Evolutionary method for railway monitoring systems

The paper presents an evolutionary method based on genetic programming (GP) for synthesizing of a monitor alarm system for the railway control traffic unit. Automatic supervision of railway traffic control is a very important and complex task. A wrong control signal can lead to very serious incidents or accidents. A well-designed monitoring system can prevent these accidents by a simple alarm which signals the appearance of a wrong control signal. The railway network or the plant is modeled by Delay Time Petri Nets (DTPN) and the railway traffic control unit by Time Petri Nets (TPN). The alarm monitor contains transitions joined to the plant and control unit in order to achieve the information on the positions of trains, respectively the control signals of the control unit, and generates an alarm whenever the control signal can cause to an incident or accident. The TPN model of the monitor system is generated by means of the genetic programming method using a Lisp representation of the solution.