Optimization of Automatic Train Control for Energy Management and Service Reliability

Abstract

A new generation of automatic train control systems is currently under development in the commuter-rail transit industry. These systems will utilize radio communication between wayside control computers and trains in order to provide high precision train control beyond the capability of today's automatic systems. The Bay Area Rapid Transit (BART) system is developing such a modern control system in collaboration with Harmon Industries. This system, called the Advanced Automatic Train Control (AATC) system, will allow for precision train locating and control, and will facilitate coordination of the trajectories of multiple trains. This system will be capable of running trains more closely together and decreasing the time a train requires to traverse the system, while simultaneously operating with a more modest traction power infrastructure, and providing a smoother, more comfortable ride to commuters. The authors have collaborated with BART to develop a simulator of the AATC system and the traction power system, and they have utilized this simulator as a testbed for the development of advanced train control techniques. Several train control algorithms, including one employing a neural network for train voltage prediction, have been developed and tested in the simulator. Smoother train trajectories, reduced power infrastructure requirements, and reduced energy consumption have been demonstrated. Improved service reliability is also expected to result.