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    <title>Transport Research International Documentation (TRID)</title>
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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>Transport Research International Documentation (TRID)</title>
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    <item>
      <title>Identifying Transit Corridors With Greatest Potential to Benefit From Transit Signal Priority</title>
      <link>https://trid.trb.org/View/2458928</link>
      <description><![CDATA[Transit signal priority (TSP) is an operational strategy that facilitates the movement of transit vehicles through signal-controlled intersections. Transit vehicle delay can occur for many reasons including traffic congestion, passenger boarding and alighting, traffic signal operations, and other factors but TSP is specifically aimed at reducing delay caused by signal operations. Connected vehicle, or vehicle-to-everything (V2X), technology was deployed on UTA buses and at signalized intersections, thus enabling “smart” TSP on Redwood Road in Salt Lake County (Route 217) and along the UVX bus rapid transit (BRT) line in the Provo-Orem area of Utah. One way to maximize the efficiency of new V2X deployments is to consider locations where TSP will provide the greatest potential benefit to buses; that is, intersections where buses experience large amounts of delay. This research analyzed bus AVL data recorded every 10 seconds for UTA's 17 core routes and counted how often buses stopped at signalized intersections. Results are compiled by individual intersection, transit route, and highway corridor. These findings will help inform UTA's and UDOT's prioritization scheme for new V2X deployments by providing a data-driven and needs-based approach to Utah's V2X planning and deployment practices.]]></description>
      <pubDate>Wed, 27 Nov 2024 13:43:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2458928</guid>
    </item>
    <item>
      <title>Identifying Microtransit Service Areas through Microsimulation</title>
      <link>https://trid.trb.org/View/2107876</link>
      <description><![CDATA[Demand-responsive microtransit services have operated in Utah since a pilot program debuted in Fall 2019. The Utah Transit Authority (UTA) and its partners see such services as providing key mobility in transit- limited areas, but how to prioritize which areas receive such services is an open question. In this research, the authors present a multi-agent daily activity simulation of regional travel demand in the Wasatch Front– using the open-source BEAM simulation developed by Lawrence Berkeley National Laboratory – including on-demand microtransit services. Though unresolved methodological limitations surrounding sample size and choice methodology exist, the simulation the authors develop successfully replicates key indicators of the pilot program including ridership and utilization. An analysis of additional prospective deployment areas suggests that all proposed areas would be successful at the current level of investment. UTA and its partners should prioritize regions that enhance the ability to build multi-modal travel paths and focus on automobile-limited households to maximize system use.]]></description>
      <pubDate>Thu, 23 Feb 2023 09:31:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2107876</guid>
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    <item>
      <title>Utah Transit Authority, Suicide Prevention Research and Demonstration Project</title>
      <link>https://trid.trb.org/View/2096559</link>
      <description><![CDATA[This project proposes to demonstrate an innovative Radar/Camera Surveillance and Detection System that will give early warning so that an operational approach can be implemented to react to trespassers on its FrontRunner commuter and TRAX light rail systems. The system includes PTZ camera, radar, load speaker, and Red/Blue LED lights and connects to  the Rail Control Centers.]]></description>
      <pubDate>Fri, 13 Jan 2023 14:49:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2096559</guid>
    </item>
    <item>
      <title>First-/last-mile experience matters: The influence of the built environment on satisfaction and loyalty among public transit riders</title>
      <link>https://trid.trb.org/View/1873447</link>
      <description><![CDATA[Public transit authorities have enhanced the travel experience to promote ridership and customer loyalty. Previous studies about satisfaction and loyalty of transit riders, however, give less attention to out-of-vehicle environments such as walking/biking routes, transfer comfort, and traffic and crime safety conditions. The first-mile and last-mile problem—distance traveled before and after using transit—is a well-known barrier of transit use, but an empirical study about how people experience it is lacking.Thus, this study aims to explore how transit riders experience out-of-vehicle environments—access, transfer, and egress—and how their experience is related to overall satisfaction and loyalty to transit service. The authors conducted a questionnaire survey of people (n = 445) living in areas served by the Utah Transit Authority and analyzed the responses through an Importance-Satisfaction analysis and a path analysis, a type of structural equation modeling. A descriptive analysis demonstrates complex first-mile travel patterns: driving is the most common mode to start a transit-involved trip (68.5%), and one-third of transit riders transfer more than once before riding on a transit (e.g., driving → walking → transit). Results from the Importance-Satisfaction analysis highlight both traffic and crime safety concerns at transit stops and walking routes as a critical out-of-vehicle element most in need of improvement. A path analysis result confirms that out-of-vehicle environments—in particular, safety and transfer experience—influence customer satisfaction and loyalty more than in-vehicle and system-related factors do. This paper concludes with practical suggestions for multiple agencies (e.g., transit, transportation, and planning agencies), including urban design strategies, land use-transit integration, and multi-modal integration.]]></description>
      <pubDate>Tue, 30 Nov 2021 10:24:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/1873447</guid>
    </item>
    <item>
      <title>Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity</title>
      <link>https://trid.trb.org/View/1844328</link>
      <description><![CDATA[Sustainable development of the transport system has been the consensus around the world for the past decades. Encouraged by the urgent need for cleaner alternatives to fossil fuels, vehicle electrification has been advancing at an unprecedented pace. As a major component of the multimodal transportation system, public transit is at the forefront of adopting battery technology into its operation. Battery Electric Bus (BEB), with superior features such as zero-emission and reduced noise, is made ready for commercial deployment in the past several years. However, it is still a grand challenge to successfully deploy BEB system given the nature of the public transit system and the unique spatio-temporal characteristics of BEB. This research presents a bi-objective optimization model for BEB deployment to consider constraints unique to the BEB system and to address the trade-off between environmental equity for the disadvantaged population and capital investment. The model is further demonstrated using the transit system operated by the Utah Transit Authority (UTA) to offer insights on the benefits gained as a result of BEB deployment. Optimal deployment plans under different budgets are provided to illustrate the effectiveness of the model. The trade-offs in each of the plans are further discussed and compared. This research set the foundation for transit agencies to develop optimal deployment strategies for BEB systems when multiple goals need to be considered, allowing planners and decision-makers to create a transportation ecosystem that better serves livable and sustainable communities.]]></description>
      <pubDate>Tue, 25 May 2021 16:22:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/1844328</guid>
    </item>
    <item>
      <title>Bi-objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity</title>
      <link>https://trid.trb.org/View/1845662</link>
      <description><![CDATA[Public transit, compared with passenger cars, can effectively help conserve energy, reduce air pollution, and optimize flow on roadways. In recent years, Battery Electric Bus (BEB) is receiving an increasing amount of attention from the transit vehicle industry and transit agencies due to recent advances in battery technologies and the direct environmental benefits it can offer (e.g., zero emissions, less noise). However, limited efforts have been attempted on the effective deployment planning of the BEB system due to the unique spatiotemporal features associated with the system itself (e.g., driving range, bus scheduling). In this project, the authors developed an innovative spatiotemporal analytical framework and web-based visualization platform to assist transit agencies in identifying the optimal deployment strategies for the BEB system by using a combination of mathematical programming methods, Geographic Information System (GIS)-based analysis, and multi-objective optimization techniques. The framework allows transit agencies to optimally phase in BEB infrastructure and deploy the BEB system in a way that can minimize the capital and operational cost of the BEB system while maximizing its environmental benefits (i.e., emission reduction). The authors engaged two transit agencies - the Utah Transit Authority (UTA) and TriMet, both in the planning phase of BEB deployment - to evaluate the usability of the platform. The web-based visualization platform operationalizes the framework and makes it accessible to transit planners, decision makers and the public. This project fits the National Institute for Transportation and Communities (NITC) theme on increasing access to opportunities, improving multimodal planning, and developing data, models, and tools for better decision making. The research could help transit agencies develop optimal deployment strategies for BEB systems, allowing planners and decision makers to create transportation systems that better serve livable and sustainable communities.]]></description>
      <pubDate>Mon, 19 Apr 2021 17:19:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/1845662</guid>
    </item>
    <item>
      <title>Transit Signal Progression Algorithm for Supporting Redwood Road Transit Signal Priority (TSP)</title>
      <link>https://trid.trb.org/View/1770734</link>
      <description><![CDATA[In 2017, a connected vehicle (CV) corridor utilizing dedicated short-range communication (DSRC) technology was built along Redwood Road in Salt Lake County, Utah. The main purpose of the CV corridor was to implement transit signal priority (TSP) when a bus is running behind its published schedule. The performance data was generated by the transit vehicles. It was then transmitted through the DSRC system, logged by the traffic signal controller, and coupled with the Utah Transit Authority (UTA) data from the transit operation system. Then, it was analyzed including requested and served TSP, indicating bus reliability, travel time, and running time. To provide better signal coordination for buses, the signal plan for this CV corridor underwent retiming in October 2018. The goal of this project was to compare the TSP performance before and after the signal retiming. The field data of August, September, November, and December 2018 were selected for use in this evaluation. Although some negative impacts of TSP on street traffic are unavoidable in most cases, they can be minimized if the base signal control plan is properly designed. From an operational aspect, the best method for achieving this goal is to support bus progression along the corridor. Hence, another primary goal of this project was to develop a web-based tool to assist UDOT employees to design a signal progression plan to benefit both buses and passenger vehicles. This tool also helps to visualize bus running time, travel time, reliability, the bus served/requested ratio, and bus trajectory.]]></description>
      <pubDate>Fri, 26 Feb 2021 10:00:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/1770734</guid>
    </item>
    <item>
      <title>Another one rides the bus? The connections between bus stop amenities, bus ridership, and ADA paratransit demand</title>
      <link>https://trid.trb.org/View/1695502</link>
      <description><![CDATA[Improving bus stops by providing shelters, seating, signage, and sidewalks is relatively inexpensive and popular among riders and local officials. Making such improvements, however, is not often a priority for U.S. transit providers because of competing demands for capital funds and a perception that amenities are not tied to measurable increases in system effectiveness or efficiency. This study analyzes recent bus stop improvements made by the Utah Transit Authority (UTA) to determine whether, and to what extent, the improvements are associated with changes in stop-level ridership and demand for Americans with Disabilities Act (ADA) paratransit service in the areas immediately surrounding improved bus stops. The study compares ridership and paratransit demand from before and after the improvements at the treated stops and at a set of unimproved stops selected using propensity score matching to control for demographic, land use, and regional accessibility influences. The analysis shows that the improved bus stops are associated with a statistically significant increase in overall ridership and a decrease in paratransit demand, compared to the control group stops. These outcomes are important for transit service providers as they seek to increase overall ridership and reduce costs associated with providing paratransit service.]]></description>
      <pubDate>Mon, 18 May 2020 11:27:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/1695502</guid>
    </item>
    <item>
      <title>Modeling net effects of transit operations on vehicle miles traveled, fuel consumption, carbon dioxide, and criteria air pollutant emissions in a mid-size US metro area: findings from Salt Lake City, UT</title>
      <link>https://trid.trb.org/View/1651034</link>
      <description><![CDATA[The Utah Transit Authority (UTA) serves Utah’s Wasatch Front, a rapidly growing conurbation with a current population of ~1.8 M people. UTA uses an electronic fare collection (EFC) system that requires riders to tap on as they enter a bus or train and tap off as they exit, as well as an automated passenger counter (APC) system that counts interruptions of infrared beams across vehicle doorways as riders board and alight. The authors analyzed EFC and APC data for 2016, along with service schedules and routes from General Transit Feed Specification (GTFS) data, to estimate the impact of UTA on the air quality in its service region by accounting for vehicle miles traveled, gasoline gallons equivalent of fuel consumed, and multiple pollutant species emitted. Buses, light rail, and commuter rail were found to collectively offset approximately 1.5% of the onroad emissions from the counties served by UTA due to transit use replacing single passenger vehicle use. These offsets are not homogeneous; ridership drops significantly (~20%–50% depending on the mode) during the summer months as some of the largest users are educational institutions with noticeable seasonal cycles. Low transit use during the weekend negates some of the air quality benefits as buses and trains travel at lower capacity. Central routes, particularly during peak travel hours provide noticeable congestion, fuel consumption, and pollutant emissions reduction due to trips taken by transit replacing personal vehicles but off-peak, and non-central routes, show lower benefits. Because the light rail is electric, its local air quality benefits are significant due to the electricity being produced primarily outside the airshed. Upgrading the bus fleet to 2010 model, and newer, diesel and compressed natural gas (CNG) buses, as well as modeling an envisioned change to Tier 3 locomotives for the commuter rail system, was found to significantly reduce regional nitrogen oxides (NOₓ), fine particulate matter (PM₂.₅), and sulfur oxides (SOₓ) emissions.]]></description>
      <pubDate>Fri, 27 Sep 2019 09:58:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1651034</guid>
    </item>
    <item>
      <title>Social-Transportation Analytic Toolbox (STAT) for Transit Networks</title>
      <link>https://trid.trb.org/View/1639251</link>
      <description><![CDATA[This project builds an open-source, socio-transportation analytic (STAT) toolbox for public transit system planning in an effort to integrate social media and general transit feed specification (GTFS) data for transit agencies in evaluating and enhancing the performance of public transit systems. This toolbox is novel and essential to transit agencies in two aspects. First, it enables the integration, analysis and visualization of two major, new open transportation data, social media and GTFS data, to support transit decision-making. Second, it allows transit agencies to evaluate service network efficiency and access equity of transit systems in a cohesive manner, and identify areas for improvement to better achieve these multidimensional objectives. The toolbox employs a combination of data mining, geographical information systems and transportation network modeling. The STAT is an open-source toolbox and is publicly accessible. The project engages two transit agencies, the Utah Transit Authority (UTA) and TriMet, to test the usability of the toolbox, where Salt Lake City and Portland are used as case studies in the platform for querying, navigating and exploring the interactions between transit users and services. STAT can assist agencies in evaluating overall system performance and identifying existing public transit connectivity gaps, particularly for disadvantaged populations, in reaching essential services. It can also act as a decision support tool for recommending improvements (e.g., prioritize the stations and routes, identify the necessity for introducing a new line within existing infrastructure, etc.) The project ties to the National Institute for Transportation and Communities (NITC) theme of improving mobility of people and creating vibrant communities. The authors expect that it can be adapted over time to cover different geographies and incorporate new data sources. In addition to serving transit agency staff, the tool can be used in university curriculum and by advocacy organizations engaged in transportation decision-making. Finally, the project lays the foundation for  NITC developing other open-source tools using big data.]]></description>
      <pubDate>Thu, 25 Jul 2019 10:08:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1639251</guid>
    </item>
    <item>
      <title>Evaluating and Enhancing Public Transit Systems for Operational Efficiency and Access Equity</title>
      <link>https://trid.trb.org/View/1530216</link>
      <description><![CDATA[Assessing the performance of public transit services has long been an important yet challenging issue for transportation agencies and researchers. Transit service performance measurement reflects a very first step towards an efficient and proactive management, where public transit agencies are increasingly pressured to provide high-quality services in spite of constrained resources. However, the performance evaluation of transit services is complicated by an array of quantitative measures available to assess the goals and the diversity in the goals themselves, which usually include improving operational efficiency and providing equitable access. While much previous work has examined public transit services for achieving optimal operational efficiency and/or access equity separately, the interplay of the two has rarely been investigated to date. This project developed a comprehensive framework and an open-source toolbox for evaluating and enhancing the overall performance of public transit systems by using a combination of mathematical programming methods, geographic information systems (GIS)-based analysis and multi-objective spatial optimization techniques. This framework enabled operational efficiency and access equity of transit systems to be assessed in an integrated manner. The python open-source toolbox operationalizes the framework and makes it accessible to transit planners, decision-makers and the public. The framework and the toolbox are applied to assessing the performance of fixed-route bus services operated by the Utah Transit Authorities (UTA) in the Wasatch Front, Utah, and transit services operated by TriMet in the Portland metropolitan area. Results demonstrate that the developed framework and toolbox can effectively account for operational efficiency and access equity in an integrated manner, providing a more comprehensive assessment for transit service performance.]]></description>
      <pubDate>Tue, 21 Aug 2018 17:02:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/1530216</guid>
    </item>
    <item>
      <title>First and Last Mile Assessment for Transit Systems</title>
      <link>https://trid.trb.org/View/1522810</link>
      <description><![CDATA[The First Mile Last Mile (FMLM) challenge garners significant attention as a means to assess the accessibility of the first leg to transit and the last leg from public transit. As a critical barrier to public transit accessibility, the challenge provides many opportunities to closely analyze conditions from the level of the transit station upwards to the level of the system-wide network. Its usefulness in contributing to the body of knowledge on barriers to transit access provides planners and researchers important information with implications in increasing ridership, transit efficiency, multimodal travel options, and accessible mobility. In this project, the authors propose a methodological framework for analyzing the FMLM problems by determining varying causes of poor public transit accessibility and identifying areas with immediate needs for improvements. The authors showcase the analytical framework using a transit network in the state of Utah operated by the Utah Transit Authority. The authors also conducted analysis on the impacts of reduced automobile use on personal and environmental health. As a companion product, a spreadsheet-based sketch planning tool is developed to estimate health cost savings as a result of mode shifts from private automobiles to active transportation options.]]></description>
      <pubDate>Wed, 18 Jul 2018 09:51:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/1522810</guid>
    </item>
    <item>
      <title>Optimizing the spatio-temporal deployment of battery electric bus system</title>
      <link>https://trid.trb.org/View/1509441</link>
      <description><![CDATA[Environmental concerns due to fossil fuel consumption and emissions drive transportation industry to shift towards low-impact and sustainable energy sources. Public transit system, as an integral part of multimodal transportation ecosystem, has been supporting such shift by exploring the adoption of electric vehicles. In recent years, the advancement in Battery Electric Buses (BEBs) and their supporting infrastructure technology made them a viable replacement for diesel and Compressed Natural Gas (CNG) buses. Yet, it remains a challenge on how to optimally deploy the BEB system due to its unique spatio-temporal characteristics. To fill this gap, this research introduces a spatio-temporal optimization model to identify the optimal deployment strategies for BEB system. The identified spatio-temporal deployment of BEB system can minimize the cost associated with vehicle procurement and charging station allocation, while satisfying transit operation constraints such as maintaining existing bus operation routes and schedules. The proposed method is implemented onto the transit network operated by the Utah Transit Authority (UTA) to showcase its effectiveness. As many transit agencies are testing electric buses and considering the integration of electric buses into future fleet, this research will help transit agencies make informed decisions regarding strategic planning and design of BEB systems.]]></description>
      <pubDate>Tue, 29 May 2018 10:24:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/1509441</guid>
    </item>
    <item>
      <title>Transit Vehicle Performance Analysis for Service Continuity/Termination: A Data Envelopment Analysis Approach</title>
      <link>https://trid.trb.org/View/1495079</link>
      <description><![CDATA[Public transit agencies aim to improve services while reducing operating costs. Transit performance analysis, as the main approach used to assess operating cost and revenue, has received much attention in recent decades. Most of such studies focus on macro-level performance analysis by comparing across transit agencies or within a transit agency across different parts of its operation. This macro-level analysis assumes that bus drivers and vehicles have identical performance in terms of production and resource consumption, yet they can vary significantly and the variations directly influence service reliability and operational efficiency. As a result, micro-level vehicle performance analysis is needed for operation optimization. This paper introduces an innovative and effective use of the data envelopment analysis (DEA) approach to estimate, project, and compare the operational efficiency of each transit vehicle. Using the paratransit fleet of Utah Transit Authority (UTA) as a case study, the study demonstrates the varying cost structures and operational efficiencies over time associated with different vehicle types. It shows that such variations and time series analysis can be used to guide prioritization of vehicle procurement and service continuity/termination, which further leads to significant cost savings and improvement in reliability of service. The proposed approach is replicable for any transit fleet with available maintenance and operation data. The proposed method provides transit agencies with data-driven analytics to facilitate the decision-making process.]]></description>
      <pubDate>Fri, 23 Mar 2018 10:32:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/1495079</guid>
    </item>
    <item>
      <title>Another One Rides the Bus? The Connections Between Bus Stop Amenities, Bus Ridership, and ADA Paratransit Demand</title>
      <link>https://trid.trb.org/View/1496520</link>
      <description><![CDATA[Improving bus stops by providing shelters, seating, signage, and sidewalks is relatively inexpensive and popular among riders and local officials. Making such improvements, however, is not often a priority for U.S. transit providers because of competing demands for capital funds and a perception that amenities are not tied to measurable increases in system effectiveness or efficiency. This study analyzes recent bus stop improvements made by the Utah Transit Authority (UTA) to determine whether, and to what extent, the improvements are associated with changes in stop-level ridership and demand for Americans with Disabilities Act (ADA) paratransit service in the areas immediately surrounding improved bus stops. The study compares ridership and paratransit demand from before and after the improvements at the treated stops and at a set of unimproved stops selected using propensity score matching to control for demographic, land use, and regional accessibility influences. The analysis shows that the improved bus stops are associated with a statistically significant increase in overall ridership and a decrease in paratransit demand, compared to the control group stops. These outcomes are important for transit service providers as they seek to increase overall ridership and reduce costs associated with providing paratransit service.]]></description>
      <pubDate>Thu, 22 Mar 2018 11:57:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1496520</guid>
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