Real-time estimation of transit OD patterns and delays using low cost-ubiquitous advanced technologies.
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2017-04-01
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Abstract:The main objective of this project is to develop and conduct limited testing of novel sensors using Bluetooth technology ; (BT) to estimate OD demands and station wait times for users of public transit stations. The NYU research team tested the ; feasibility of the utilization of sensors with Bluetooth technology to estimate Origin-Destination (OD) demands and station waittimes ; of users of transit systems with a focus on subway systems. For example, if the entrance and exit turnstiles at subway stations ; were equipped with this type of sensors, it is possible to capture OD information for some of the riders with activated devices. ; 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 mitigate cost, among other benefits. The proposed method of tracking ; Bluetooth IDs uses inexpensive, small, and easy to deploy wireless detectors / readers with specialized software developed by the ; research team. This is a low-cost and viable alternative to traditionally used surveys or other advanced technologies. ; Following a literature review and device testing, a series of one-day pilot tests are 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 day to ; one week indoor tests are conducted with continuous data collection and monitoring to assess the feasibility and usefulness of longterm ; data collection using the proposed sensor technology. Two software tools to post process the collected data and to perform ; self-diagnosis and remote data acquisition functions are developed as part of the overall research project. The results and ; recommendations are provided to the MTA and other interested transit agencies.
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Main Document Checksum:urn:sha-512:f741a1d78ac769e886a8a8087004fb891962d6f5134c6e54dbdc0a1960897ffdba24679caa697efc494722e923e115495f181635caab37b2d603586dbc0f9577