Satish V. Ukkusuri

TL;DR: This study considers the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns and presents a simple mobility model for predicting peoples’ visited locations using the popularity of places in the city as an interaction parameter between different individuals.

TL;DR: Urban human mobility and activity patterns are analyzed using location-based data collected from social media applications (e.g. Foursquare and Twitter) to characterize aggregate activity patterns and characterize individual activity patterns.

TL;DR: A data-driven modeling approach, based on topic modeling, is proposed to classify patterns in individual activity choices and provides an activity generation mechanism which when combined with the data from traditional surveys is potentially a useful component of an activity-travel simulator.

TL;DR: In this article, the link of land use and road design on pedestrian safety and the effect of the level of spatial aggregation on the frequency of pedestrian accidents was investigated for New York City based on an extensive dataset collected from different sources over a period of 5 years.

TL;DR: In this paper, a linear programming formulation for autonomous intersection control (LPAIC) is proposed to account for traffic dynamics within a connected vehicle environment, where a lane based bi-level optimization model is introduced to propagate traffic flows in the network, accounting for dynamic departure time, dynamic route choice, and autonomous intersections control in the context of system optimum network model.