This paper presents a variable speed limit (VSL) control algorithm for simultaneous maximizing mobility, safety, and environmental benefits in a connected vehicle (CV) environment. In a CV environment, data is available at a microscopic level capable of providing real-time individual driver information to a system that could provide guidance to vehicles in the network.



Methodology



This paper investigated a VSL control algorithm using a microscopic approach by focusing on individual driver’s behavior (e.g., acceleration and deceleration) through use of Model Predictive Control (MPC). A microscopic traffic flow prediction model was used to calculate total travel time (TTT), time to collision (TTC) was used to measure instantaneous safety, and a microscopic fuel consumption model (VT-micro) was used to measure environmental impacts.