A novel maximum likelihood based probabilistic behavioral data fusion algorithm for modeling residential energy consumption.

The current research effort is focused on improving the effective use of the multiple disparate sources of data available by proposing a novel maximum likelihood based probabilistic data fusion approach for modeling residential energy consumption. To demonstrate our data fusion algorithm, we consider energy usage by fuel type variables (for electricity and natural gas) in residential dwellings as our dependent variable of interest, drawn from residential energy consumption survey (RECS) data. The national household travel survey (NHTS) dataset was considered to incorporate additional variables that are not available in the RECS data.

A comprehensive analysis of COVID-19 transmission and mortality rates at the county level in the United States considering socio-demographics, health indicators, mobility trends and health care infrastructure attributes.

Background: Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) that can contribute to the COVID-19 transmission/mortality rate. The current study effort is designed to remedy this by analyzing COVID-19 transmission/mortality rates considering a comprehensive set of factors in a unified framework.

The Potential Impacts of Urban and Transit Planning Scenarios for 2031 on Car Use and Active Transportation in a Metropolitan Area.

Land use and transportation scenarios can help evaluate the potential impacts of urban compact or transit-oriented development (TOD). Future scenarios have been based on hypothetical developments or strategic planning but both have rarely been compared. We developed scenarios for an entire metropolitan area (Montreal, Canada) based on current strategic planning documents and contrasted their potential impacts on car use and active transportation with those of hypothetical scenarios.

Environmental and health impacts of transportation and land use scenarios in 2061.

We compared numbers of trips and distances by transport mode, air pollution and health impacts of a Business As Usual (BAU) and an Ideal scenario with urban densification and reductions in car share (76%-62% in suburbs; 55%-34% in urban areas) for the Greater Montreal (Canada) for 2061. We estimated the population in 87 municipalities using a demographic model and population projections. Year 2031 (Y2031) trips (from mode choice modeling) and distances were used to estimate those of Y2061.

Speed-profile-based road segmentation for accident occurrence modelling for hilly terrains.

Modelling the accident occurrences per unit length of the road requires segmentation of road stretch. In the case of hilly terrains, homogeneity-based approach results in extremely small sections thus creating a biased accident data. This result is due to the high variations in geometry along the length of the road stretch.