Blocking time reduction for level crossings using the genetic algorithm

Abstract

The blocking time of a level crossing influences traffic on a road that crosses a rail line. The blocking time of a level crossing will be especially long on a heavy traffic rail line. The purpose of this paper is to reduce the blocking time of level crossings by optimising the railroad schedule. We propose an optimal schedule in which the departure time at each station is delayed minutely from the time of the planned schedule. Since there are many trains on a heavy traffic rail line, the number of combinations of minutely adjusted departure times will be enormous. We used the genetic algorithm (GA) for searching for an optimal railroad schedule. The delay time for each train at each station is used as a gene value, and a chromosome is composed by connecting the genes for each train. The fitness value is the total blocking time of all level crossings on the model rail line. Results for the computer simulation show that our optimal railroad schedule gives a shorter total blocking time compared with the planned schedule. In addition, we report our examination of a composition of the GA calculation with a grid computing technology for the purpose of reducing the GA operation time

Demonstration of Smart Railway Level Crossing Design and Validation Using Data from Metro Rail, South Africa

“…e optimal schedule was calculated from a genetic algorithm using time delay for each train at each station as a gene value and the closing time as the fitness value. us, the study confirmed the reduction of the railway level crossing blocking time with the changing combinations of the departure time [19]. Moreover, the study concluded that the rail-road waiting time can be reduced through the application of the genetic algorithm on the calculation of the schedule, taking into account the train's location and speed [20].…”