scholarly journals Nowcasting for Real-Time COVID-19 Tracking in New York City: Evaluation Study Using Reportable Disease Data From the Early Stages of the Pandemic (Preprint)

10.2196/25538 ◽  
2020 ◽  
Author(s):  
Sharon K Greene ◽  
Sarah F McGough ◽  
Gretchen M Culp ◽  
Laura E Graf ◽  
Marc Lipsitch ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Real Time ◽  
York City ◽  
Evaluation Study ◽  
Early Stages

A Conversation and Two Epilogues

2016 ◽  
Author(s):  
Judy Malloy
Keyword(s):  
New York ◽  
New York City ◽  
Los Angeles ◽  
Real Time ◽  
York City ◽  
Cultural Centers ◽  
Main Street ◽  
The World ◽  
As If

When Kit Galloway and Sherrie Rabinowitz arrived in Telluride for Tele-Community in the summer of 1993, it seemed as if the whole town joined them on Main Street, as using slow scan video they connected townspeople and visiting digerati with artists, universities, and cultural centers around the world. Their Electronic Café had already presented New York City pedestrians with display windows of people waving and talking real time from Los Angeles (...

Planning from the Bottom Up

Last Subway ◽  
2020 ◽  
pp. 124-156
Author(s):  
Philip Mark Plotch
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
System Capacity ◽  
Bottom Up ◽  
Early Stages ◽  
System Increase ◽  
Subway System ◽  
Rail Service

This chapter recounts how New York City Transit Authority rail service planners Peter Cafiero, Chuck Kirchner, Glenn Lunden, and Jon Melnick resurrected the Second Avenue subway in 1988. Even though the Transit Authority was in the early stages of its 1987–91 capital program, the planners' bosses wanted to start getting ready for the next program, which would run from 1992 to 1996. The first step would be to create a document that assessed the authority's long-term needs and identified projects that would rehabilitate the subway system, increase ridership, improve productivity, and expand system capacity. One proposal the planners wrote to address the Lexington Avenue's problems was an idea that the MTA planner Bob Olmsted had first championed in 1975—a Second Avenue subway north of 63rd Street. As the Second Avenue subway proposal moved up the Transit Authority hierarchy, the authority's president, David Gunn, agreed that the time was right to begin thinking about expanding the subway system. Before he could devote significant resources to advancing the Second Avenue subway, however, it would have to compete with other potential megaprojects under discussion at the MTA's agencies.

Real-Time Measurements of SO2, H2CO, and CH4Emissions from In-Use Curbside Passenger Buses in New York City Using a Chase Vehicle

2005 ◽  
Vol 39 (20) ◽  
pp. 7984-7990 ◽  
Author(s):  
Scott C. Herndon ◽  
Joanne H. Shorter ◽  
Mark S. Zahniser ◽  
Joda Wormhoudt ◽  
David D. Nelson ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Real Time ◽  
York City

Automated Train Identification and Train Position Monitoring at New York City Transit

2020 ◽  
Vol 2674 (9) ◽  
pp. 843-854
Author(s):  
Shay Lehmann ◽  
Alla Reddy ◽  
Chan Samsundar ◽  
Tuan Huynh
Keyword(s):  
New York ◽  
New York City ◽  
Real Time ◽  
York City ◽  
Service Management ◽  
Short Term ◽  
Subway System ◽  
Competing Priorities ◽  
Position Monitoring

Like any legacy subway system that first opened in the early 1900s, the New York City subway system operates using technology that dates from many different eras. Although some of this technology may be outdated, efforts to modernize are often hindered by budgetary limits, competing priorities, and managing the tradeoff between short-term service disruptions and long-term service improvements. At New York City Transit (NYCT), the locations of all trains on all lines are not visible to any one person in any one place and, for much of the system, train locations can only be seen at field towers for the handful of interlockings in its operational jurisdiction as result of the legacy signal system, which may come as a surprise to many daily commuters or personnel at newer metros. In 2019, developers at NYCT gained full access to the legacy signal system’s underlying track circuit occupancy data and developed an algorithm to automatically track trains and match these data with schedules and manual dispatchers’ logs in real time. This data-driven solution enables real-time train identification and tracking long before a full system modernization could be completed. This information is being provided to select personnel as part of a pilot program via several different tools with the aim of improving service management and reporting.

Real-Time Measurements of Nitrogen Oxide Emissions from In-Use New York City Transit Buses Using a Chase Vehicle

2005 ◽  
Vol 39 (20) ◽  
pp. 7991-8000 ◽  
Author(s):  
Joanne H. Shorter ◽  
Scott Herndon ◽  
Mark S. Zahniser ◽  
David D. Nelson ◽  
Joda Wormhoudt ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Nitrogen Oxide ◽  
Real Time ◽  
York City ◽  
Nitrogen Oxide Emissions ◽  
Transit Buses

Real-Time Estimation of Platform Crowding for New York City Subway: Case Study at Wall Street Station on No. 2 and No. 3 Lines in Financial District

2017 ◽  
Vol 2648 (1) ◽  
pp. 68-78 ◽  
Author(s):  
Adam Caspari ◽  
Brian Levine ◽  
Jeffrey Hanft ◽  
Alla Reddy
Keyword(s):  
New York ◽  
New York City ◽  
Real Time ◽  
York City ◽  
Time Estimation ◽  
Time Of Day ◽  
Time Data ◽  
Wall Street ◽  
Time Model ◽  
Control Center

Amid significant increases in ridership (9.8% over the past 5 years) on the more than 100 year-old New York City Transit (NYCT) subway system, NYCT has become aware of increased crowding on station platforms. Because of limited platform capacity, platforms become crowded even during minor service disruptions. A real-time model was developed to estimate crowding conditions and to predict crowding for 15 min into the future. The algorithm combined historical automated fare collection data on passenger entry used to forecast station entrance, automated fare collection origin–destination inference information used to assign incoming passengers to a particular direction and line by time of day, and general transit feed specification–real time data to determine predicted train arrival times used to assign passengers on the platform to an incoming train. This model was piloted at the Wall Street Station on the No. 2 and No. 3 Lines in New York City’s Financial District, which serves an average 28,000 weekday riders, and validated with extensive field checks. A dashboard was developed to display this information graphically and visually in real time. On the basis of predictions of gaps in service and, consequently, high levels of crowding, dispatchers at NYCT’s Rail Control Center can alter service by holding a train or skipping several stops to alleviate any crowding conditions and provide safe and reliable service in these situations.

Development of a Real-Time Stringlines Tool to Visualize Subway Operations and Manage Service at New York City Transit

2015 ◽  
Vol 2538 (1) ◽  
pp. 19-29 ◽  
Author(s):  
Boris Suchkov ◽  
Mikhail Boguslavsky ◽  
Alla Reddy
Keyword(s):  
New York ◽  
New York City ◽  
Real Time ◽  
York City
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