The research has tested several policy scenarios, and the practical implications of parking supply management is discussed. The results obtained help provide a better understanding of the need of freight parking and the policy alternatives available to improve the efficiency of urban freight systems. The results of the simulation provided the following insights related to which parking policies could be implemented to improve freight parking.

This research project produced an open source transit market data visualization and analysis tool suite, The Bus Transit Market Analyst (BTMA), which contains user-friendly GIS mapping and data analytics tools, and state-of-the-art transit demand modeling microsimulation capabilities. BTMA combines both archived transit operations data (e.g., automatic fare-box data), and new open data resources, particularly GTFS and US Census.

This document is a summary of findings based on this research as presented in several conferences during the course of the project. The research focused on identifying the basic metrics and models that can be used to develop representations of performance response that can be used to define resilience in urban environments, and to bring together data resources that can be investigated to understand and validate the interactive behavior of our complex transportation infrastructure systems, including the use of underground space.

This study had the following objectives: 1. To identify and clarify these two emerging effects – real time data and changing culture, 2. To identify the shifts in data collection and transportation modeling that must take place to assist in identifying and forecasting travel behavior, and 3. To discuss the impacts of such operational shifts, both in cost and outcomes to provide NYMTC with the cost and efficacy impacts of incorporating these emerging tools.” To address these objectives, the research team at Albany Visualization and Informatics Lab (AVAIL), led by Dr.

Between 1981and 2011, the State of Florida and private corporations, sometimes jointly, sometimes alone, made four different attempts to implement very high speed rail lines between Miami, Orlando, and Tampa, on which trains would run at very high speed, between 150 and 220 miles per hour. Yet, at present, the only new passenger line that is likely to begin operations between these cities is not very high speed, and will not run on dedicated track. Why did all the earlier attempts at very high speed lines fail, while a moderate speed line appears likely to succeed?

In 2006, the Panama Canal Authority decided to expand the Canal by investing more than $5 billion to accommodate bigger vessels than now to traverse the current facility. Along with the Nicaragua Canal construction that is optimally expected to finish 2019 (Miller, 2014), the widening of the Panama Canal will allow larger tankers to be able to go directly to the East or Gulf of Mexico ports and bypass the West Coast ports where so many imports currently change modes to cross-continental trucks or rail.

The objectives of this research are to understand the economic importance of border bridges on the U.S.-Canada economies, especially involving the various US states proximate to the Provinces of Ontario, and to simulate various the U.S.-Canada border bridge policy and security scenarios. To this end, we combined a novel bi-national highway network data with a freight flow dataset using ports of entry (POE) via highway border crossings. Through several sub-procedures, the US and Canada highway systems are integrated into a single network dataset.

In the field of transportation planning and engineering, the activity-based approach continues to generate interest in terms of model development and implementation. The Household Activity Pattern Problem (HAPP), is a mathematical programming approach to travel analysis under the activity-based framework. According to HAPP, activity travel patterns are the result of a household optimization with respect to a set of space-time and resource constraints, where the objective function represents travel (dis)utility.

This paper develops a random utility based estimation framework for the Household Activity Pattern Problem (HAPP). Based on the realization that output of complex activity-travel decisions form a continuous pattern in space-time dimension, the estimation framework is treated as a pattern selection problem.

Evidence is rapidly accumulating that attaining the full set of benefits from Automated Vehicles (AVs) will require that they do not merely mimic human-driving behavior.