Optimization of space elements in high-speed railway hubs based on passenger activity chains of whole travel process and multi-scenario simulation

With growing passenger travel demand, the issues of inadequate spatial efficiency and limited facility service capacity of China’s high-speed rail (HSR) hubs have become more noticeable. The complexity of passenger behavior further complicates the optimization of spatial elements. Therefore, it is necessary to propose and evaluate optimization strategies using quantitative models to improve the spatial usage efficiency and facility service level of hubs. First, this study developed a passenger activity chain choice model based on the multinomial logit model to analyze the activity characteristics and choice preferences of passengers entering and exiting a station. Second, AnyLogic software was employed to conduct passenger flow simulations and spatial analyses under three typical scenarios: off-peak period, peak period, and emergency events, revealing key areas and vulnerable spaces at Chengdu East Railway Station. Targeted strategies were proposed for pedestrian, facility service, commercial, and connection spaces. Simulation results showed that the optimization scheme effectively reduced passenger flow density and facility queue lengths during the peak period while improving transfer efficiency. Safety, fluency, and efficiency indices increased by 17.51%, 50.44%, and 22.49%, respectively. Overall, this strategy significantly enhanced hub performance, offering a theoretical framework and technical pathway for the refined design and management of HSR hubs.