Real-time and dynamic multi-intersection path navigation quantum searching method of urban transportation road network

Abstract

The invention discloses a real-time and dynamic multi-intersection path navigation quantum searching method of an urban transportation road network. A preference value generated by influences on routes of roads and a cost value generated by mutual influences in a running process of vehicles are combined to form a comprehensive evaluation index effective value; whether route navigation schemes are good or not is evaluated by utilizing the size of the effective value, and effective values of all the route navigation schemes are computed in parallel by utilizing quantum computation; the route navigation schemes meeting the requirements are efficiently found by utilizing quantum searching. The real-time and dynamic multi-intersection path navigation quantum searching method sufficiently considers various factors capable of influencing the smoothness of the roads, and influence degrees on the transportation by the various factors are quantitated and are finally integrated to obtain the effective value and whether the route navigation schemes are good or not is accurately evaluated by utilizing the effective value. Meanwhile, the quantum computation and the quantum searching are introduced so that a computation result of the effective value can be obtained in real time and the suitable route navigation schemes are obtained; under the condition that personal interests of each driver are met, traffic jam of the urban road network is improved obviously.

Description

technical field [0001] The invention belongs to the technical fields of computer science and intelligent traffic systems, and in particular relates to a quantum search method for real-time dynamic multi-intersection path navigation in urban traffic road networks. Background technique [0002] The traffic network of large and medium-sized cities is increasingly congested, and the time cost, management cost and economic cost caused by congestion are increasing. Traffic congestion increases the travel time of residents, affects people's work efficiency and quality of life, and restricts urban development. It reduces energy consumption and exhaust emissions, aggravates environmental pollution, and solves the congestion problem of urban traffic network, which is beneficial to the country and the people. However, the pattern of urban traffic road network has been hard to change, and road resources are limited. Efficient route navigation and reasonable road resource allocation have...

AI Technical Summary

Problems solved by technology

Although with the vigorous development of the network, it is not difficult to provide real-time route navigation information for vehicles, but the simple dynamic real-time predictive flow model limits the accuracy of the real-time predictive model, resulting in a relatively low ability to deal with real-time traffic emergencies. However, complex dynamic real-time forecasting models consider many factors, and the computational complexity increases exponentially with the increase of road network scale. Therefore, the current dynamic route navigation is not yet mature, and most of them remain in the theoretical stage.

The contradiction between the accuracy and complexity of dynamic real-time prediction models limits the development of dynamic route navigation

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