Reference:
Y. Wang,
B. De Schutter,
B. Ning,
N. Groot, and
T.J.J. van den Boom,
"Optimal trajectory planning for trains using mixed integer linear
programming," Proceedings of the 14th International IEEE
Conference on Intelligent Transportation Systems (ITSC 2011),
Washington, DC, pp. 1598-1603, Oct. 2011.
Abstract:
The optimal trajectory planning for trains under constraints and fixed
maximal arrival time is considered. The variable line resistance
(including variable grade profile, tunnels, and curves) and arbitrary
speed restrictions are included in this approach. The objective
function is a trade-off between the energy consumption and the riding
comfort. First, the nonlinear train model is approximated by a
piece-wise affine model. Next, the optimal control problem is
formulated as a mixed integer linear programming (MILP) problem, which
can be solved efficiently by existing solvers. The good performance of
this approach is demonstrated via a case study.