Yonghua Zhou¹, Xun Yang¹, Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.92, No.5, pp. 477-491, 2013, DOI:10.3970/cmes.2013.092.477

Abstract Route selections for vehicles can be equivalent to determine the optimized operation processes for vehicles which intertwine with each other. This paper attempts to utilize the whole methodology of model predictive control to engender rational routes for vehicles, which involves three important parts, i.e. simulation prediction, rolling optimization and feedback adjustment. The route decisions are implemented over the rolling prediction horizon taking the real-time feedback information and the future intertwined operation processes into account. The driving behaviors and route selection speculations of drivers and even traffic propagation models are on-line identified and adapted for the simulation prediction in next prediction… More >

Yonghua Zhou¹ , Xun Yang¹ , Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.90, No.6, pp. 415-437, 2013, DOI:10.3970/cmes.2013.090.415

Abstract High-speed train transportation is organized in a way of globally centralized planning and locally autonomous adjustment with the real-time known positions, speeds and other state information of trains. The hierarchical integration architecture composed of top, middle and bottom levels is proposed based on model predictive control (MPC) for the real-time scheduling and control. The middle-level trajectory configuration and tractive force setpoints play a critical role in fulfilling the top-level scheduling commands and guaranteeing the controllability of bottomlevel train operations. In the middle-level MPC-based train operation planning, the continuous cellular automaton model of train movements is proposed to dynamically configure the… More >