**Reference:**

X. Luan,
Y. Wang,
B. De Schutter,
L. Meng,
G. Lodewijks, and
F. Corman,
"Integration of real-time traffic management and train control for
rail networks - Part 1: Optimization problems and solution
approaches," *Transportation Research Part B*, vol. 115, pp.
41-71, Sept. 2018.

**Abstract:**

We study the integration of real-time traffic management and train
control by using mixed-integer nonlinear programming (MINLP) and
mixed-integer linear programming (MILP) approaches. Three innovative
integrated optimization approaches for real-time traffic management
that inherently include train control are developed to deliver both a
train dispatching solution (including train routes, orders, departure
and arrival times at passing stations) and a train control solution
(i.e., train speed trajectories). Train speed is considered variable,
and the blocking time of a train on a block section dynamically
depends on its real speed. To formulate the integrated problem, we
first propose an MINLP problem (P_{NLP}), which is
solved by a two-level approach. This MINLP problem is then
reformulated by approximating the nonlinear terms with piecewise
affine functions, resulting in an MILP problem
(P_{PWA}). Moreover, we consider a preprocessing
method to generate the possible speed profile options for each train
on each block section, one of which is further selected by a proposed
MILP problem (P_{TSPO}) with respect to safety,
capacity, and speed consistency constraints. This problem is solved by
means of a custom-designed two-step approach, in order to speed up the
solving procedure. Numerical experiments are conducted using data from
the Dutch railway network to comparatively evaluate the effectiveness
and efficiency of the three proposed approaches with heterogeneous
traffic. According to the experimental results, the MILP approach
(P_{TSPO}) yields the best overall performance
within the required computation time. The experimental results
demonstrate the benefits of the integration, i.e., train delays can be
reduced by managing train speed.

Online version of the paper

Corresponding technical report: pdf file (3.82 MB)

@article{LuaCor:18-012,

author={X. Luan and Y. Wang and B. {D}e Schutter and L. Meng and G. Lodewijks and F. Corman},

title={Integration of real-time traffic management and train control for rail networks -- {Part} 1: {Optimization} problems and solution approaches},

journal={Transportation Research Part B},

volume={115},

pages={41--71},

month=sep,

year={2018},

doi={10.1016/j.trb.2018.06.006}

}

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