01592085

Component

In this paper, the authors present a real-time toll optimization framework where the toll optimization is integrated with a mesoscopic traffic simulator, DynaMIT, so that the tolls are optimized based on predicted traffic conditions. DynaMIT embeds several modules including demand simulation, supply simulation, and online calibration. The toll optimization module is in complete interaction with DynaMIT such that the optimized toll is decided with several iterations between the two rather than a single feedback function. Two main formulations are proposed; the first maximizes revenue and the second considers also the traffic conditions on managed lanes while maximizing revenue. The objective of this paper is to analyze the framework on a simple network in order to show its potential and understand the impact of several factors. Different numerical experiments are presented with different formulations and behavioral assumptions. It is shown that the framework generates consistent results such that as the demand increases or the willingness to pay is higher, the optimized tolls are higher. When constraints are introduced on traffic conditions, the resulting revenue is lower but network conditions are improved as expected. Based on this preliminary analysis, the authors see that the proposed framework is promising in the context of congestion pricing.

This paper was sponsored by TRB committee ABE25 Standing Committee on Congestion Pricing.

01584066

16-2073

English

15p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Congestion pricing; Demand; Network analysis (Planning); Optimization; Tolls; Traffic simulation

Data and Information Technology; Highways; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2016 Paper #16-2073

TRIS, TRB, ATRI

Jan 12 2016 4:54PM