Sustainability Performance Simulation of the U.S. Urban Mobility Policies

Abstract

Heavy dependence on personal vehicle usage in the U.S. has made the transportation sector one of the greatest contributors to air pollutant emissions the associated human health concerns. The transportation mode choices of urban commuters play a key role in the evaluation and management of these threats. This study investigates the impacts of autonomous vehicles (AVs) on transportation mode choice and on applicable trends in transportation-related externalities, carbon emissions, and air pollution for the year 2050. To this end, in addition to testing various market penetration scenarios for AVs, this study will analyze common policy applications such as limiting lane-mile increases on roadways (i.e. limiting the expansion projects) and introducing carbon-tax policies to vehicle owners from the year 2025 onward. Demographic parameters and five transportation mode choices for 929 metro/micropolitan areas of the U.S. are processed in simulations of a fractional split multinomial model. A system dynamics modeling approach is integrated in this study with discrete-event model outcomes as part of a novel hybrid simulation model. The results show that policies such as line-mile increases and carbon taxes have a negligible reduction effect on transportation-related sustainability impacts. On the other hand, the introduction of AVs into the U.S. transportation has significant potential to reduce annual CO₂ emissions compared to any combination of lane-mile and carbon-tax policy scenarios by the year 2050.