Real-time Train Driver Rescheduling by Actor-Agent Techniques
Public Transport, 2 (3):
249--268 (2011)DOI: 10.1007/s12469-010-0033-6
Аннотация
Passenger railway operations are based on an extensive planning process
for generating the timetable, the rolling stock circulation, and
the crew duties for train drivers and conductors. In particular,
crew scheduling is a complex process.
After the planning process has been completed, the plans are carried
out in the real-time operations. Preferably, the plans are carried
out as scheduled. However, in case of delays of trains or large disruptions
of the railway system, the timetable, the rolling stock circulation
and the crew duties may not be feasible anymore and must be rescheduled.
This paper presents a method based on multi-agent techniques to solve
the train driver rescheduling problem in case of a large disruption.
It assumes that the timetable and the rolling stock have been rescheduled
already based on an incident scenario. In the crew rescheduling model,
each train driver is represented by a driver-agent. A driver-agent
whose duty has become infeasible by the disruption starts a recursive
task exchange process with the other driver-agents in order to solve
this infeasibility. The task exchange process is supported by a route-analyzer-agent,
which determines whether a proposed task exchange is feasible, conditionally
feasible, or not feasible. The task exchange process is guided by
several cost parameters, and the aim is to find a feasible set of
duties at minimal total cost.
The train driver rescheduling method was tested on several realistic
disruption instances of Netherlands Railways (NS), the main operator
of passenger trains in the Netherlands. In general the rescheduling
method finds an appropriate set of rescheduled duties in a short
amount of time. This research was carried out in close cooperation
by NS and the D-CIS Lab.