A Design & Optimization Method for Intercity Demand-responsive Transit Considering Passengers' Choice Behavior

Demand-responsive transit is an emerging reservation-based travel service. However, existing studies have mainly focused on intracity context, while studies on service design and optimization in intercity context re-main limited. Meanwhile, current models typically pursue a single operator-oriented objective, such as operational cost minimization or profit maximization, but rarely incorporate operation profits and consumer surplus, thereby lim-iting their ability to enhance overall social welfare. Additionally, most studies assume fixed demand density and fail to adequately involve passengers'choice preferences. To address these shortcomings, this study incorporates passen-gers'choice behavior and develops a design & optimization model for intercity demand-responsive transit (IDRT) service. The objective of this model is maximizing social welfare, which is defined as the sum of operation profits and consumer surplus. The decision variables include departure interval, service-area ratio between the major city and satellite cities, and ticket fare. The model is formulated using the continuous approximation method and solved with the Lagrange multiplier method. Furthermore, the optimal solutions of models with social welfare maximiza-tion and operation profit maximization are compared. Results show that although operation profit is negative in the model of social welfare maximization, an appropriate subsidy can raise social welfare from 54.976 CNY/h to 110.906 CNY/h, demonstrating the effectiveness of the proposed method. The results of the sensitivity analysis on se-lected model parameters indicate that the service area of satellite cities has only a minor impact on social welfare and is not a key constraint in IDRT layout, whereas length of intercity highway has a significant influence on passen-gers'choice behavior, highlighting the importance of empirical surveys for rational deployment of IDRT layout. Over-all, the proposed method not only provides decision-makers with a practical tool to determine departure intervals, ser-vice-area allocation, and ticket fares given demand density conditions, but also assists them in selecting appropriate vehicle types based on sensitivity analysis, thereby improving both operational efficiency and social welfare.