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Traffic State Recognition of Intersection Based on Image Model and PCA Hashing
المؤلفون المشاركون
المصدر
Journal of Advanced Transportation
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-15
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
The premise of implementing an effective traffic control strategy is the accurate traffic state recognition.
In the existing study, traffic state recognition methods were processed by using statistical characteristics and long-term scale detection of field traffic data.
Hence, the dynamic characteristics and subtle changes in traffic flow were easy to overlook.
At present, more and more advanced traffic detection technology provides reliable and accurate data for measuring and distinguishing the state of urban road traffic, such as the cooperative vehicle-infrastructure system, wide-area radar technology, and 5G technology.
This study proposes a novel method called HTSI (High Precision Traffic State Identification Method), which is based on the advanced detection technology in traffic state recognition at the intersection: The raw data used for intersection traffic state recognition is high-precision detection data of tracking characteristics, which make the data look like a picture of the intersection at God’s perspective.
To this end, we construct an image model for intersections and implement image feature extraction in a way that is different from traditional image processing.
Then, the traffic state recognition problem at the intersection is translated into an image searching problem with tags.
The image searching is realized by the hashing algorithm.
Finally, the comprehensive experiments prove that the proposed method is more accurate and finer than other methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Li-li& Wang, Li& Zhao, Qi. 2020. Traffic State Recognition of Intersection Based on Image Model and PCA Hashing. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1175561
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Li-li…[et al.]. Traffic State Recognition of Intersection Based on Image Model and PCA Hashing. Journal of Advanced Transportation No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1175561
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Li-li& Wang, Li& Zhao, Qi. Traffic State Recognition of Intersection Based on Image Model and PCA Hashing. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1175561
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1175561
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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