Dynamic Congestion and Tolls with Mobile Source Emission

TL;DR

This paper develops a dynamic congestion pricing model that incorporates mobile source emissions, balancing individual travel costs with network-wide emission reduction goals, and demonstrates its effectiveness through numerical analysis.

Contribution

It introduces a novel emission-aware tolling model formulated as an MPEC and MPCC, with a solution approach and insights into traffic-emission paradoxes.

Findings

Tolling strategies effectively reduce emissions and congestion.

The model reveals a Braess-type paradox in emission context.

Numerical results demonstrate the approach's potential benefits.

Abstract

This paper proposes a dynamic congestion pricing model that takes into account mobile source emissions. We consider a tollable vehicular network where the users selfishly minimize their own travel costs, including travel time, early/late arrival penalties and tolls. On top of that, we assume that part of the network can be tolled by a central authority, whose objective is to minimize both total travel costs of road users and total emission on a network-wide level. The model is formulated as a mathematical program with equilibrium constraints (MPEC) problem and then reformulated as a mathematical program with complementarity constraints (MPCC). The MPCC is solved using a quadratic penalty-based gradient projection algorithm. A numerical study on a toy network illustrates the effectiveness of the tolling strategy and reveals a Braess-type paradox in the context of traffic-derived emission.