In order to improve the efficiency of urban planning and design and reduce the construction waste caused by inefficient design schemes, this paper proposes an application method of environmental protection building elements based on artificial intelligence technology in the field of urban planning and design. This model enables agents to learn how to interact with the environment with appropriate strategies, so as to generate the road network design scheme required by users. In order to better control the generation of the result scheme, this paper designs the rules and feedback of the agent. Among them, rules restrict the behavior of agents to avoid design schemes that do not meet the road design specifications. Feedback determines the values followed by agents, that is, the direction of agent strategy optimization. The experimental results show that after 4×105 iterations of the training process, the model is derived and used to generate 10000 plot road network schemes, the mean and variance of key indicators are calculated, and the scores of 153 plots with similar area and shape and the same land function in the same indicators from the real case base are calculated. From the performance of these indicators, it can be seen that the performance of the road network generated by the model is similar to that of the real road network in terms of traffic performance. Conclusion. the model completely retains the structural geographic information inside the plot, and the generated results can be directly applied to mainstream urban design software through data format conversion.