Redesigning urban intermodal transit for passenger and freight co-modal mobility

Metro line planning with integrated truck routing

Journal Article (2026)
Author(s)

Yahan Lu (TU Delft - Civil Engineering & Geosciences)

Yuwen Peng (Student TU Delft)

Dongyang Xia (TU Delft - Civil Engineering & Geosciences)

Patrick Stokkink (TU Delft - Technology, Policy and Management)

Shadi Sharif Azadeh (TU Delft - Civil Engineering & Geosciences)

Research Group
Transport, Mobility and Logistics
DOI related publication
https://doi.org/10.1016/j.trb.2026.103538 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Transport, Mobility and Logistics
Journal title
Transportation Research Part B: Methodological
Volume number
211
Article number
103538
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Abstract

Urban transportation systems are under increasing pressure to efficiently accommodate both passenger and freight mobility within limited infrastructure and operational budgets. Operators face growing pressure to make more efficient use of existing infrastructure due to economic and environmental constraints. In this regard, we investigate the capacitated line planning problem with integrated truck routing for passenger and freight co-modal mobility in an intermodal network composed of an urban rail transit (URT) system and road-based truck services. Different from existing research that either focuses on passenger-oriented line planning in a single-modal network or optimizes tactical- and operational-level decisions for passenger and freight co-modal mobility based on fixed line plans, we consider a strategic-level problem where urban planners aim to fundamentally re-optimize the allocation of existing infrastructure resources and budget across the intermodal network. We formulate this problem as a path-based mixed-integer linear programming model. The model determines line plans and frequency for both URT and truck services, as well as the passenger and freight routing, with the aim of optimizing the total weighted travel time of passengers and freight. To solve large-scale instances, we develop a column generation algorithm with a two-phase diving procedure. Our algorithm incorporates acceleration techniques and budget reservation strategies derived from the mathematical properties of the formulation. We evaluate our approaches on both artificial instances and real-world case studies from the Rotterdam intermodal network. The results show that our algorithm obtains solutions with an average optimality gap of 0.77%, while reducing computation time by 95.53% compared to GUROBI. Using the existing Rotterdam URT line plan with optimized frequencies as a benchmark, we demonstrate that our approach improves service quality by 6.50% without increasing operational costs. From a practical perspective, real-life case studies suggest that accommodating the passenger and freight co-modal mobility in existing passenger-oriented metro systems requires redesigning the line plan from scratch, rather than merely adjusting frequencies or incrementally expanding the current network. The results further indicate that effective freight integration depends on reallocating budget across modes, with URT serving as the backbone of the intermodal system and truck services providing a complementary function.