traffic signs. After obtaining the binary images of the traffic signs through normalization and binarization, PC-LDA can extract the feature subspace of the traffic sign images with the best description and classification. The extracted features are recognized by using the minimum distance classifier. The approach is verified by using MPEG7 CE Shape-1 Part-B computer shape library and traffic sign image library which includes both standard and natural traffic signs. The results show that under the condition that the traffic sign is in a nature scene, PC-LDA approach applied to binary images in which shape features are extracted can obtain better results.
