Traffic pollution control method and system and storage medium

Abstract

The invention discloses a traffic pollution control method and system and a storage medium, and the method comprises the following steps: obtaining original tail gas monitoring data and traffic flow information data, and carrying out the preprocessing; and inputting the processed data into a preset traffic pollution management and control model, and outputting a management and control strategy. Aconstruction method of the traffic pollution management and control model comprises the following steps: collecting exhaust monitoring data and preprocessing the exhaust monitoring data; constructinga traffic pollution reinforcement learning model; and setting a traffic pollution control model strategy algorithm and performing training based on the data processed in the step S201. The long-term return optimal value function is estimated by using the deep Q network to overcome the problem of overlarge action state space, and the time sequence dependence of the exhaust environment system is constructed by using the mixed environment state, so that an effective traffic flow and speed limiting strategy is formulated to reduce traffic pollution.

Description

technical field [0001] The invention relates to the technical field of urban traffic pollution control in the traffic field, in particular to a traffic pollution control method, system and storage medium. Background technique [0002] Carbon monoxide (CO), carbon dioxide (CO 2 ), hydrocarbons (HC), nitrogen oxides (NO x ), and solid particulate matter (PM2.5) seriously endanger public health. With the rapid growth of the number of motor vehicles, urban air pollution is increasing day by day. Therefore, it is necessary to study traffic pollution control methods to provide decision-making support for traffic-related regulatory departments to formulate reasonable flow and speed limit measures. [0003] The current research work on traffic pollution control can be divided into traffic pollution control methods based on model feedback control and traffic pollution control methods based on traffic flow pattern characteristic management. The method based on model feedback contr...

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Problems solved by technology

[0004] A traffic pollution control method, system, and storage medium proposed by the present invention use a deep Q network to estimate the long-term return optimal value function to overcome the problem of excessively large action state space, and design a mixed environment state to construct the timing dependence of the exhaust environment system

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