Abstract
The extension of planning tools to consider the impact of new technologies and mobility trends, such as ride-hailing (RH) and connected autonomous vehicles (CAVs), is a pressing need among transportation planners and decision-makers. This paper discusses the incorporation of empty (zero-occupancy) trips attributable to RH and CAVs into a four-step planning model. We estimate RH empty trips using an exogenous constant-multiplier. For CAVs, we consider the vehicle miles traveled (VMT) generated by empty “return home” and “park elsewhere” trips. The “return home” and “park elsewhere” trip fractions are determined using a binary choice model based on distance to home and average parking cost at the destination zone. Parking location choice is modeled using a logit approach that considers parking costs and distance to parking location. The methods developed in this work are incorporated into a model of the Dallas-Fort Worth region, U.S., that was previously extended to account for RH and CAVs. Results suggest that, for a 40% penetration of CAVs and a 4% mode share by RH, empty trips add 22 million VMT and have significant impacts on vehicle hours traveled and traffic congestion. While results depend on modeling assumptions, our experiment illustrates the value of extended models in understanding the implications of policies such as parking costs and limiting the movement of empty vehicles. The four-step process is still the primary tool used for long-term planning, making our proposed modeling approach a feasible option for planning organizations to consider.
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