Optimizing integrated passenger and freight transport in demand-responsive transit systems with meeting points

Urban transportation systems face persistent inefficiencies, characterized by underutilized public transit capacity during off-peak hours and heightened congestion from freight deliveries during peak periods. To address these dual challenges, we propose an integrated passenger-freight transport framework that leverages a demand-responsive transit system with meeting points. We formulate a joint optimization model to coordinate passenger trips and parcel deliveries within dynamically shared vehicle capacity. The modelos accuracy and computational characteristics are first validated on a small-scale case using the Gurobi solver. A heuristic algorithm was subsequently developed to solve larger-scale, practical instances. Numerical experiments across heterogeneous demand patterns demonstrate that compared with pure transportation operations, incorporating meeting points consistently enhances service quality, although profitability remains highly scenario dependent. In the Passenger PeakɃFreight Uniform scenario, the analysis further revealed a significant interaction effect between the time sensitivity coefficient and the meeting point matching radius. These results confirm the feasibility of the proposed integrated scheduling approach for passenger-freight DRT services and underscore its potential to improve urban mobility and logistics efficiency while optimizing resource utilization.