News Note

Advanced Automatic Train Control Optimization

A new era of automatic train control has begun, in which mass transit trains will be commanded with precision beyond the capabilities of past systems. Although transit districts such as San Francisco's Bay Area Rapid Transit (BART) have controlled their trains automatically for decades, the control systems have provided limited capability. On a daily basis, the current system experiences approximately 20 delays of five or more minutes. The resulting backups can lead to wasted energy or even power outages. Therefore new systems, such as the Advanced Automatic Train Control (AATC) system, are under development. Our goal is to use optimization within the AATC system to smooth out train operations and reduce energy consumption and power infrastructure requirements. We are focusing on a schedule-constrained problem with the primary objective of improving passenger comfort. In general, train control optimization encompasses such classes of optimization as mixed integer nonlinear programming, nonlinear optimal control, and multi-objective optimization. Using Java, a simulation of train control in a single control zone has been developed. This will permit evaluation and testing of the optimization algorithms under development.

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