Automated, electric, or both? Investigating the effects of transportation and technology scenarios on metropolitan greenhouse gas emissions

Abstract

The anticipated impacts of automated transportation are numerous. Of importance are the effects on energy consumption and greenhouse gas (GHG) emissions. Can automation promote low carbon transportation? Another question often raised relates to the appropriateness of current tools. Will existing tools become irrelevant in the face of the disruptive changes or can we extend the capabilities of our models to broadly capture the effects of automated transportation? This study presents an approach to estimate fuel-cycle GHG emissions, integrated within an activity-based travel demand model for the Greater Toronto and Hamilton Area. The model chain is used to evaluate different shares of automated vehicles (AV), and the effects of electrification of AVs. Daily operating GHG emissions were estimated at 29,000 t in CO2eq with 96% attributed to private vehicles and 4% to transit. While sharing a minor portion of emissions, the public transit system carries 32% of daily passenger kilometers traveled. When accounting for fuel-cycle emissions, the daily total was estimated to be over 36,000 t for private vehicles. With the introduction of AVs, higher vehicle kilometers travelled (3.6%–5.4%) and GHG emissions (2.5%) are expected. However, electrification of AVs can reduce regional GHG emissions (5%), and emission intensities of all vehicles (11%).