武汉理工大学毕业论文（设计）
外文翻译
原文1
Research on key technologies of intelligent transportation based on image recognition and anti-fatigue driving
Jun Wang, Xiaoping Yu, Qiang Liu, and Zhou Yang
Abstract: Intelligent transportation system needs to solve the main problems in traffic safety. This paper focuses on the traffic safety caused by fatigue driving based on image recognition of key technologies for research and analysis. This paper proposes that the location of face and facial feature points and the classification of fatigue detection are the key links to determine the fatigue driving detection rate. In the analysis of face localization algorithm based on skin color modeling, a corner-based optimization method is proposed to optimize the face region. Based on the analysis of the binary algorithm of human eye localization algorithm, a bi-directional integral projection method is proposed to achieve accurate human eye localization. Then the commonly used fatigue classification algorithm (KNN algorithm) is analyzed. Finally, the proposed method is verified by the simulation test of fatigue driving. Experimental results show that the algorithm based on skin color modeling can accurately locate the driverrsquo;s face region. The eye location algorithm based on the two-valued algorithm can also locate the eye location of the tester accurately. The accuracy of KNN fatigue detection model is 87.82%. It can identify driverrsquo;s fatigue state with high accuracy.
KEY WORDS: Image recognition, Fatigue driving, Intelligent traffic
1 Introduction
At the same time of large-scale urban expansion, the reform of infrastructure construction and management mode is relatively lagging behind, resulting in “urban disease” becoming more and more serious. The explosive growth of urban population and the rapid increase of the number of vehicles in the city have led to urban traffic obstacles and development bottlenecks. The main obstacles and problems are as follows [1]: serious urban traffic congestion, resulting in increased travel time and consumption of large amounts of energy, serious traffic safety problems, and frequent accidents; noise pollution and air pollution are becoming increasingly serious. Traffic safety is one of the main problems in the development of urban transportation, and it needs to be solved in time [2]. In the global human casualty accidents, traffic casualties are one of the main causes of human casualties. Statistics show that in 2016, 86.443 million traffic accidents occurred in China, resulting in 63,093 deaths and 1.21 billion yuan of direct property losses [3] ; in May 2017, traffic network data show that 787 traffic accidents occurred in Huairsquo;an section of Beijing-Shanghai Expressway in 2016, including 414 traffic accidents caused by fatigue driving, and it accounts for about 52.6% of the total accident. Thus, fatigue driving is the main cause of major traffic accidents, so real-time monitoring of driver fatigue state has important practical significance in reducing traffic accidents and casualties.
In order to solve the problem of traffic safety, many countries in the world have given comprehensive consideration to the driving process, vehicle scheduling, and the overall control safety of vehicle operation. Intelligent transportation system (ITS) [4] emerged and developed continuously. Intelligent transportation system (ITS) makes full use of Internet of Things, cloud computing, Internet, artificial intelligence, automatic control, mobile Internet, and other technologies in the field of transportation. It collects traffic information through high tech and manages traffic, transportation, public travel, and other traffic areas in all aspects as well as the entire process of traffic construction and management to support the management, so that the transport system in the region, the city, and even a larger space-time range with the perception, interconnection, analysis, prediction, control, and other capabilities could fully protect traffic safety, play the effectiveness of transport infrastructure, and enhance transportation system operation efficiency and management level, for smooth public travel and sustainable economic development services. At present, the intelligent transportation system has also been widely applied. For example, [5] the intelligent traffic prediction system (ITPS) in Singapore consists of a computerized traffic signal system, an electronic scanning system, a city expressway monitoring system, a joint electronic eye, and a road pricing system to predict traffic flow over a predetermined period of time. It can help traffic controllers to predict traffic flow and prevent traffic congestion. Stockholm, Sweden, has introduced a new intelligent toll system, which reduces traffic by 22% and emissions by 12 to 40%. The goal of intelligent transportation system is to improve transportation efficiency, ease traffic congestion, improve the capacity of road network, and reduce traffic accidents through the harmony and close cooperation of people, vehicles, and roads. At present, there are many researches on intelligent transportation system. For example, Zhang [6] and others analyzed the architecture of intelligent transportation system and gave the overall framework, system functions, database structure, and the best path analysis method of Luoyang intelligent transportation system. Xie [7] and others put forward an intelligent urban traffic system based on the Internet of Things, which uses the technology of group intelligence perception to realize information collection and uses radio and television technology, mobile phone technology, and vehicle netw
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