Modelling emissions and energy use in traffic equilibria

Abstract

Over the last ten years, there has been increased awareness of greenhouse gases and their effect on climate change. The significant contribution of greenhouse gases from vehicles has provoked interest in estimating emissions in traffic models, such as in the Traffic Assignment (TA) model, which is capable of identifying traffic patterns that minimise vehicle emissions. Furthermore, zero-polluting electric vehicles are increasingly present in society, resulting in the need to model their energy consumption.

Average speed models are widely used for high-level modelling, including TA. Because of this, we use average speed models of energy consumption and emissions within TA. The literature concerning TA commonly assumes that energy consumption and emissions models are increasing with respect to traffic flow. These assumptions mean that standard TA solution algorithms can be employed to identify traffic patterns that minimise energy consumption or emissions.

We relax the assumptions of an increasing arc cost function, as energy consumption and emissions models are, in fact, non-monotonic with respect to flow. We then address the TA problem with non-monotonic arc cost functions, which is not often considered in the literature. Solution algorithms to the standard TA problem face several challenges when applied to the TA problem with non-monotonic arc costs. We discuss these challenges in detail and propose a solution algorithm that can identify solutions to the TA problem with non-monotonic arc cost functions; however, the solutions are not guaranteed to be globally optimal.

Within the literature concerning emissions in TA, user route choice is primarily determined by the emissions produced when the vehicle's engine is at operating temperature, also known as hot emissions. We consider cold-start emissions -- excess emissions produced due to engine inefficiencies when cold at the beginning of a trip. The models of cold-start emissions are dependent on the length of a trip. We solve the corresponding shortest path and TA problems with path-dependent arc costs to determine optimal user route choice.

We then discuss various extensions and applications of energy consumption and emissions models in the context of TA, using the concepts previously introduced theoretically in earlier chapters of the thesis.