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 (PNLP), 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 (PPWA). 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 (PTSPO) 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 (PTSPO) 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.
Keywords
Real-time traffic management,   Train control,   Integrated
optimization,   Delay recovery,   Mixed
integer linear programming (MILP)
Highlights
• We address the integration of real-time traffic management and train control by using
optimization methods.
•
We propose three optimization models to construct the real-time train timetable in a way
of optimizing the train accelerating and braking actions.
•
We demonstrate the good performance of the proposed approaches and investigate the
benefits of the integration.
•
A 8% reduction of train delay can be achieved by using the proposed method, compared
with the solution neglecting train dynamics.
原文传递: https:/www.sciencedirect.com/science/article/pii/S0191261517305933