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 Although some of this technology may be outdated, efforts to modernize are often hindered by budgetary limits, competing priorities, and managing the tradeoff between short-term service disruptions and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.

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.

Unemployed Needn’t Apply: Unemployment Status, Legislation, and Interview Requests

2019 ◽  
Vol 46 (8) ◽  
pp. 1380-1407 ◽  
Author(s):  
Tiffany M. Trzebiatowski ◽  
Connie R. Wanberg ◽  
Karyn Dossinger
Keyword(s):  
New York ◽  
New York City ◽  
Los Angeles ◽  
Job Search ◽  
York City ◽  
Self Report ◽  
Short Term ◽  
Search And Selection ◽  
Job Postings

This research investigates whether and when a job applicant’s unemployment status (i.e., employed, short-term unemployed, or long-term unemployed) affects the probability of receiving an interview request by examining interview request rates in the presence of versus absence of unemployment status antidiscrimination legislation. In response to 3,335 fictitious resumes sent to 1,237 online job postings in Los Angeles and New York City, we received an overall interview request rate of 10.37. Long-term unemployed applicants were less likely to receive an interview request than short-term unemployed applicants in Los Angeles but not in New York City, which has unemployment status antidiscrimination legislation. These findings are supplemented with self-report survey data about perceptions of the unemployed from 200 hiring personnel in New York City and Los Angeles. Practical and theoretical implications are discussed for the unemployment, job search, and selection literatures.

Short-term forecast model of taxi demand based on time and space heterogeneity

2021 ◽  
pp. 1-12
Author(s):  
Zhiyu Yan ◽  
Shuang Lv
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Urban Traffic ◽  
Percentage Error ◽  
Density Level ◽  
Traffic Data ◽  
Short Term ◽  
Time And Space ◽  
Density Data

Accurate prediction of traffic flow is of great significance for alleviating urban traffic congestions. Most previous studies used historical traffic data, in which only one model or algorithm was adopted by the whole prediction space and the differences in various regions were ignored. In this context, based on time and space heterogeneity, a Classification and Regression Trees-K-Nearest Neighbor (CART-KNN) Hybrid Prediction model was proposed to predict short-term taxi demand. Firstly, a concentric partitioning method was applied to divide the test area into discrete small areas according to its boarding density level. Then the CART model was used to divide the dataset of each area according to its temporal characteristics, and KNN was established for each subset by using the corresponding boarding density data to estimate the parameters of the KNN model. Finally, the proposed method was tested on the New York City Taxi and Limousine Commission (TLC) data, and the traditional KNN model, backpropagation (BP) neural network, long-short term memory model (LSTM) were used to compare with the proposed CART-KNN model. The selected models were used to predict the demand for taxis in New York City, and the Kriging Interpolation was used to obtain all the regional predictions. From the results, it can be suggested that the proposed CART-KNN model performed better than other general models by showing smaller mean absolute percentage error (MAPE) and root mean square error (RMSE) value. The improvement of prediction accuracy of CART-KNN model is helpful to understand the regional demand pattern to partition the boarding density data from the time and space dimensions. The partition method can be extended into many models using traffic data.

Patterns of waste generation: A gradient boosting model for short-term waste prediction in New York City

2017 ◽  
Vol 62 ◽  
pp. 3-11 ◽  
Author(s):  
Nicholas E. Johnson ◽  
Olga Ianiuk ◽  
Daniel Cazap ◽  
Linglan Liu ◽  
Daniel Starobin ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Gradient Boosting ◽  
Waste Generation ◽  
Short Term

Long-Term Outcomes of an Abstinence-Based, Small-Group Pregnancy Prevention Program in New York City Schools

2000 ◽  
Vol 32 (5) ◽  
pp. 237 ◽  
Author(s):  
Lisa D. Lieberman ◽  
Heather Gray ◽  
Megan Wier ◽  
Renee Fiorentino ◽  
Patricia Maloney
Keyword(s):  
New York ◽  
New York City ◽  
Small Group ◽  
York City ◽  
Prevention Program ◽  
Pregnancy Prevention ◽  
Long Term Outcomes ◽  
Pregnancy Prevention Program ◽  
City Schools

Building-level analyses to prospectively detect influenza outbreaks in long-term care facilities: New York City, 2013-2014

2015 ◽  
Vol 43 (8) ◽  
pp. 839-843 ◽  
Author(s):  
Alison Levin-Rector ◽  
Beth Nivin ◽  
Alice Yeung ◽  
Annie D. Fine ◽  
Sharon K. Greene
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Long Term Care ◽  
Term Care ◽  
Care Facilities ◽  
Influenza Outbreaks ◽  
Building Level

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 (...

The transition from injection to non-injection drug use: long-term outcomes among heroin and cocaine users in New York City

Addiction ◽  
2007 ◽  
Vol 102 (5) ◽  
pp. 778-785 ◽  
Author(s):  
Don C. Des Jarlais ◽  
Kamyar Arasteh ◽  
Theresa Perlis ◽  
Holly Hagan ◽  
Douglas D. Heckathorn ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Drug Use ◽  
Injection Drug Use ◽  
York City ◽  
Injection Drug ◽  
Long Term Outcomes ◽  
Cocaine Users
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