Talk about how artificial intelligence can enable intelligent transportation
this article reprints self express information. The original title is "significance for development". Yiou smart city will review the article twice for readers' reference
with the progress of the times and the continuous development of various technologies, great changes have taken place in our daily life. The wide promotion and application of big data technology and artificial intelligence technology have made our life more convenient and fast. On this basis, the creation of intelligent traffic management mode can effectively solve the current traffic congestion problem in China, and enable the standardized development of China's transportation field, Improve the efficiency of traffic management
wireless sensing technology and artificial intelligence recognition technology are the main ways of object perception and identification, and they are also the basic technical conditions for the construction of intelligent transportation. Intelligent identification is the unique two-dimensional code or bar code and other identification tags that can represent the identity of the object. The unique location information and characteristics are recorded in the relevant electronic tags. Then these information can be accurately identified through artificial intelligence devices, and then the read information can be uploaded to the control system center for analysis and decision-making. Wireless sensor network is mainly to set up a large number of micro sensors in the monitoring target area and form a comprehensive monitoring network. The information exchange between various nodes is mainly through the wireless network. Its main outstanding advantages are convenient deployment, low-cost operation and flexible layout. Sensors in intelligent transportation mainly include two parts: nodes and acquisition nodes, whether in terms of capital investment or technical indicators. For example, each individual collection point is actually a small information processing system, which can automatically collect the data information in the responsible area, and then uniformly transmit the collected information to other nodes, or to the node convergence center, which then sends the comprehensive information to the processing center for unified processing
wisdom needs to strengthen supply side management. At present, each module in the transportation system is still in a state of independent operation and information separation, which cannot promote the effective connection between various data information, resulting in serious data waste. Smart transportation cloud is a management technology that integrates cloud computing with the field of transportation services. At the same time, it also has the advantages of unified resource analysis, information security and massive information storage in cloud computing, providing an effective channel for data management and sharing of urban transportation. Cloud computing actually refers to the concentration of a large number of high-speed computers in the network, so as to form a large virtual resource management place, which can provide storage and analysis computing services for remote network end users. Users can rent cloud computing services provided by service providers without purchasing various independent hardware. Similar to cloud services, cloud services in intelligent transportation can be divided into software services, platform services and infrastructure services. Cloud processing platform is also the main research direction of intelligent transportation. It can analyze, calculate and store massive data, so as to reduce the pressure of real-time data storage and improve the development potential
the data information in intelligent transportation has the characteristics of heterogeneity, diversity and magnanimity, which increases the difficulty of data information processing, ranging from the data collection of vehicles and various traffic facilities to the complex work, such as the detection and judgment in traffic events, which is inseparable from the data processing work. Common processing technologies in intelligent transportation include data visualization, data activation, data mining, data fusion and other technologies. In addition, data should be selectively uploaded to maintain personal privacy. Data fusion also involves data processing technology in many fields such as decision-making, communication and artificial intelligence. It can comprehensively detect multi-source information from three perspectives: decision-making layer, feature layer and data layer according to the cost state of vanadium battery. Because the process of data fusion also involves a large number of sensors and information acquisition work, before the formal fusion work, we should also preprocess the relevant data space and data time. By aligning the space and time, we can effectively avoid the confusion of data management and promote the effective improvement of data reliability and consistency
a major problem in the process of modern urban development is traffic congestion. To completely solve this stubborn disease in urban development, we need to build an intelligent transportation system in the city with the support of modern high-tech technology, and thoroughly solve the problem of urban congestion from the source. The intelligent transportation system involves a variety of advanced technologies such as cloud computing, big data and artificial intelligence technology. It makes full use of various transportation resources, promotes the effective reduction of transportation costs, and enables the smooth development of the transportation field
the intelligent control system also includes several important parts, such as instant feedback, centralized command, cloud processing and information collection [1]. Taxi drivers, urban traffic police and video monitoring system in the city are the main sources of information collection. The collected information and data are transmitted to the urban command center in time, and then the relevant computer system conducts centralized analysis of the big data, and formulates the optimization plan of urban traffic, which is fed back to the relevant management personnel and traffic facilities to make their physical characteristics more different from the metal, So as to control the urban traffic intelligently. For example, the traffic light system, an important component of urban traffic, changes its traditional operation mode according to a fixed time, which is easy to lead to serious traffic congestion and other problems in a certain direction. However, under the management and control of the intelligent transportation system, it can conduct intelligent analysis on the road sections in the same direction in combination with the collected vehicle speed, number, distribution density and other factors, and then combine the corresponding analysis results, Scientific regulation of traffic light conversion can promote the effective reduction of vehicle waiting time
the urban transportation system consists of light rail, subway, taxi, tram, bus and other parts, and the above-mentioned modes of transportation have separate management institutions, which belong to different departments, and are in a state of split operation, which reduces the transfer efficiency between different modes of transportation, resulting in poor coordination and cooperation between various modes of transportation, It will have a certain adverse impact on the overall transportation capacity. Therefore, effective measures should be taken to solve it in time. Based on the intelligent dispatching system, the overall traffic operation status of the city should be scientifically planned, so that various transportation modes can be effectively coordinated, and the effective connection of various transportation links can be promoted to form a good traffic network, so that passengers can travel conveniently and promote the overall improvement of traffic efficiency, Reduce the no-load rate and promote the full utilization of urban traffic resources
private cars play an important role in the urban transportation system. Compared with the public transportation in the city, private cars have the characteristics of liberalization, personalization and decentralization in daily traffic. The role of intelligent transportation can be mainly reflected in the guidance and services for private cars, such as timely transmission of traffic information and road traffic conditions for private cars through electronic navigation, road display, City radio and other tools, guiding private cars to effectively avoid traffic congestion areas in the city, helping private cars plan travel routes scientifically, and designing corresponding parking management modules for parking problems in the city, The data and information of some public parking areas are included in the urban traffic management system, so that private cars can find spare parking spaces according to relevant app software, so as to promote the efficient use of parking resources
through the intelligent warning system, we can further improve the public's concept of civilized travel, and effectively punish those illegal behaviors in urban traffic, such as climbing over guardrails, retrograde vehicles, running red lights, and violating guidance. On the basis of artificial intelligence recognition technologies such as face recognition and vehicle number recognition, the relevant information systems in the public security institutions can be used to accurately locate them, so as to transmit specific warning information to the violators, or use the public display screen in the city to expose specific violators, so that the traffic police can investigate their laws. With scientific and technological support and information paving, smart cities are mainly built on a variety of advanced high technologies. Therefore, we should make full use of various technologies, including data communication systems, computer processing systems, data acquisition systems, etc. at the same time, we should also pay attention to the rational use of artificial intelligence technology
LINK
Copyright © 2011 JIN SHI