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Modeling and Simulation

Reinforcement Learning Methods for Traffic Demand Analysis and Control in Intelligent Transportation Systems

Within the dynamic field of transportation research, Reinforcement Learning (RL) has been recognized as a critical approach to monitor, model, and manage transportation systems. Among the diverse array of RL techniques, the Upper Confidence Bound (UCB) algorithm stands out for its potential in solving long-standing transportation problems.

Dynamic Toll Lane Microsimulation Calibration and Simulation: Improving Mobility by developing new pricing and control strategies for Dynamic Toll Lanes

This project constitutes a research effort to verify and calibrate a Dynamic Toll Lane (DTL) microsimulation model (Phase I) that will be used to test innovative pricing and control strategies aimed at reducing congestion (Phase II), specifically in a DTL and the main tollway lanes in the Metropolitan Area of San Juan, PR. The DTL was built recently and has already experienced congestion at the entrances and exits. The primary objective of this facility is to reduce, in some way, the time it takes to traverse the congested section of the freeway during peak hours.

Feasibility of employee shuttles for equitable mobility and improved housing options for low- and middle-income employees: A Case for Stony Brook University Campus

The objective of this project is to assess the feasibility of an employee shuttle for Stony Brook University (SBU) campus employees to reduce car dependency and to expand employee access to more affordable housing choices. The ultimate aim of the project is to develop a demand responsive employee shuttle pilot through an online mobility platform for work-home commute, complemented by on-demand service for noncommute trips (e.g., grocery) and carpool matching.

Transportation Risk and Resilience Metrics

This research, addressing the areas of Inclusive Advanced Technology Application and Climate Resilient Infrastructure, will evaluate a set of proof-of-concept transportation resilience measures to determine their utility and scalability as state and local performance measures. The research will review the latest scientific literature on risk and resilience measures to catalog methodologies scoring road network assets based on road segment attributes, hazard intersections, network centrality, and accessibility.

Evaluating a Microhub Pilot Program

Rapid urbanization in cities like New York City (NYC) has spurred an overwhelming surge in consumer demand, with a consequential 80% of deliveries now aimed at residential customers. Predominantly facilitated by trucks, which account for 90% of deliveries, this has detrimentally impacted air quality, traffic congestion, and overall life quality. In response, NYC has initiated the concept of micro-distribution centers or microhubs—spaces designed to transition deliveries from larger trucks to sustainable modes such as electric vehicles or cargo cycles.

Updating Princeton’s circa 2010 nation-wide, virtual household, virtual individual, virtual personTrip files to circa 2020

For over ten (10) years, Princeton University’s Transportation Program, under the direction of Professor Alain Kornhauser has been developing interactive web-based tools to make readily available to planners and researchers the fundamental demand for mobility that supports a desirable quality-of-life that reflect where people live and the distribution of land uses in which real residential patterns are imbedded.

Dr. Michael Katehakis

Dr. Katehakis is a distinguished professor at Rutgers University. He holds a courtesy appointment in Rutgers' New Brunswick Department of Mathematics Graduate Faculty, and he is a member of DIMACS the Center for Discrete Mathematics and Theoretical Computer Science, he is a Primary Investigator of CDDA the Rutgers Center for Dynamic Data Analytics, and a member of RUTCOR, the Rutgers Center for Operations Research.

Business Location Data Analysis and Editing Interface Tool Development

One of the most important aspects of transportation planning is understanding employment information of businesses and organizations. Information such as location of employment, size of organization or business in terms of employees, sales, can provide valuable input to understanding travel patterns and human activities. Visualizing this information along with several administrative, transportation and infrastructure facilities provides key contextual information to transportation planning agencies.

An Analysis Framework for Determining the Best Location of VMS's in a Transportation Network Using DTA

The location of Variable Message Signs (VMS) has not been adequately addressed by the research community yet it is a standard practice among state and local transportation agencies. The past few years have witnessed a new trend - mainly in Asian countries (e.g. Beijing, Shanghai, Singapore) – in the use of VMSs to provide traffic flow information in full/partial LED displays.

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