Abstract
A road pricing model is presented that determines tolls for congested highways. The main contribution of this paper is to include density explicitly in the pricing scheme and not just flow and time. The methodology solves a nonlinear constrained optimization problem whose objective function maximizes toll revenue or highway use (2 scenarios). The results show that the optimal tolls depend on highway design and the level of congestion. The model parameters are estimated from a Chile’s highway data. Significant differences were found between the highway’s observed tolls and the optimal toll levels for the two scenarios. The proposed approach could be applied to either planned highway concessions with recovery of capital costs or the extension or retendering of existing concessions.
Highlights
This study presents an analytic road pricing model based on macroscopic traffic models to determine the tolls for congested highways
The parameters of the model were estimated using regression analysis, taking particular care to address possible problems of collinearity and endogeneity of tolls, traffic speed, and traffic density. The results of this application are that the optimal tolls in the maximum revenue scenario (MR) scenario are significantly higher than those for the maximum infrastructure use scenario (MIU) scenario
These results are consistent with the predictions of economic theory: the available infrastructure is more intensely used in the MIU scenario because in the MP scenario the tolls are raised to the point where marginal revenue is zero whereas in the MIU scenario highway use is maximized so tolls must be lower
Summary
Received 7 June 2017; Revised 27 July 2017; Accepted 9 August 2017; Published 17 October 2017. A road pricing model is presented that determines tolls for congested highways. The main contribution of this paper is to include density explicitly in the pricing scheme and not just flow and time. The methodology solves a nonlinear constrained optimization problem whose objective function maximizes toll revenue or highway use (2 scenarios). The results show that the optimal tolls depend on highway design and the level of congestion. The model parameters are estimated from a Chile’s highway data. Significant differences were found between the highway’s observed tolls and the optimal toll levels for the two scenarios. The proposed approach could be applied to either planned highway concessions with recovery of capital costs or the extension or retendering of existing concessions
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