Aiming at the dual predicament of the ‘last mile’ pain point in urban logistics distribution and the insufficient utilization of rail resources, combined with the road traffic congestion problem caused by the dense population in commercial and residential areas, as well as the significant temporal and spatial uneven distribution characteristics of metro passenger transport, a three-dimensional urban logistics optimization scheme of coordinated transportation by road and urban rail is proposed. By integrating the underground idle space and the transportation capacity during the off-peak hours of the subway, a two-stage optimization model for the location and route of the urban logistics network based on the collaboration of subway and freight cars is constructed. The first stage focuses on the layout and resource allocation optimization of subway freight transfer stations, and the second stage designs the collaborative distribution routes of subway and freight cars based on the existing lines. Considering the particularity of rail transportation, constraints such as customer service time Windows, remaining metro transportation capacity, and vehicle capacity are set. With the goal of minimizing the total cost and in combination with the characteristics of the model, a two-stage hybrid solution algorithm integrating adaptive genetic algorithm and improved ant colony algorithm is designed. Finally, the validity of the model and algorithm is verified by taking the goods distribution in the central urban area of Chongqing as an example. The results show that, compared with the traditional distribution scheme, this model can significantly shorten the distribution distance by 56.35% and reduce the network operation cost by 30.21%, which is of positive significance for alleviating the problems of urban logistics transportation.