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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Commercial Package Delivery through Public Transportation Systems in Rural States</title>
      <link>https://rip.trb.org/View/1714623</link>
      <description><![CDATA[The purpose of this project is to provide the Small Urban, Rural and Tribal Center on Mobility with additional information and greater understanding of the feasibility of last mile package delivery for commercial entities via public transportation in rural areas.
This project will investigate innovative “last mile” package delivery systems and how rural public transportation systems may have a role in the process.  It will include a synthesis of current last mile package delivery practices in public transportation systems in rural states; an analysis of state policies regarding the use of public transportation for package delivery; and an estimate of demand, capacity need, and revenue generation for rural transit systems in regard to last mile package delivery.  This feasibility study will also include recommendations for policy and planning.]]></description>
      <pubDate>Wed, 10 Feb 2021 14:00:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/1714623</guid>
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      <title>Indiana State Highway Cost Allocation and Revenue Attribution Study/Estimation of Travel by Out-of-State Vehicles on Indiana Highways</title>
      <link>https://rip.trb.org/View/1362673</link>
      <description><![CDATA[The project will develop a methodology for allocating highway costs and attributing revenues to all vehicle classes. The results will provide a clear quantitative understanding of the extent of costs incurred by various vehicle classes and the revenues they contribute. This understanding will allow an assessment of the appropriateness of types and rates of current taxes and fees and to devise future rates and types to meet the financing needs of coming years. The research will also include a companion study on the estimation of the extent of travel of out-of-state vehicles on Indiana's highways.]]></description>
      <pubDate>Thu, 23 Jul 2015 01:00:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/1362673</guid>
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      <title>Real-time Estimation of Transit Origin-Destination Patterns and Delays Using Low-Cost Ubiquitous Advanced Technologies</title>
      <link>https://rip.trb.org/View/1357759</link>
      <description><![CDATA[The Polytechnic Institute of New York University (NYU Poly) research team proposes utilizing Bluetooth technology to estimate origin-destination demands and station wait times of users of the Metropolitan Transportation Authority (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 Origin-Destination (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 media access control (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 (BT) 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 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 &amp; 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.]]></description>
      <pubDate>Wed, 17 Jun 2015 01:00:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/1357759</guid>
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      <title>Data Acquisition, Detection and Estimation for Structural Health Monitoring</title>
      <link>https://rip.trb.org/View/1314839</link>
      <description><![CDATA[Although using sensor networks for SHM (structural health monitoring) is not a new concept, very few projects have investigated the problems of detection (of defects) and estimation (of damage location) using network-acquired data. In statistics detection and estimation theory were established by assuming the measurement data come with reliable statistics, for instance, the probability of a particular observation. However, such statistics often requires large amount of observations. In wireless sensor networks, data acquisition is a costly operation since wireless sensor networks are both bandwidth and power limited. The amount of measurement data that can be reported to the base station is therefore very limited. Data acquisition from sensor networks has been treated as a trivial subject and often is performed by using fixed-interval sensing and reporting. In this project, we will provide a thorough treatment of sampling, detection and estimation for using sensor network data. Specifically, (a) We will investigate the fundamental sampling issue, particularly, for each type of physical measurement, what is the best sampling rate and whether adaptive sampling is more suitable than uniform sampling. Based on the sampling discipline, the sensing and communication protocols are developed; (2) for structural defect detection, we propose to use the likelihood ratio test method with Bayes criterion and compare it with the basic LRT method; through the detector, we narrow the scope of the defect to be within the spatial interval of some sampling points; (3) once it is concluded that a defect exists, the maximum likelihood estimator is used to further estimate the location of the defect. The algorithms will be validated thorough test bed experiments or simulations.]]></description>
      <pubDate>Thu, 03 Jul 2014 01:01:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/1314839</guid>
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