The purpose of this project is to address the issue of robustness in the design of variable speed limit and bring them closer to successful implementation with consistent and well-understood benefits.
In this study, the researchers will use optimization and simulation modeling to explore the impacts of using battery electric heavy-duty trucks (BEHDTs) in freight operations (e.g., fleet size) and emissions, taking into account differences in performance and refueling.
This research project will implement a before/after, experimental-control group study of slow street infrastructure to examine the role that supportive non-motorized infrastructure can play in non-motorized travel.
This project examines changes in the spatial pattern of warehousing and distribution (W&D) activities and how these changes may impact truck vehicle miles traveled.
The research team will create a quantitative spatial equilibrium model of on-site and remote worker location choice and transport demand in the contiguous United States in order to examine how the distribution of jobs and residents within and across U.S. cities would change if the 2020 surge in working from home becomes permanent, and what the effect on demand for commuting and freight transport would be.
The purpose of this research is to provide a ride-sharing planning scheme that will consider all three sources of uncertainties to provide a robust travel plan while at the same time reducing travel time for the commuters.
This white paper analyzes evidence on the economic benefits of placemaking efforts that prioritize pedestrian and non-motorized access and that, at times, reduce vehicle miles traveled. The researchers summarize evidence on how locally oriented placemaking efforts are associated with benefits that help boost local economies.
One of the drawbacks of ridesharing is the extra inconvenience to the drivers and passengers of excessive detours to pick up new riders. The research team proposes to develop an optimization-based solution procedure to solve this problem based on iteratively solving the routing and pick up and drop off points.