Modeling and simulation of congestion control strategies on freeways: Pricing, ramp metering, and variable speed limit
Cho, Hyun Woong
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When demand exceeds supply (capacity), freeways become congested. However, in a congested state, compared to the uncongested state, the capacity of a freeway decreases. The purpose of freeway operations and traffic management systems is to maximize capacity and utility of the freeway system. For decades, researchers have introduced traffic congestion control strategies such as managed toll lanes, on-ramp metering, and variable speed limits. This dissertation examines the modeling and simulations of demand- and supply-side management strategies that reduce freeway congestion. The first part of this dissertation analyzes real-time pricing strategies for controlling the demand for a managed lane facility, such as the HOT lane. We devise a system-optimal real-time congestion pricing strategy capable of handling variable capacity because of the weaving activity and find that the proposed model outperforms existing methods in minimizing total delay savings, particularly when bottleneck capacities vary significantly. The method is simple to implement with current technology. The second part of this dissertation investigates supply-side strategies. It proposes a variable speed limit and ramp metering (VSL-RM) control strategy for preventing and recovering from losses in freeway capacity at freeway merge bottlenecks. Using kinematic wave theory, this study derives analytical models that are implemented in the microsimulation model GTsim and finds that the combined VSL-RM system outperforms both systems in preventing traffic breakdown; if only one system has to be used, the choice depends on the distribution of traffic demand. The third part of this dissertation presents a case study that implements the VSL-RM strategy in a real-life freeway corridor in Atlanta. Using a stochastic simulation-based optimization framework that combines GTsim and a genetic algorithm-based optimization module, we determine the optimal parameter values of a combined VSL-RM system that minimizes total vehicle travel time.