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Traditional static traffic assignment models no longer meet the strategic planning needs of most major metropolitan areas, especially in regard to evaluating major infrastructure projects. One promising possibility is dynamic traffic assignment (DTA), which has been receiving greater attention in the research community for the last ten years. This work describes the ongoing experience of building...
Transformative technologies such as autonomous vehicles (AVs) create an opportunity to reinvent features of the traffic network to improve efficiency. The focus of this work is dynamic lane reversal: using AV communications and behavior to change the direction vehicles are allowed to travel on a road lane with much greater frequency than would be possible with human drivers. This work presents a novel...
The introduction of plug-in electric vehicles (PEVs) represents an unprecedented interaction between the road network and electricity grid. In this new integrated system, travel demand, behavior, and traffic congestion will influence the temporal and spatial characteristics of electricity usage and environmental impacts. Furthermore, uncertainty in the transport characteristics will manifest as a...
This work introduces a novel formulation of system optimal dynamic traffic assignment that captures strategic route choice in users under demand uncertainty. We define strategic route choice to be that users choose a path prior to knowing the true travel demand which will be experienced (therefore users consider the full set of possible demand scenarios). The problem is formulated based on previous...
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