| dc.description.abstract | Two common means of pricing managed lanes (MLs) are to vary tolls based on time of day or to vary them dynamically based on real-time congestion. It is not clear which of the two tolling options is more effective in regulating ML usage. In this research, large datasets on toll prices, vehicle travel speeds, and traffic volumes were used to assess the effects of the two different congestion pricing strategies on traffic conditions on six MLs around the United States. The MLs included two variably priced: SR-91 and I-25; and four that were dynamically priced: I-35W, I-394, I-35E, and MoPac.
The research used nine different performance measures to examine the ability of the toll to regulate traffic on the MLs. These included travel time savings, variability benefit, planning time index benefit, mobility benefit, buffer time index benefit, the ability of the toll to impact congestion, speed threshold achievement, speed graphs, and scoring index. These performance measures included several unique measures developed as part of this research and proved useful in measuring how well the ML toll was able to regulate traffic flow and keep the MLs operating smoothly.
Using these nine performance measures, the impact of the two pricing approaches on traffic conditions was evaluated. Overall, both pricing measures were found to keep traffic flowing on MLs, and neither pricing method was clearly superior. Although there was no clear winner, this does mean that both pricing mechanisms can work to keep MLs flowing and thus are viable options for ML operators. One item for future research would be to apply these performance measures to additional ML datasets to see if one method does perform significantly better given a larger set of MLs to investigate. These performance measures are a key contribution of this research and provide excellent benchmarking for the effectiveness of tolling on regulating ML traffic flow. | en |
