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Real-time Estimation of Transit Origin-Destination Patterns and Delays Using Low-Cost Ubiquitous Advanced Technologies

The NYU Poly research team proposes utilizing Bluetooth technology to estimate origin-destination demands and station wait times of users of the MTA New York City Subway system. If the entrance and exit turnstiles at subway stations are equipped with Bluetooth receivers, it is possible to capture O-D information for some percentage of the riders with visible Bluetooth devices. The riders who have electronic devices such as most cell phones, iPods, and computers carry unique information in their devices’ Bluetooth MAC address. This information can be used scrambled and used anonymously to detect the origin and destination of riders by matching data collected at entrances and exits from the system. Assuming that visible Bluetooth devices are uniformly distributed among the riders, it is possible to estimate a transit O-D matrix for the entire system not only on a daily basis but also over a time period allowing the agency analyze time-dependent OD demand for different station pairs. Moreover the same BT sensors proposed by the research teams will capture waiting times of the same sample of transit riders at fixed locations in each station. This information will then be converted average hourly, daily, weekly delays that can be used in conjunction with OD matrices.

Estimation of daily and hourly Origin-Destination (OD) demands and delays is important for transit agencies because it can help improve their operations, reduce delays, and save money, among other benefits. As a low-cost and easy to implement alternative to surveys or other advanced technologies, the research team proposes tracking anonymous Bluetooth IDs using inexpensive, small and easy to deploy Bluetooth detectors / readers with specialized software developed by the research team.

Following a literature review and device testing, a series of one-day pilot tests will be conducted in coordination with the MTA to iron out all of the possible hardware and software issues. Following further consultation with the MTA, a full one week to one months test will be conducted with continuous data collection and monitoring to assess the feasibility and usefulness of long-term data collection using the proposed sensor technology. Two software tools to post process the collected data and to perform self Real-time Estimation of Transit Origin-Destination Patterns & Delays Using Low-Cost Ubiquitous Advanced Technologies Region II UTRC 2012-2013 Faculty-Initiated Research Proposal ii diagnosis and remote data acquisition functions will be developed as part of the overall research project. The results and recommendations will be provided to the MTA and other interested transit agencies.

Project Details

Project Type: 
Faculty-Initiated Research
Project Dates: 
June 1, 2014 to December 31, 2015
Principal Investigators: 
Dr. Kaan Ozbay
Dr. Neveen Shlayan
Dr. Hani Nassif
Institution: 
New York University
State University of New York (SUNY)
Rutgers University
Sponsor(s): 
University Transportation Research Center (UTRC)
Publications: 
Final Report
Project Status: 
Complete
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