Automated, Electric, or Both? Investigating the Effects of Transportation and Technology Scenarios on Metropolitan Greenhouse Gas Emissions

The anticipated changes that automated transportation systems are expected to bring about in urban areas are numerous. Of utmost importance are the effects on energy consumption and greenhouse gas (GHG) emissions. Can automation promote low carbon transportation options? As government agencies begin to ask these questions to develop transportation policies and vehicle/fuel standards, another question often raised relates to the appropriateness of the tools currently available. Will existing tools become irrelevant in face of the disruptive changes affecting transportation systems or can the authors extend the capabilities of existing models to broadly capture the effects of automated transportation? This study presents an approach to estimate lifecycle GHG emissions. The methodology is integrated with an activity-based travel demand model for the Greater Toronto and Hamilton Area. The integrated modeling chain is used to evaluate various policy scenarios including different penetration rates of automated vehicles (AV), and the effects of electrification of AVs. In the base case, daily operating GHG emissions for the region were estimated at 29,000 tonnes CO2eq with 96% from private vehicles and 4% from transit. While sharing a minor portion of GHG emissions, the public transit system carries 32% of the daily passenger kilometers traveled. When including upstream emissions, daily emissions were estimated to be over 36,000 tonnes 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 slightly reduce regional GHG emissions (5%), and substantially reduce emission intensities of all vehicles (11%).

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC70 Standing Committee on Transportation Energy.
  • Authors:
    • Wang, An
    • Stogios, Christos
    • Gai, Yijun
    • Vaughan, James
    • Ozonder, Gozde
    • Lee, SeungJae
    • Posen, I Daniel
    • Miller, Eric J
    • Hatzopoulou, Marianne
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 6p

Subject/Index Terms

Filing Info

  • Accession Number: 01661282
  • Record Type: Publication
  • Report/Paper Numbers: 18-01570
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 26 2018 1:45PM