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Webinar: Autonomous Vehicle Good Citizenry Standard
2023-06-29 12:00 - 13:00 (America/New_York)
Presented by:
Sarah Kaufman, Interim Director, NYU Rudin Center for Transportation
Joseph Chow, Associate Professor, NYU
Thursday, June 29, 2023: 12:00pm – 1:00pm ET | Virtual
New York City is moving toward a more efficient, safer, and sustainable future that includes autonomous vehicles for transit, e-commerce, and medical transport. However, autonomy often runs on incomplete or flawed foundations: training data sets might not prepare vehicles to “see” people of color; transit shuttles may operate without safety considerations for women, frequent targets of sexual harassment on transit; delivery pods might be sharing personal data with several third parties. Although the City will regulate vehicle safety and efficacy on the street, autonomous mobility must be evaluated under more ambitious and holistic standards. The Responsible Autonomous Mobility (RAM) Framework aims to identify partnership in several areas.

Summer Webinar Series
2023-06-15 15:00 - 16:00
Presented by the Transportation Research Board (TRB) subcommittee AEP30(2) Route Choice and Spatio-Temporal Behavior
Speaker: Professor Marcela A. Munizaga, Universidad de Chile.

Webinar: Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed
2023-06-13 12:00 - 13:00
Presented by: Joseph Chow, Associate Professor, NYU
Haggai Davis, PHD Candidate, NYU
Tuesday, June 13, 2023: 12:00pm – 1:00pm ET | Virtual

Summer Webinar Series- Route Choice and Spatio-Temporal Behavior: The Perturbed Utility Route Choice Model
2023-05-24 12:00 - 13:00
The perturbed utility route choice model represents traveler behavior as a utility maximizing assignment of flow across an entire network under a flow conservation constraint. Substitution between routes depends on how much they overlap. The model is estimated considering the full set of route alternatives, and no choice set generation is required. Nevertheless, estimation requires only linear regression and is very fast. Predictions from the model can be computed using convex optimization, and computation is straightforward even for large networks. In this talk, Professor Fosgerau presents results from application to large datasets (1,337,096 GPS traces of car trips, 280,000 GPS traces of bicycle trips) in Copenhagen.
SPEAKER
Mogens Fosgerau is a professor in the Economics Department, University of Copenhagen. His areas of research include micro-economics and micro-econometrics applied to problems in transportation, in particular to issues concerning time, reliability and congestion.
Presented by the Transportation Research Board Subcommittee on Route Choice and Spatio-Temporal Behavior (AEP30/AEP40)

USDOT Free Public Webinar: Intersection Safety Challenge Prize Competition
2023-05-22 15:30 - 16:45 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
The U.S. Department of Transportation (DOT) will host a webinar on May 22 to discuss the Intersection Safety Challenge Prize Competition, which launched on April 25, 2023.
Each year, roughly one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States are attributed to intersections. According to the latest data from the National Highway Traffic Safety Administration (NHTSA), an estimated 42,939 people died in motor vehicle traffic crashes in 2021, a 10.1% increase compared to 39,007 fatalities reported in 2020. From 2020 to 2021, pedestrian and pedalcyclist fatalities and injuries increased at an alarming rate. For example, pedestrian fatalities increased 13% and pedestrian injuries increased 11% from 2020 to 2021. In response to growing concerns regarding the safety of vulnerable road users at intersections and as part of the recent National Roadway Safety Strategy (NRSS) Call to Action, the DOT aims to transform intersection safety through the innovative application of emerging technologies to identify and mitigate unsafe conditions involving vehicles and vulnerable road users.
To help address this growing problem and support U.S. DOT’s vision, U.S. DOT is launching the Intersection Safety Challenge. This Challenge includes a multi-stage Prize Competition to encourage teams of innovators and end-users to develop and test their intersection safety systems (ISS) to compete for up to $6 million total in prizes.
The Challenge is considering the potential of emerging technologies to transform intersection safety and ensure equity among all road users (including vehicles and vulnerable road users). Leveraging emerging technologies to anticipate, prevent, and mitigate unsafe roadway conditions could augment traditional safety engineering in roadway design and intersection control. These emerging technologies could include machine vision, machine perception, sensor fusion, real-time decision-making, artificial intelligence, and vehicle-to-everything (V2X) communications (among other approaches). These technologies in most cases rely on real-time decision-making informed by data ingested and analyzed from multiple sensor systems.
The webinar will discuss the U.S. DOT Intersection Safety Challenge Prize Competition, including a program overview, the Prize Competition structure, and Stage 1A expectations. Please register for this webinar by visiting the following registration link: https://iscwebinar.eventbrite.com.
For more information about the program, please visit the program website: https://its.dot.gov/isc. For more information about the ITS JPO, please visit: https://www.its.dot.gov/.

Deep Neural Networks for Choice Analysis
2023-05-19 14:00 - 15:00 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
Individual choice has been an enduring question across disciplines. Deep neural networks (DNNs) have demonstrated their high predictive power over the classical discrete choice models (DCMs) in many empirical studies. However, DNNs as a new modeling paradigm still present pressing challenges in interpretation, generalization, and robustness. This presentation introduces a deep choice framework that synergizes DNNs and DCMs to model individual travel decision. It demonstrates that the DNNs can provide economic information as complete as classical DCMs, including choice predictions, choice probabilities, market shares, substitution patterns of alternatives, social welfare, heterogeneous values of time, among many others, thus partially resolving the interpretation challenge. It introduces how to use the prior behavioral knowledge to design a particular DNN architecture with alternative-specific utility functions, which improves the generalizability of DNNs with a domain-knowledge-based regularization method. It then extends the framework to deep hybrid models, which integrates classical numerical data and the unstructured data (i.e., imagery and graphs) to analyze travel behavior. Overall, this presentation lays out a new foundation of using DNNs to analyze travel demand, enhancing economic interpretation, architectural design, and robustness of deep learning through classical utility theory.

SPEAKER
Shenhao Wang is an assistant professor and the director of the Urban Artificial Intelligence Laboratory at the University of Florida. He is also a research affiliate to Urban Mobility Lab and Media Lab at the Massachusetts Institute of Technology. He seeks to develop fundamental theory for urban science using artificial intelligence. He develops deep choice models, which analyze individual decision-making by integrating discrete choice models and deep learning with applications to urban travel behavioral analysis. He also analyzes collective mobility networks by integrating classical network theory and graph neural networks to quantify risk and uncertainty, thus promoting resilient economic growth. Dr. Wang completed his interdisciplinary Ph.D. in Computer and Urban Science at Massachusetts Institute of Technology in 2020. He received B.A. in Economics from Peking University (2014) and B.A. in architecture and law from Tsinghua University (2011), Master of Science in Transportation, and Master of City Planning from MIT (2017).

Learning from big and small data for transportation planning and resilience analysis
2023-05-16 12:00 - 13:00 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
POSTPONED – TO BE RESCHEDULED
COVID has exacerbated two emerging trends in transportation analysis: (1) the rise of passively-generated big data; and (2) the increasing need to deal with the “unexpected” disruptions. This talk emphasizes the need for learning big and small data for transportation planning and resilience analysis. Different ways of learning are described, with applications ranging from long-term planning analysis to rapid responses under disruptions.
PRESENTER
Cynthia Chen is a professor in the Department of Civil & Environmental Engineering at the University of Washington (Seattle). She is also a professor and the interim chair of the Department of Industrial & Systems Engineering at UW. She is an internationally renowned scholar in transportation science and directs the THINK (Transportation-Human Interaction and Network Knowledge) lab at the UW. Cynthia has published over 60 peer-reviewed publications in leading journals in transportation and systems engineering including Transportation Research Part A-F and Omega, as well as interdisciplinary journals such as PNAS. Her research has been supported by federal agencies such as NSF, NIH, APAR-E, NIST, USDOT, and FHWA as well as state and regional agencies. Cynthia served a two-year assignment (2017-19) as the Program Director of Civil Infrastructure Systems, CMMI (Civil, Mechanical, and Manufacturing Innovation) division with the National Science Foundation. She is an associate director of TOMNET (Center for Teaching Old Models New Tricks), a USDOT-funded Tier 1 University Transportation Center led by ASU, as well as a key member of the new Center of Understanding Future Travel Behavior and Demand, a USDOT-funded national center led by UT Austin. Currently, Cynthia serves as an associate editor for Transportation Science, and is on the editorial board of Sustainability Analytics and Modeling.

KAIST-NYU: KN-C³ Workshop
2023-05-15 - 2023-05-18 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
Members of faculty from KAIST (Korea Advanced Institute of Science & Technology) will visit NYU for the first KN-C³ workshop at NYU Tandon. This four-day workshop consists of research exchanges between the two schools focusing on transportation and urban research. The goal is to connect researchers and find common research interests for future collaboration. Academic exchange programs including dual and/or joint degree will also be discussed. Learn more.

Old Models with New Tricks: Bridging the Gap in Bureau of Public Roads (BPR) Functions with A Cross-Resolution Perspective of Theoretical Fundamentals and Emerging Applications
2023-05-05 12:00 - 13:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
In transportation planning, volume-delay functions (VDFs) are essential functions used for traffic assignment and network design problems. However, the static Bureau of Public Roads (BPR) function, created by the US Bureau of Public Roads in 1964, can only provide average travel time measures and cannot capture traffic dynamics at an oversaturated bottleneck. This talk will systematically review VDF-related research, including modeling efforts that connect traffic flow’s fundamental diagrams (FDs) to queueing models and link delay/performance functions under both undersaturated and oversaturated conditions. We will discuss a cross-resolution modeling approach for understanding the dynamic relationship between demand and supply and resulting congestion. We will also describe oversaturated system dynamics using parsimonious macroscopic analytical formulations with consistent mesoscopic queue vehicular fluid models. By providing a unified integration of multi-scale models, city planners can have a valid analytical framework to analyze queue saturation evolution processes. The effectiveness of this approach will be demonstrated through case studies using empirical data from heavily congested corridors in metropolitan areas, including New York, Los Angeles, and Phoenix. This talk will showcase how old models can be revitalized with new tricks to address the challenges of transportation planning and feedback-based control in the modern era.
PRESENTER
Xuesong (Simon) Zhou is an Associate Professor of Transportation Systems at the School of Sustainable Engineering and the Built Environment, Arizona State University (ASU), Tempe, Arizona. Dr. Zhou’s research focuses on developing methodological advancements in multimodal transportation planning applications, including dynamic traffic assignment, traffic estimation and prediction, large-scale routing, and rail scheduling. Dr. Zhou serves as an Associate Editor of Transportation Research Part C, an Executive Editor-in-Chief of Urban Rail Transit, and an Editorial Board Member of Transportation Research Part B. He was the former Chair of INFORMS Rail Application Section (2016) and currently serves as a subcommittee chair of the TRB Committee on Transportation Network Modeling (AEP40).
Dr. Zhou is the Director of the ASU Transportation+AI Lab, where he is the principal architect and programmer for several open-source packages, including DTALite, NEXTA, and OSM2GMNS, which have collectively received over 100,000 downloads and many system deployments at various metropolitan planning agencies and state DOTs. He has published over 100 papers in Transportation Research Part B, Transportation Research Part C, and other leading transportation journals, with an H-index of 54 and a total of 9,000 citations in Google Scholar.
In addition to his academic achievements, Dr. Zhou is passionate about connecting practitioners, researchers, academics, students, and others involved in transportation planning and travel modeling. He serves as the conference chair for the TRB Innovations in Travel Analysis and Planning Conference in 2023, and a board member of Zephyr Foundation, a non-profit organization dedicated to advancing transportation research and education.

Python for GIS: An Introduction to OSMnx
2023-04-28 11:00 - 12:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Shajnush Amir, North South University & University of Twente
Hands-on exercise: Yes
Beginner level: No prior experience required.
Schedule: Friday April 28, 11:00am-12:00pm
Description: In this course, you will learn how to harness the power of OSMnx, a Python library for extracting and visualizing Open Street Maps data. Through hands-on exercises, you will gain practical experience in using OSMnx to model and simulate projects and have a solid understanding of this Python library and be able to apply OSMnx to real-world problems.

Stairway Towards Systematic Review: Utilizing Rayyan Software & PRISMA Guidelines
2023-04-14 10:00 - 11:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Samiha Tasnim, North South University
Hands-on exercise: Yes
Beginner level: No prior experience required.
Schedule: Friday April 14, 10:00am-11:00am
Description: Rayyan is a free web tool that aims to help researchers work on systematic reviews by accelerating the process of screening and selecting articles. Besides, the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) checklist is an extensively used tool for reporting systematic reviews, which strives to create transparent, credible, and reliable research results. This course intends to cover the fundamentals of using Rayyan and PRISMA, why, and how to utilize them to kickstart your pathway toward research.

Optimal dispatching of electric vehicles for providing charging on- demand service leveraging charging-on-the-move technology
2023-04-06 12:00 - 13:00
Range anxiety and charging infrastructure scarcity have been the main challenges for the mass adoption of electric vehicles (EVs). The emerging mobile electric-vehicle-to-electric-vehicle (mE2) charging technology offers a promising solution, which combines battery-to-battery and connected and autonomous vehicle technologies to enable an EV with an extra battery to charge another EV on the move. This webinar focuses on the efficient pairing and routing of electricity providers (EPs) to demand (EDs) by extending the existing Charging-as-a-Service (CaaS) strategy to the mE2 charging service (referred to as CaaS + ). Dr. Lili Du will discuss the EP fleet management problem, which is mathematically modeled as a vehicle routing problem (i.e., mE2-VRP), aiming to optimally dispatch the minimum number of EPs to approach and serve the EDs using different proportions of EV flows to save EDs’ travel time and mitigate traffic congestion to different extents in different network congestion and charging station coverage scenarios. She will also discuss suggestions for improving the service efficiency of CaaS + .
PRESENTER
Dr. Lili Du is an associate professor in the Civil and Coastal Engineering Department, University of Florida. Before that, she worked as an assistant and then an associate professor at the Illinois Institute of Technology (IIT) from 2012 to 2017, and as a Post-doctoral Research Associate for NEXTRANS at Purdue University from 2008 to 2012. Dr. Du received her Ph.D. degree in Decision Sciences and Engineering Systems with a minor in Operations Research and Statistics from Rensselaer Polytechnic Institute in 2008. Dr. Du’s research is characterized by integrating operations research, network modeling, game theory, control theory, machine learning, and statistical methods into traffic flow analysis, transportation system analysis, and network modeling. Her current research mainly focuses on the impacts of connected and/or autonomous vehicles and electric vehicles, mobility on demand, smart curb, network resilience, and traffic flow analysis. Dr. Du’s research has been published in Transportation Research Part B, Part C, and Part D, IEEE Transactions on ITS, Networks and Spatial Economics. Her research has been funded by National Science Foundation (NSF), State DOT, STRIDE UTC, and Toyota InfoTechnology Center. Dr. Du is a recipient of the NSF CAREER award in 2016. Her recent project, “Driverless City” won the First Nayar Prize at IIT. She is the founding chair of both TRB AEP40-4 subcommittee on Emerging Technologies in Network Modeling and ASCE-T&DI Artificial Intelligence in Transportation Committee. She serves as an editor for Transportation Research Part B: Methodological, an associate editor for IEEE Transactions on Intelligent Transportation Systems, and a member of the editorial advisory board for Transportation Research Part C: Emerging Technologies.

Unleash Your Creativity with Unity 3D Simulation and Transportation Network Modeling
2023-03-31 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Lukelo Thadei Luoga, New York University Abu Dhabi
Schedule: Friday March 31, 1:00-2:00pm
Description: In this hands-on course, you’ll learn how to use Unity 3D to build 3D models of road networks. You’ll start with the basics of Unity 3D, including its interface, GameObjects, components, and scripting. From there, you’ll dive into building 3D models of road networks, covering elements such as roads, buildings, and terrain.

5th Women in Transportation Panel Discussion and Networking Event
2023-03-28 18:00 - 19:00 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
The C2SMART Center and the NYU chapter of the Institute of Transportation Engineers (ITE) are excited to host our annual Women in Transportation Panel Discussion, including an opportunity for attendees to network and socialize. This year’s panel boasts three amazing women working in the transportation industry who will share their perspectives and experiences.
This event is a one-hour evening event in a panel format with women from within the industry and agencies with professional experience in the engineering and planning field, to help engage the female students and empower them to pursue their career goals. They will discuss gender challenges in the engineering/ planning field, give advice for overcoming those challenges, and tips for future transportation engineers/planners. The event will conclude with a 10-minute Q&A and an opportunity for the students to network with the panelists. Pizza and refreshments will be provided.
PLEASE NOTE: this will be a hybrid event, and all attendees are welcome to come in-person. However, ALL attendees must register via Zoom, regardless of whether they are attending in person, in order to receive building access.
PANELISTS
Nadereh Moini is the Chief of Transportation at the New Jersey Sports and Exposition Authority (NJSEA) Formerly Known as New Jersey Meadowlands Commission. She has diverse scholar and field experiences in planning, design, safety, operation, maintenance, and assessment of multimodal transportation systems and the application of the state-of-the-art technologies in transportation. In her current capacity, she is managing more than 125 adaptive signalized intersections throughout the Meadowlands District. She is also responsible to develop “Meadowlands District Transportation Plan” and the first “Meadowlands Action Plan for Safety”, which is newly funded by USDOT.
She holds Ph.D. in Civil & Environment Engineering. She is a licensed Professional Engineer in the states of NY and NJ. She is also a registered Professional Traffic Operation Engineer (PTOE) and Professional Transportation Planner (PTP). Additionally, she has International Municipal Signal Association –IMSA Level I Certification.
Haley Hutson is a Traffic Engineer at AKRF, Inc. Haley started her career in Texas after graduating from the University of Texas and has spent the past two years working in New York. She specializes in adaptive traffic signal controls, traffic modeling, and roadway design. She is the Vice Chair for the ITE Urban Goods Committee and a co-chair of the ITE Met Section Young Member Committee. When her engineering hat isn’t on she is a Senior Disaster Responder volunteer for the Red Cross.
Mira Philipson is Senior Analyst for MTA’s Accessibility team in the Office of the Chair. In her four and a half years working to improve accessibility across the MTA, she has researched and piloted new solutions, technological and otherwise, for people with disabilities and all customers. She has managed pilot projects including the Accessible Station Lab and Transit Innovation Partnership’s Transit Tech Lab Accessibility Challenge to discover smartphone wayfinding applications and other physical wayfinding solutions in subway stations and along bus routes. She also collaborates internally to ensure all MTA content, public-facing and employee-facing, is accessible. Her role also includes maintaining relationships and conducting outreach with members of the disability community in New York, as well as collaboration with accessibility professionals at public transportation agencies across the country and world to information and experience-share.
Mira graduated from Barnard College with a Bachelor of Arts degree in Urban Planning with a Concentration in Sociology. She completed her senior thesis on the history of the Second Avenue Subway after spending time studying European urban transportation in Copenhagen, Denmark. She is passionate about making cities, and specifically transportation infrastructure, more accessible to underserved populations.

Unlock the Power of Graph Neural Networks: Understanding the Fundamentals and Knowing When to Implement
2023-03-24 12:00 - 13:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Zilin Bian, New York University
Schedule: Friday March 24, 12:00pm-1:00pm
Description: Graph Neural Networks (GNNs) are a powerful tool for analyzing and processing graph-structured data. This course covers the basics of GNNs, including graph convolutional networks, graph attention networks and graph wavelet networks, including how they work and how to implement them. The session aims to provide a solid understanding of GNN modeling for machine learning practitioners, data scientists, and anyone interested in AI advancements.

Chatting with ChatGPT: Exploring the Advancements in AI Language Models
2023-03-10 11:00 - 12:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Fan Zuo, New York University
Schedule: Friday March 10, 11:00am-12:00pm
Description: In this course, you will learn about ChatGPT, a state-of-the-art language model developed by OpenAI. You will gain an understanding of how ChatGPT works and how it can be used to generate human-like text, answer questions, and perform various natural language processing tasks. Through hands-on activities and live demos, you will also get to apply ChatGPT to real-world problems and understand its advantages as well as limitations. Whether you are a student, developer, or researcher, this course will provide you with a solid foundation in the exciting field of AI and natural language processing. (Yes, this is written by ChatGPT!)

2nd NYU-TJU Urban Transportation Forum
2023-02-22 08:30 - 12:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
3On February 22, 2023, New York University and Tongji University are joining forces to host an online urban transportation forum. The topics to be covered in this virtual event include the future of transportation, sustainability and equity in transportation systems, travel behavior, and safety in urban transportation. This forum will provide a platform for experts and students to come together and discuss the pressing issues in the field, and offer new perspectives on shaping the future of urban transportation.
Agenda (click to expand)
20230222 NYU-TJU 2nd Urban Transportation Forum Agenda
Pre-registration via Zoom is required. Please click the Register button below.

Roundtable on Traffic Safety Research featuring Dr. Tarek Sayed
2023-02-21 16:00 - 17:00 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
The increasing popularity of smart cities and recent developments in sensing, edge computing and vehicle technologies and the availability of “big data” combined with sophisticated AI techniques offer an opportunity to substantially advance and fundamentally transform the road safety profession—enabling continuous, real-time, proactive safety evaluation and optimization. The application of innovations that are both progressing and disrupting the status quo represents an opportunity for improved transportation safety. However, with the introduction of new modes of mobility and the complex interactions created by these different technologies within the transportation system, governments will need to rely on advanced research and analysis techniques to support policies towards the transition to these new forms of mobility and technologies. These issues are discussed and several methods and techniques developed in this area are described with example projects from several agencies worldwide.

Tarek Sayed is a distinguished professor and a Tier 1 Canada Research Chair of Transportation Safety and Advanced Mobility at the University of British Columbia. His research focuses on traffic operation and safety, Intelligent Transportation Systems (ITS), and the application of information technologies.

A Framework for Modeling Human-vehicle Interactions with Increasingly Autonomous Systems
2023-02-14 10:30 - 11:30 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
Dr. Linda Ng Boyle is a Professor of Industrial Systems Engineering & Civil and Environmental Engineering at the University of Washington

Transit Techies #13: Projects on Bike Safety & Infrastructure with NYU Tandon
2023-02-06 17:45 - 19:30 | 370 Jay Street, Room 1201, 370 Jay Street, Brooklyn, 11201
Transportation Techies is a group of technologists, urban planners, commuters and more who are interested in how technology can enable the future of mobility in metropolitan areas. This showcase will feature 2 projects on improving commuting experience for bikers in NYC. First, Ariel Kadouri will give an update on mapping bike and pedestrian infrastructure. He will be giving his State of the Map talk, and opening it up for Q&A.
Following this, C2SMART’s Suzana Duran Bernardes give a live demo of her mountable sensors to improve cyclist safety. She will deliver a Q&A afterwards.

Smart Electric Vehicle Charging: Modeling Drivers’ Choices and Autonomous Vehicles’ Strategies
2022-12-02 13:00 - 14:00 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201
As transportation is increasingly electrified, understanding travel and charging choices of electric vehicle drivers and users of shared electric mobility systems is crucial for service planning and operations. Ultimately, quantitative models of users’ behavior enable the estimation of local and regional demand impinging on transportation and electricity networks and the development of approaches to manage the demand so that such networks can operate efficiently. Developing realistic models of individual behavior to use as “users’ digital twins” in planning and operations is challenging enough, due to the inherent uncertainties of how individuals make everyday choices and their heterogeneity in approaching decisions. Even more challenging is to attempt to anticipate how users might respond to new technologies and changes in infrastructure or services. In this case choice data from systems’ operations or “revealed preference” users’ surveys may not exist, be available only from early adopters, or relate to the system before the change. In this case, often the only option available is to generate new data using choice experiments. In the first part of this seminar, Dr. Daina will present pioneering work adopting these techniques to model electric vehicles driver’s charging choices under smart charging. While in the near term e-mobility is and will be dominated by human drivers, on demand e-mobility services delivered by fleets of autonomous vehicles are on the horizon. Therefore, in the second part of this talk, he will present recent work on reinforcement learning approaches to smart charging management of shared autonomous electric vehicle fleets.
Dr. Nicolò Daina is a Research Scientist in the Department of Civil Engineering and Engineering Mechanics and a Research Scholar at the Center on Global Energy Policy at Columbia University. Using data science approaches, econometric techniques and experimentation Dr. Daina seeks to characterize and model the behavior of users of integrated transportation and energy systems. By developing realistic behavioral models and embedding them in systems’ simulation and optimization, Dr. Daina’s research aims to harness the flexibility and the cooperation of end users in both planning and operations of integrated transportation and energy systems as they transition to net-zero. Dr. Daina obtained his PhD in Transport from Imperial College London in 2014. Following his PhD, he worked at Imperial College London’s Department of Civil and Environmental Engineering first as a postdoctoral research associate then as a research fellow. Before moving to Columbia University, Dr. Daina was appointed as a faculty (Chancellor’s Fellow and Lecturer in Transport Policy) at the University of Strathclyde, Glasgow in the United Kingdom. Dr. Daina is currently an Honorary Lecturer in the School of Government and Public Policy of the University of Strathclyde. He is also a member of the US’ Transportation Research Board’s Standing Committee on Alternative Fuels and Technologies.

Student Learning Hub: How to develop a survey using Qualtrics: A step-by-step guide
2022-11-18 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Hella Alnajjar, New York University
Hands-on exercise: Yes
Beginner level: No prior experience required.
Schedule: Friday, November 18, 2022, 1:00pm – 2:00pm
Description: This course is for students who want to learn how to conduct, distribute, and analyze a survey-based study using Qualtrics, a powerful online survey tool, for research purposes. The lesson will include hands-on exercises on how to create sets of questions of various types, import data, set up a display or skip logic for a question, and how to effectively visualize, export and analyze the data collected.

Connected Vehicle Applications: Lessons Learned and Future Research & Deployment Roundtable
2022-11-16 16:00 - 17:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
The USDOT Connected Vehicle (CV) Pilot Program sought to test vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) applications to improve tranportation systems, mobility, and safety with real-world deployments in New York City, Tampa, and Wyoming.
This roundtable discussion will focus on these recently completed connected vehicle pilots and the lessons learned. Our panelists will feature practitioners, decision-makers, and researchers involved in CV deployments and leading the way for their wide-scale adoption.
This roundtable caps off C2SMART’s State of the Field: Connected Vehicle Applictions series, and there will be a synthesis of prior presentations and a discussion on future directions and applications for research, testing, and deployment.
We look forward to your participation!
Panelists:

Sisinnio Concas serves as Program Director at the Center for Urban Transportation Research (CUTR) and Research Associate Professor the University of South Florida (USF) College of Engineering. Dr. Concas has over 20 years of experience as a transportation economist conducting economic impact and benefit-cost analyses for public transportation, airport and roadway projects. Dr. Concas leads CUTR’s Autonomous & Connected Mobility Evaluation (ACME) Program. ACME focuses on producing quick-response solutions to better inform practitioners and policy maker in selecting and prioritizing cost-feasible innovative transportation alternatives. He has performed numerous research projects for the U.S. Federal Transit Administration, Federal Highway Administration, the Florida Department of Transportation, state and local transportation authorities. Dr. Concas leads the Performance Measurement Evaluation and Support of the Tampa CV Pilot Deployment.

Dr. Mohamad Talas is the Deputy Director of ITS System Engineering, New York City Department of Transportation. He brings long standing career experience in traffic engineering and continue with over 27 years in Traffic Engineering and Operation experience in New York City Department of Transportation. He currently serves as the Director for the NYC Department of Transportation ITS project Management, Research and Development where he supervises the Intelligent Transportation System projects and initiatives in New York City. These projects include the development and implementation of the New York City Traffic Computerization System at the Traffic Management Center modernizing and operating over 12,000 signals and the currently deployed Active Traffic Management System in in Manhattan(Midtown In Motion) and NYC Connected Vehicle Pilot Deployment. He has earned his PhD in Transportation Planning and Engineering at NYU -Poly University, Master degrees in Transportation, Planning and Engineering and a Masters in Electrical Engineering from Fairleigh Dickinson University.

Billy Chupp is a data analyst and engineer at the U.S. Department of Transportation’s Volpe Transportation Systems Center in Cambridge, Massachusetts. Mr. Chupp supports a wide range of projects at the Volpe Center including cloud database and analysis system development and management for DOT’s Chief Data Officer, artificial intelligence and machine learning development initiatives for DOT’s ITS Joint Program Office, and air quality modeling and data analysis projects for the Federal Highway Administration. Mr. Chupp most recently served as the technical lead on Volpe’s independent safety evaluation effort for the three connected vehicle pilot programs in New York City, Tampa, and Wyoming, and continues to support the ITS JPO on data documentation and strategy efforts within the connected vehicle space and beyond.

Dr. Karl Wunderlich holds a joint appointment at Noblis in Washington, DC., serving as both is the Director of the Surface Transportation Division and the Director of the Noblis Autonomous Systems Research Center. He is a key contributor to both research and development projects and technology deployment programs sponsored by the US Department of Transportation (USDOT) and the Federal Highway Administration (FHWA). Dr. Wunderlich is an expert in the use of simulation techniques to evaluate the potential impact of emerging technologies to improve traveler mobility or system productivity – including vehicle connectivity, autonomy, and blockchain. He is a published author and patent-holder in orchestrated autonomy, which leverages blockchain to create efficient and collision-free path planning among heterogenous, unfamiliar, and autonomous machines. Dr. Wunderlich holds a Ph.D. in Operations Research from the University of Michigan.
Dr. Kaan Ozbay is a Professor at New York University’s Tandon School of Engineering, and Director of C2SMART Center, a Tier 1 USDOT University Transportation Center. Dr. Ozbay served as Principal Investigator (PI) of the NYU/C2SMART team as part of the NYCDOT-led New York City Connected Vehicle Pilot, under USDOT’s Connected Vehicle Pilot Program. He joined NYU’s Department of Civil and Urban Engineering and Center for Urban Science and Progress (CUSP) in August 2013, and is also Global Network Professor of Civil and Urban Engineering, NYU Abu Dhabi (NYUAD) and Global Network Professor of Engineering and Computer Science, NYU Shanghai (NYUSH).
Moderated by:
Jingqin (Jannie) Gao completed her Ph.D. in Transportation Planning and Engineering at NYU Tandon, where she works with C2SMART Director Kaan Ozbay. She studied Science and Technology of Optical Information and received her B.S. from Tongji University in China and her M.S in Transportation Planning and Engineering from New York University. Her research interests lie in offline and real-time simulation modeling, big data and machine learning approach for transportation, and transportation economics. She also worked for the New York City Department of Transportation on modeling and data analysis to support the agency’s internal planning, technical review processes and coordinated with external agencies on regional projects since 2012. Jingqin is the former president of NYU’s joint Institute of Transportation Engineers (ITE) and The Intelligent Transportation Society of America (ITS) Student Chapter during 2018-2019, through which she organized various company visits, tech talks, women in transportation events and the 2019 ITE Northeastern District Traffic Bowl.

Student Learning Hub: Machine learning and Deep learning approaches in bridge degradation modeling and forecasting
2022-11-11 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Zhanhang Li, Rutgers University
Hands-on exercise: Yes
Level: No prior experience required.
Schedule: Wednesday, November 11, 2022, 1:00pm – 2:00pm
Description: This course will provide students with a foundational understanding of machine learning models and degradation processes. With the bridge degradation modeling case study, students will learn about different types of neural networks, their strengths, and context of application. Case studies and live demos will be provided using Artificial Neural Network (ANN) (Multilayer Perceptron [MLP]) and Convolutional neural network (CNN) for bridge rebar degradation modeling.

Workshop: Defining Flood Risk Metrics to Place FloodNet Sensors in New York City
2022-11-10 09:00 - 13:00 | 370 Jay Street, Room 1201, 370 Jay Street, Brooklyn, 11201
Inland and coastal floods caused by severe weather events have always been a threat for New York City (NYC). Only last year, Hurricane Ida brought massive precipitation to the city, shattering historical records for single-hour rainfall. Hurricane Ida’s precipitation exceeded the stormwater network’s capacity, ultimately flooding streets, subways, and homes, and tragically taking the lives of 13 New Yorkers.
The NYU Disaster Risk Analysis Lab, FloodNet Team, and the NYC Mayor’s Office of Climate and Environmental Justice are working together to identify NYC’s areas with the highest flood risk to help NYC place FloodNet sensors. NYC FloodNet is a flood data collection program for real-time street-level flood information to city agencies, residents, emergency response teams, and researchers. The city has already installed 29 FloodNet sensors and will install another 500 in priority areas citywide over the next five years.
This workshop will bring together multiple stakeholders to help the city prioritize the areas for deploying NYC FloodNet sensors. To prioritize these areas, we invite emergency responders, city officers, researchers, and disaster risk specialists to propose, discuss, and assess comprehensive risk metrics with a thorough consideration of equity for our communities. By combining multiple stakeholders’ perspectives, we will create a wider picture of flood impacts on the city, assigning a scale of importance to the different risk and equity metrics. The workshop will also be an opportunity to explore how FloodNet sensors can help support many other uses for flood risk management and mitigation to build a more resilient and equitable NYC.
This workshop is sponsored by the NYU Connected Cities with Smart Transportation (C2SMART) Center.
Workshop Schedule
9:00 – 10:00 Presentations
● Welcome
● Overview of Flood Risk in New York City
● Overview of FloodNet Initiative
● Stormwater Resiliency Plan
10:00 – 10:15 Icebreaker activity
A brief activity for self introduction and familiarization among the participants.
10:15 – 11:45 Brainstorming and moderated discussion on three main topics:
● Quantitative risk assessment for floods in New York City
● Equity and environmental justice
● FloodNet data collection and usage
11:50 – 12:30 Quantitative Exercise: Analytic Hierarchy Process (AHP)
Individual ranking exercise of available quantitative metrics to assess flood risk in New York City.

Simulation-Based Safety Evaluation Framework for Connected Vehicle Applications for Safety And Operational Measures
2022-11-09 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Proper calibration process is key for traffic safety evaluations using simulation models. Allowing for a with and without comparison under controlled environment that is not directly testable in the field, microsimulation-based approach has drawn considerable attention for the performance evaluation of emerging technologies, including connected vehicle (CV) safety applications. Different from the traditional approaches to evaluate mobility impacts, safety evaluations of such applications demand the simulation models to be well calibrated to match real-world safety conditions. This seminar will present a novel calibration framework which combines traffic conflict techniques and multi-objective stochastic optimization to calibrate the operational and safety measures simultaneously. The conflict distribution of different severity levels categorized by time-to-collision (TTC) is applied as the safety performance measure. Simultaneous perturbation stochastic approximation (SPSA) algorithm, which can efficiently approximate the gradient of the multi-objective stochastic loss function, is used for model parameters optimization that minimizes the total simulation error of both operational and safety performance measures. A case study will be demonstrated by calibrating a microscopic simulation model to evaluate CV safety applications as a part of the NYC Connected Vehicle Pilot Deployment Program.
Speaker:
Dr. Kaan Ozbay is a Professor at New York University’s Tandon School of Engineering, and Director of C2SMART Center, a Tier 1 USDOT University Transportation Center. Dr. Ozbay served as Principal Investigator (PI) of the NYU/C2SMART team as part of the NYCDOT-led New York City Connected Vehicle Pilot, under USDOT’s Connected Vehicle Pilot Program. He joined NYU’s Department of Civil and Urban Engineering and Center for Urban Science and Progress (CUSP) in August 2013, and is also Global Network Professor of Civil and Urban Engineering, NYU Abu Dhabi (NYUAD) and Global Network Professor of Engineering and Computer Science, NYU Shanghai (NYUSH).

Student Learning Hub: Everything you need to know about digital twins: Building a campus model
2022-11-04 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Talha Azfar, Ph.D Candidate at UTEP
Hands-on exercise: Yes
Level: No prior experience required.
Schedule: Friday, November 4, 2022, 1:00pm – 2:00pm
Description: Realistic digital geographical models of real-world locations are a necessary starting point for digital twin applications, especially for simulation and visualization. This presentation will cover efficient and convenient procedures to create a 3D digital model of the UTEP campus along with the road network on the Unreal Engine project for CARLA, a driving simulator. This can enable applications like computer vision, traffic simulation, and autonomous driving experimentation. It can serve as a testbed for connected sensors and synchronized databases towards a complete digital twin.

Deluge Data, Data Deluge
2022-11-02 16:00 - 17:00 | 370 Jay Street, Room 825, 370 Jay Street, Room 1201, New York City, NY, 11201, United States
Virtual Sessions: October 19th, 26th and November 2nd, 2022
In person symposium @ Tandon School of Engineering, NYU (Brooklyn Campus): November 4th, 2022
Register for all sessions here

The FloodNet Consortium is pleased to host Deluge Data, Data Deluge, an online talk series and in-person symposium that brings critical perspectives from the humanities and arts into dialogue with engineering and data practitioners engaged in flood sensing. The online talks will be held over three weeks, culminating in an in-person day-long symposium held at New York University’s Brooklyn campus in fall of 2022.
Climate change in New York City means a future of flooding. With sea level rise and increasingly intense rainstorms, flooding is expected to have an outsized influence on public health, infrastructure, and mobility in urban areas. One response to this growing challenge is improving the city’s data collection capacities through the construction of a city wide flood sensor network, capable of providing real time, hyperlocal flood data. In this symposium we consider flooding as a signal of a rapidly changing environment to ask, what does it mean for flooding to become digitally sensed? We aim to explore the following questions:

What does data do? What are the potentials and limitations of data-driven technologies and practices in climate change response, adaptation and resilience? How does the way it is produced, presented and shared shape how cities manage present day and coming environmental change?
What role can data play to engage different publics with issues of flooding and climate emergency responsiveness? How are different publics already engaging with these technologies and data? How can data catalyze public engagement in new ways? How are data-driven technologies reshaping issues of equity and justice in flood response?
How can we bring critical perspectives from the humanities and arts into dialogue with engineering and data practitioners? This event aims to catalyze a dialogue between theory and practice
What are principles and pathways for building public engagement with flood data?

Sponsors
This event is supported by the Alfred P. Sloan Foundation, the Department of Integrated Design and Media, New York University and the Advanced Science Research Center at the City University of New York.

Organizing Team

Tega Brain is an artist, researcher and environmental engineer. She investigates implications of emerging computational technologies on how the environment is understood and imagined. She is an Industry Associate Professor in the department of Technology, Culture and Society, NYU Tandon School of Engineering.

Elizabeth Hénaff is a computational biologist and an artist investigating the way living beings interact with their environment, with a focus on the ubiquitous and invisible microbial component of our environment. She is an Assistant Professor in the department of Technology, Culture and Society, NYU Tandon School of Engineering.

Kendra Krueger is an intersectional scientist, educator, artist and woman of color on many edges. She is the STEM Outreach and Education Manager at CUNY’s Advanced Science Research Center, where she has also founded The Community Sensor Lab as a space for DIY community science and advocacy.

Hannah Eisler Burnett is an anthropologist who studies water and the people who live and work alongside its shifting boundaries. She is a Postdoctoral Fellow with the FloodNet Project in the department of Technology, Culture and Society, NYU Tandon School of Engineering.

Student Learning Hub: Diving into open data - What is available and how to use them for transportation research
2022-10-26 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Instructor: Hector Landes, New York University
Hands-on exercise: Yes
Level: No prior experience required.
Schedule: Wednesday October 26, 2022, 1:00pm – 2:00pm
Description: This course will be a general introduction to how to use open data for transportation projects. It will start with a short lecture to introduce open-data sources and software to use for data engineering with a focus on demographic, traffic, economic, and safety data. The second part will be a tutorial on how to retrieve data from these sources, how to clean them, manipulate them, and finally visualize them. Finally, this course will also cover how to troubleshoot during data pre-processing and how to overcome an error in either the code or the data. Hands-on exercises on how to use Excel, Tableau, Jupyter Notebook, and QGIS to process the data will be presented.

Assisting Pedestrians with Vision Disabilities in Navigating Urban Streets – Lessons Learned from the NYC Connected Vehicle Pilot Mobile Accessible Pedestrian Signal System
2022-10-25 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
New York City is piloting connected vehicle (CV) technology to support the Vision Zero initiative and help eliminate injuries and fatalities caused by crashes. In Manhattan, 73% of all crash fatalities involve pedestrians while this figure is only 14% nationwide. As a part of the USDOT CV Pilot Deployment Program, two pedestrian oriented applications are deployed: 1) a generalized warning to vehicles of pedestrians in the roadway based on thermal imaging detection and 2) a Mobile Accessible Pedestrian Signal System (PED-SIG) application to assist pedestrians with vision disabilities. The PED-SIG application supports cellular communications to receive localized Signal Phase and Timing (SPaT) and MAP messages broadcast by the local Roadside Unit (RSU) to provides audio alerts and haptic prompts to assist pedestrians with vision disabilities in safely crossing streets at instrumented intersections. Volunteer participants with vision disabilities were recruited to participate in the field tests where Personal Information Devices (PIDs) were given to participants. This seminar will present how the pedestrian application was designed, deployed and tested along with several valuable lessons learned throughout the deployment.
Speaker:
Dr. Jingqin (Jannie) Gao is currently working as a senior research associate at C2SMART University Transportation Center funded by the US Department of Transportation. She received her Ph.D. and M.S. in Transportation Planning and Engineering from New York University, and her B.S. in Science and Technology of Optical Information from Tongji University. Her research interests lie in emerging technologies with emphasis on connected and automated vehicles, accessible transportation, big data and artificial intelligence solutions for transportation, traffic simulation modeling, and parking management. She was one of the lead researchers in evaluating the performance of the New York City Connected Vehicle Pilot Deploymentand and testing the mobile accessible pedestrian application. Before joining NYU, she worked for the New York City Department of Transportation on modeling and data analysis to support the agency’s internal planning and technical review processes. Jingqin plays a leadership role both within her research group and for the larger NYU Tandon community, serving as the past president of the student chapters of the Institute of Transportation Engineers and the Intelligent Transportation Society.
