The objective of this work is to develop a last-mile delivery optimization model based on Continuous Approximation (CA) techniques and cost-based sustainability assessments, capable of testing various last-mile strategies.
This project measures sidewalk, curb ramp, and curb cut quality data to evaluate pedestrian infrastructure quality. The project considers accessible, active travel for people with physical disabilities.
This project will look at the geospatial modeling of electric vehicles supply equipment (EVSE). This project aims to develop a set of up-to-date geospatial models for future fuel infrastructure transition in California.
This project measures NO2 and particulate matter (PM 2.5) concentrations in Riverside, California. There is special focus on the spatial and temporal variability of the pollutants in relation to major urban roadways.
Using Atlanta’s MARTA rail system as a case study, this thesis will assess the feasibility of integrating autonomous transit vehicles (transit AVs) into the public transportation system as a first-mile and last-mile solution for riders.
This research aims to develop an Artificial Neural Network (ANN) to forecast EVs’ trip destinations and charging behavior–information that is essential for electricity load aggregators to effectively manage charging loads.