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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>A Data-driven Approach in Improving Truck Parking Efficiency</title>
      <link>https://rip.trb.org/View/2684213</link>
      <description><![CDATA[Freight transportation systems are a critical component of the United States' economy, underscoring the importance of adequate truck parking to ensure safe and efficient operations. However, a significant disparity between truck parking demand and supply has resulted in numerous challenges, including increased road safety risks, regulatory non-compliance, and operational inefficiencies. This study aims to address this knowledge gap by conducting a comprehensive review of current truck parking management approaches, with a focus on data-driven prediction models, and truck parking pattern analysis. In collaboration with the North Carolina Department of Transportation (NCDOT), the study will analyze truck parking patterns along key freight corridors and develop data-driven solutions to enhance parking efficiency and address these pressing challenges.

This project aims to address this gap by conducting a comprehensive review of existing literature and offering a nuanced exploration of potential truck parking solutions. Using NC as a case study, the project will provide data-driven recommendations to improve the efficiency and utilization of existing parking facilities along key freight corridors. By enhancing the safety and efficiency of truck parking, this study will directly benefit truck operators, supply chain stakeholders, regulatory agencies, and local communities. The findings will serve as a foundation for informed policymaking and infrastructure planning, ensuring that North Carolina’s freight transportation network remains resilient, sustainable, and operationally efficient in the face of growing demands.]]></description>
      <pubDate>Wed, 25 Mar 2026 17:16:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684213</guid>
    </item>
    <item>
      <title>Emergency Truck Parking Location Modeling</title>
      <link>https://rip.trb.org/View/2684216</link>
      <description><![CDATA[This research project will develop and apply optimization methods for the modeling of the emergency truck parking problem. This research is directly aligned with the Center for Freight Transportation for Efficient and Resilient Supply Chain (FERSC) goal of advancing research and practice for resilient and safe freight transportation. The results of this research can be used to inform policy and identify needed investments in truck parking facilities. The end goal is to inform the establishment of safe parking facilities to minimize risks for truck drivers and the public that are associated with commercial vehicles stopping at inadequate (sometimes illegal) locations due to the lack of appropriate short- and long-term parking in emergency situations.

A top concern for truck drivers is finding adequate parking. Truck drivers need a safe place to stop for compliance with hours-of-service (HOS) regulations and for other reasons related and unrelated to their jobs. Finding adequate truck parking is even more critical in emergency situations when regular truck parking facilities might not be accessible. This research project will apply optimization methods for the modeling of the emergency truck parking problem. A mathematical programming approach will be used to identify appropriate locations for emergency truck parking under different scenarios of disruptive emergency events. The mathematical model will be tested with an instance developed for Oregon. The results of this research have the potential to inform policy and identify needed investments in truck parking facilities.]]></description>
      <pubDate>Wed, 25 Mar 2026 16:59:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684216</guid>
    </item>
    <item>
      <title>Refining the Understanding of Parking Space Requirements and Its Impact on Vehicle Miles Traveled</title>
      <link>https://rip.trb.org/View/2487321</link>
      <description><![CDATA[In 2023, the Minnesota legislature passed H.F. No. 2887 which implemented several policies to reduce greenhouse gases (GHG) in transportation. One of the key areas identified to reduce GHGs was through the reduction of vehicle miles traveled (VMT), which reduces GHG emissions by reducing the total distance travelled by cars in the state. Many VMT reduction strategies hold additional benefits such as increasing accessibility, safety, and reducing congestion. Parking space requirements have been highlighted as a specific element associated with driver modal choice, but little documented information is available on the established requirements or long-term benefits and challenges associated with modifying or removing these requirements. The goal of this project will be to explore, document, and broaden the collective understanding of mandated parking minimums within Minnesota and the region. Specifically, this project will examine the long-term benefits and challenges presented by reducing and/or removing currently established parking space requirements with new or redevelopment projects, and opportunities for parking space reallocation with existing uses.]]></description>
      <pubDate>Wed, 08 Oct 2025 11:55:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2487321</guid>
    </item>
    <item>
      <title>A Guide for Airport Parking Operation and Revenue Management Models


</title>
      <link>https://rip.trb.org/View/2588329</link>
      <description><![CDATA[Airport parking fees are a critical source of non-aeronautical revenue for airports. According to a 2024 Airport Council International (ACI) report, U.S. airports generate approximately $5-7 billion annually from parking, accounting for 43% of total non-aeronautical revenues. Given the significance of this revenue stream, airports are prioritizing enhanced customer experiences while exploring new monetization opportunities. Over the past 5–10 years, many airports have adopted innovations such as cashless, attendant free in-lane kiosks, dynamic pricing models, and pre-booked parking reservations to streamline operations and boost yields. 

Research is needed to help airport practitioners compare the long-term financial and operational performance of various parking operating models (including hybrid third-party) across different airport sizes and regions. This research should help airport practitioners assess the impact of emerging technologies and pricing strategies on customer satisfaction, utilization rates, and revenue optimization under various operating models.

OBJECTIVE: The objective of this research is to develop a guide to help implement parking strategies, map the future parking models and evaluate the pros and cons of each operational model, and enable airports to select the approach that best aligns with their strategic goals.]]></description>
      <pubDate>Tue, 12 Aug 2025 10:30:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2588329</guid>
    </item>
    <item>
      <title>New Transit, Bike Infrastructure, and Green Space: Do They Have a Multiplying Effect on Gentrification and Displacement?</title>
      <link>https://rip.trb.org/View/2422603</link>
      <description><![CDATA[Researchers have documented how new rail transit and bus rapid transit (BRT), new bike infrastructure, and new parks have contributed to gentrification. Much of this research, however, has focused on one type of investment at a time, has used aggregate tract-level data, and has only examined whether gentrification follows public investment, and now whether it can also precede it. To start addressing this gap, this project seeks to disentangle the impacts of different public investments on neighborhood change. We ask: Do new transit, bike infrastructure, and green space have a multiplying effect on gentrification and displacement? Specifically, when new transit is built in low-income communities, do concurrent investments in bike infrastructure or green space increase the odds of gentrification and displacement? And does gentrification precede public investments in new transit, bike infrastructure, and green space? We will focus on four metropolitan areas in the Western U.S. (Denver, Wasatch Front, Portland, and Seattle) that have seen significant investment in new rail/BRT, bike infrastructure, and parks. We will build a longitudinal dataset with household-level data from Data Axle between 2006 and 2023 in the four regions. Data for public investments will come from Transit Explorer (transit and BRT), metropolitan planning organizations and cities (bike infrastructure), and the Trust for Public Land (parks). We will classify households in gentrification-eligible tracts as treatment if within a half mile of a new public investment (e.g., new rail transit) and as control if otherwise, considering multiple combinations of proximity to several types of public investments (e.g., proximity to new rail transit and park vs. proximity to park only). We will then build mixed-effect models to track residential mobility in and out of areas near new transit but without new park investment and bike infrastructure investments and compare such residential mobility with new transit areas that do have new parks and/or new bike infrastructure. To do so, models will include interaction terms between the various treatments (e.g., transit treatment and park treatment). Thanks to this household-level dataset, we will be able to track the low-income households who will move out of various treatment areas, which will enable us to model potential displacement processes. In these models, we will control for several other variables such as neighborhood demographics, housing characteristics, crime, and other characteristics known to affect gentrification and displacement. We will use evidence from this study to define gentrification and displacement propensity factors associated with new public investments in sustainable infrastructure. We will disseminate such propensity factors via a peer-reviewed publication and policy brief. We believe that these factors will inform the planning of transit-oriented developments by providing planners with information about the potential impacts of other public investments alongside transit. To make it easier for researchers to use household-level data such as Data Axle to model gentrification and displacement, we will share publicly the code we will develop to process and analyze such data. If permitted, we will share data about new parks and new bike infrastructure in the four selected metropolitan areas. Outputs will include 1. A peer-reviewed publication describing the results of the study 2. A peer-reviewed publication describing the technical aspects of using Data Axle to model neighborhood change and residential mobility 3. A policy brief for practitioners summarizing our main findings and providing recommendations about propensity factors of gentrification and displacement induced by new transit on its own and in conjunction with other investments 4. A presentation for practitioners disseminated via a webinar 5. A conference presentation 6. A webpage that will host the R and Python codes we used to process and analyze Data Axle data; the page will also host all data collected and processed in this study, except for Data Axle data.]]></description>
      <pubDate>Tue, 27 Aug 2024 18:12:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2422603</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Airport Practices. Topic S07-04. Airport Property Used for Parks and Recreational Use</title>
      <link>https://rip.trb.org/View/2077891</link>
      <description><![CDATA[ACRP Synthesis 137: Parks and Other Recreational Uses on Airport Property, from the Transportation Research Board (TRB)'s Airport Cooperative Research Program (ACRP), describes the experiences of airports that provide airport property for publicly accessible parks and other recreational uses. ]]></description>
      <pubDate>Wed, 07 Dec 2022 18:28:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2077891</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Airport Practices. Topic S03-19. Airport Parking Reservation Systems and Techniques</title>
      <link>https://rip.trb.org/View/2077893</link>
      <description><![CDATA[ACRP Synthesis 140: Airport Parking Reservation Systems and Techniques, from TRB's Airport Cooperative Research Program, documents the use of online booking systems at U.S. airports, including their benefits, costs, and implementation challenges.]]></description>
      <pubDate>Wed, 07 Dec 2022 18:14:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/2077893</guid>
    </item>
    <item>
      <title>WSDOT FMCSA-Truck Parking Information and 
Management System (TPIMS)</title>
      <link>https://rip.trb.org/View/1907133</link>
      <description><![CDATA[To help commercial drivers plan their trips and maximize the use of available parking, Washington State Department of Transportation (WSDOT), in partnership with the University of Washington (UW) STAR Lab, will develop and install a self-learning and optimizing Truck Parking Information and Management System (TPIMS). The project will be approached as a collaborative effort between WSDOT and UW.]]></description>
      <pubDate>Thu, 17 Mar 2022 14:53:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/1907133</guid>
    </item>
    <item>
      <title>Transportation Research Related to COVID-19. Guide on Truck Rest and Service Areas for Critical Supply Chain Delivery</title>
      <link>https://rip.trb.org/View/1842757</link>
      <description><![CDATA[The objective of this research is to develop a guide for effective practices and implementation strategies to integrate resilience and emergency response planning and operations related to truck rest and service areas for supply chain delivery.
]]></description>
      <pubDate>Wed, 24 Mar 2021 18:28:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/1842757</guid>
    </item>
    <item>
      <title>Development of Level of Service Analysis Procedures and Performance Measurement Systems for Parking</title>
      <link>https://rip.trb.org/View/1697989</link>
      <description><![CDATA[In SPARKMAN, a C2SMART Year 3 project, University of Texas, El Paso (UTEP) researchers have: (1) Developed a university student parking lot Zoning and Zone Permit Pricing (Z2P2) model and coded it as a software tool named SPARKMAN and (2) Conducted a student survey, determined the ITS needs for campus parking based on the survey data, and established the Level of Service (LOS) criteria for parking. This proposed year 4 project will focus on the LOS for parking and will extend the concept of LOS for parking to a Performance Measurement System (PMS) for parking. The objectives of this project are: (1) To develop LOS analysis procedures for open surface parking lots; (2) To develop a LOS analysis procedure for multistory parking garages; (3) To develop a Concept of Operations (ConOps) of a PMS in smart parking garages; and (4) To explore PMS for street parking using existing smart technology. The LOS analysis procedure will incorporate field data collection procedures by traditional traffic survey techniques including sensing and potential use of mobile smartphone applications.]]></description>
      <pubDate>Thu, 16 Apr 2020 09:15:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/1697989</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Airport Practices. Topic S01-25. Airport Parking Pricing Strategies</title>
      <link>https://rip.trb.org/View/1668963</link>
      <description><![CDATA[Parking is important for airports. More than 70 percent of airline passengers and visitors at most airports use private vehicles to access the airport, and public parking is an important contributor to an airport's finances and revenues, frequently representing the largest source of non-aeronautical revenues at most airports.

The TRB Airport Cooperative Research Program's ACRP Synthesis 118: Airport Parking Pricing Strategies provides information airport staff and others require to select and to implement a rate-making strategy that serves the airport's needs.]]></description>
      <pubDate>Mon, 25 Nov 2019 17:55:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/1668963</guid>
    </item>
    <item>
      <title>Accessing America's Great Outdoors: Forecasting Recreational Travel Demand</title>
      <link>https://rip.trb.org/View/1628597</link>
      <description><![CDATA[The objectives of this project are to develop the following: (1) A recreational travel demand model component that is compatible with and can be incorporated into, or used in conjunction with, transportation demand models currently in use by state DOTs, metropolitan planning organizations (MPOs), and other transportation planning agencies. (2) Guidelines for state DOTs and other affected transportation and land management agencies on enhanced recreational travel modeling using the recreational travel demand component: (a) Description and assessment of existing methods and procedures for evaluating recreational travel demand and associated data gaps, focusing on public lands (federal, state, and local). This assessment will provide the baseline needed for effective analytical approaches to measure the effects of changing recreational travel demand and the impact recreational travel has on transportation system performance. (b) Identification and exploration of factors driving recreational travel volumes and patterns. The outcome and products of this study should clearly describe which factors are correlated with recreational visitation (number of visitors to a site) versus which factors drive changes in recreational travel (travel to and from sites). 
These guidelines will help state DOTs and other transportation and land management agencies integrate recreational travel demand into overall transportation system planning and forecasting, enabling affected jurisdictions to make better-informed decisions about investments in multimodal transportation improvements, economic development, and other issues that may enhance traveler experience and improve quality of life for residents in affected communities.

]]></description>
      <pubDate>Thu, 06 Jun 2019 20:06:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/1628597</guid>
    </item>
    <item>
      <title>Sparkman: A Smart Parking Management Tool for University Campuses</title>
      <link>https://rip.trb.org/View/1607550</link>
      <description><![CDATA[Most universities are constantly challenged by the problem of inadequate parking supply to meet the demand. The common parking management policies are zoning of parking lots (allocation of stalls to different types of users), differentiation of permits and pricing. As an initial step towards finding a comprehensive parking solution, this research focuses on student parking, which is the largest group of parking users on campus. 
The objectives are:
1.	To conduct a survey to understand the factors that influence students’ parking location choices, usage patterns, preferences among the different Intelligent Transportation Systems (ITS) applications for parking and levels of tolerance for parking search time. 
2.	To develop the level of service (LOS) criteria for parking search time;
3.	To develop a student parking lot zoning and zone permit pricing (Z2P2) model that groups several parking lots into a zone, and recommend the permit price for the zone; 
4.	To develop Version 1.0 of a software tool named Sparkman (acronym for Smart Parking Management) that estimates a campus’ total student parking demand, the “base price” of student parking permits, zoning of student parking lots, and the permit prices of the different zones.  The total demand and “base price” models have been developed by the PI as two separate models in earlier research, while the Z2P2 models will be developed as part of this project (objective 1). The total demand, “base price” and Z2P2 models will be integrated into Sparkman as part of this research.
]]></description>
      <pubDate>Wed, 22 May 2019 13:08:40 GMT</pubDate>
      <guid>https://rip.trb.org/View/1607550</guid>
    </item>
    <item>
      <title>Truck Parking Needs in Tennessee</title>
      <link>https://rip.trb.org/View/1552811</link>
      <description><![CDATA[The objectives of this research are to provide the Tennessee Department of Transportation (TDOT) with important guidance on truck parking issues and opportunities, by identifying parking needs (i.e., addition of capacity and/or construction of new facilities); developing truck parking violation rates (i.e., truck parking on on- and off- ramps) and developing/applying a methodology to identify candidate locations for new truck parking facilities in the State of TN. This study extends the work done by Golias et al. (2017) and Cherry et al. (2017) who used truck global positioning system (GPS) and survey data to evaluate the performance of truck parking in TN.]]></description>
      <pubDate>Wed, 03 Oct 2018 16:39:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/1552811</guid>
    </item>
    <item>
      <title>Truck Parking Study: Unveiling the Parking Space density and Truck Volume Relationship: Phase 1</title>
      <link>https://rip.trb.org/View/1531771</link>
      <description><![CDATA[Truck parking has been a national concern for many years. There are several reasons behind it. One is that truck driving and on-duty hours are regulated by the federal law for the sake of traffic safety. Truckers cannot drive for more than 7 hours within any consecutive 24 hours of time. Truckers, especially those for inter-city travel, must find a resting spot when the driving hours reaches its federally enforced limit. Due to unavailability of truck parking space at locations, it is needed, truckers are often found to park illegally on highway ramps or other unsafe spots. Alternatively, some truckers are caught driving beyond the hours limit, which significantly contributes to the highway fatal rate. 

The objective of this study is to study the relation between truck volume and parking space density in a simulation environment as phase I. The truck space availability issue is essentially one between volume and density subject to boundary conditions. The intuitive observation is that a higher volume demands more parking space statistically. The boundary condition is that there must be a minimum density no matter how low the volume is. In realistic situations such as those along the corridors of I-94 in Wisconsin and Minnesota as well as I-35, HW29 in Iowa and Texas, the team believes that there must be an inherent relationship between the space needed and the truck volume. The study means is a computer simulation, which allows to flexibly examining all different situations along the interstate highways in terms of volumes and density. The goal is to explore a statistical formula for this relationship in a hope that policymakers may use to examine the adequacy of truck parking space within their jurisdiction areas.]]></description>
      <pubDate>Sat, 11 Aug 2018 22:20:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/1531771</guid>
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