Abstract: The suitability and charging requirements of electric vehicles (EVs) may differ in rural areas, where the electrical grid may be less robust and daily VMT higher. Although other studies have examined issues of regional power requirements of EVs, none have done so in conjunction with the spatial considerations of travel demandand accessibility. We use three datasets to forecast the future spatial distribution of EVs, as well asto assessthese vehicles’ ability to meet current daily travel demand: the National Household Travel Survey (NHTS), geocoded Vermont vehicle fleet data, and an E911 geocoded dataset of every building statewide. We consider spatial patterns in existing daily traveland home-based tours to consider EV charging locations, as well as area-types that are unsuited for widespread electric vehicle adoption. We also consider how built environment attributes, including residential and commercial density and retail accessibility,affect travel demand and thus future EV energy requirements. We found that existing hybrid vehicles were more likely to be located nearother hybrids than conventional vehicles were. This clustering of current hybrid vehicles,in both urban and ruralareas, suggeststhat the distribution of future EVs may alsobeclustered. Our analysis suggests that between 69 and 84% of the state’s vehicles could be replaced by a 40-mile range EV, and 96-99% could be replaced by a 100-mile EV, depending on the availability of workplace charging.We did not find a strong relationship between land-use and travel demand, perhaps due to our low number of urban data points,the highly variable nature of rural travel, and the limitations of using a one-day travel log dataset. Our results suggest EVs are a viable option to serve existing traveldemand by rural residents but may require special consideration for power supply and vehicle charging infrastructure.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).