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Transit Techies #13: Projects on Bike Safety & Infrastructure with NYU Tandon
2023-02-06 17:45 - 19:30 (America/New_York) | 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.

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

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.

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.

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!)

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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/.

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)

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
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: Autonomous Vehicle Good Citizenry Standard
2023-06-29 12:00 - 13:00
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.

Transit Techies July Meetup
2023-07-17 18:00 - 19:30
Technologists who love transit.
Transit enthusiasts who hack!
At Transit Techies NYC, speakers present transit-related projects. Presenters may be household hackers, data scientists, researchers, product developers, or you! All presentations will be technical and awesome.

Webinar: Exploring Cost-effective Computer Vision Solutions for Smart Transportation Systems: Urban Work Zone Detection and Safety Analysis Using Near Miss Data
2023-07-25 12:00 - 13:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
Jingqin Gao: Assistant Director of Research, C2SMART, NYU; Chuan Xu: PHD Candidate, NYU
Tuesday, July 25, 2023 | 12:00pm ET | Virtual
While computer vision technology is widely acknowledged, it remains underutilized for routine operations and traffic safety in complex urban environments. Our research develops a deep learning-based, automatic data acquisition and analytics approach utilizing vision-based sensors. This approach harnesses data from existing transportation infrastructure and connected and automated vehicles (CAVs), illustrating how computer vision can create fresh streams of mobility and safety information for strategic planning and operations. It presents two applications: WorkZoneX, leveraging 900+ traffic cameras in NYC for real-time urban work zone identification and size estimation, and SAFExMAP, a risk indicator scoring system using near-miss data from in-vehicle cameras. Findings suggest significant potential for computer vision in smart cities, offering cost-effective solutions to improve planning, operations and traffic safety analysis.

Summer Webinar Series: A Variational Autoencoder Approach for Route Choice Set Generation
2023-08-03 14:00 - 15:00
In the context of route choice modeling, choice set generation is a challenging task, since the consideration set is generally unknown to the modelers, and the full choice set cannot be enumerated in real size networks. The proposed variational autoencoder approach (VAE) is motivated by the idea that the chosen alternatives must belong to the consideration set. The VAE approach explicitly considers maximizing the likelihood of including the chosen alternatives in the choice set, and infers the underlying generation process. The VAE approach for route choice set generation is exemplified using a real dataset. VAE-CNL model has the best performance in terms of goodness-of-fit and prediction performance, compared to models estimated with conventionally generated choice sets.
Shlomo Bekhor is a professor in the Faculty of Civil and Environmental Engineering at the Technion – Israel Institute of Technology, and serving as Faculty Dean since 2019. He has a BSc in Aeronautical Engineering from ITA, Sao Jose dos Campos, Brazil. MSc and PhD degrees in Transportation Engineering were obtained at the Technion. He teaches and conducts research in transportation planning and network equilibrium models and has special interest in route choice modeling.
Presented by the Transportation Research Board Subcommittee AEP30(2)/AEP40 on Route Choice and Spatio-Temporal Behavior

Digital Twin Technologies Towards Understanding the Interactions between Transportation and other Civil Infrastructure Systems: Phase 2
2023-08-14 12:00 - 13:00 | https://nyu.zoom.us/webinar/register/WN_jQg9UllxRB26w9QmMn9OqQ

The Reconstruction of Penn Station
2023-08-15 12:00 - 13:30
Please join the NYU Rudin Center for Transportation for an illuminating presentation on the reconstruction of Penn Station, led by Jamie Torres-Springer, President, MTA Construction & Development. Delve into the planned transformation of this essential hub. The presentation will be followed by a conversation between Jamie Torres-Springer and Sarah Kaufman.

C2SMARTER RFP Requirements Webinar
2023-08-16 12:00 - 13:00
The purpose of the webinar is to inform prospective PIs and research teams on the new requirements of C2SMARTER Center projects, answer any questions, and provide a forum for potential team-building collaboration. The topics we will cover include:

Feedback on received project abstracts and potential teaming opportunities
Proposal submission requirements
New USDOT reporting requirements
Project management and tracking systems
Timelines and schedules
Q&A

PhD New Student Orientation
2023-08-24 | C2SMART Center Viz Lab, 6 Metrotech Center, Room 460, Brooklyn, 11201

Highlights of Lane-Free Automated Vehicle Traffic with Nudging
2023-09-01 13:00 - 14:00 | Virtual, 6 MetroTech Center, Brooklyn, NY, 11201, United States
A novel paradigm (named TrafficFluid) for vehicular traffic in the era of connected and automated vehicles (CAVs) was recently proposed, which is based on two combined principles. The first principle is lane-free traffic, which renders the driving task for CAVs smoother and safer, as risky lane-changing manoeuvres become obsolete; increases the capacity of the roadway due to increased road occupancy; and mitigates congestion-triggering vehicle
manoeuvres. Also, lane-free CAV traffic implies that incremental road widening (narrowing) leads to corresponding incremental increase (decrease) of capacity, and this opens the way for real-time internal boundary control on highways and arterials to flexibly share the total (both directions) road width and capacity among the two traffic directions in dependence of the bi-directional traffic conditions, so as to maximize the total system efficiency. The second principle is vehicle nudging, whereby vehicles may be influencing other vehicles in front of them; this allows for traffic flow to be freed from the anisotropy restriction, which stems from the fact that human driving is influenced only by downstream vehicles. Nudging leads to improved traffic flow capacity and stability.
After presenting the TrafficFluid motivation and general features, some highlights of related work will be outlined, such as: Nonlinear feedback control of CAV in lane-free traffic with nudging; Optimal path planning for individual vehicles and vehicle groups; Emerging macroscopic traffic flow modeling; Internal boundary control; Driving on large-scale lane-free roundabouts (Place Charles de Gaulle in Paris). See www.trafficfluid.tuc.gr

NY Statewide Behavioral Impact Decision Support Tool with Replica
2023-09-07 12:00 - 13:00
One of the enduring challenges in statewide transportation planning is that consistent population travel data remains scarce. This is changing with the availability of large-scale ICT data. A one-year project was initiated to develop a behavioral impact decision support tool based on NY statewide synthetic population data provided by Replica Inc. First, a NY statewide model choice model is developed to deterministically fit heterogeneous coefficients for trips along each census block-group OD pair, called group-level agent-based mixed (GLAM) logit. Considerations were made for four population segments, six trip modes, and twelve attributes. Second, a decision support tool for statewide mobility service region design was proposed. The tool is based on an assortment optimization problem with agent-specific coefficients and linear constraints, which can be efficiently solved through linear or quadratic programming (depending on variant). The decision support tool is applied to optimize service regions with one of the three objectives: (1) maximizing the total revenue; (2) maximizing the total change of consumer surplus; (3) minimizing the disparity between communities.
Presented by Xiyuan Ren; PHD Candidate, NYU; Joseph Chow, Associate Professor, NYU

ECE Seminar: Boundary Stabilization of Polynomial Reaction Diffusion Equations
2023-09-14 14:30 - 15:30 | 370 Jay Street, Room 1013, 370 Jay Street, Brooklyn
We show how to stabilize a polynomial reaction diffusion system using boundary control, integration by parts, completing the square and an infinite dimensional extension of Al’brekht’s method.
Presented by Alfred J. Krener.
