To adapt to the travel needs of urban agglomeration passengers and maximize the overall benefits of the system

a problem of collaborative range and collaborative route optimization selection of urban agglomerations was proposed based on the marginal benefit theory. A super network model of multi-mode and multi-link traffic system in urban agglomerations was constructed

and factors such as the correlation strength of passenger flow and transfer facilities were considered to generate a collaborative route candidate set. The routes of the super network were divided into on-going sections and transfer sections

and the generalized travel cost of the multi-mode travel routes was established. The route choice behaviors of passengers in urban agglomerations were constructed by using three-tier nested Logit model. On this basis

a bi-level programming model was established with the optimization objective of maximizing social welfare. Genetic algorithm and successive averaging method were used to solve the upper and lower models and the collaborative transportation range and collaborative routes were determined based on the theory of diminishing marginal benefits. Finally

the Beijing-Tianjin-Hebei Urban Agglomeration was taken as an example to illustrate the performance and application of the model. Results show that there was marginal benefit in the scale of collaborative transportation routes

and the optimized collaborative routes could basically meet the travel demand of Beijing-Tianjin-Hebei Urban Agglomeration. It provides reference and theoretical guidance for the implementation of collaborative operation of multi-mode transport in urban agglomerations in China.