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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <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>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Reducing congestion in port hinterlands: an agent-based modeling case study of truck parking facility impacts</title>
      <link>https://trid.trb.org/View/2663321</link>
      <description><![CDATA[The increasing volume of container handling at seaports leads to a rise in heavy vehicle traffic, often resulting in congestion that poses a significant challenge to port competitiveness by disrupting operational fluidity, increasing logistics costs and delays. This study presents the development of an agent-based simulation model designed to evaluate the impact of incorporating a truck parking facility on the hinterland operations. The model is adaptable to diverse maritime supply chain and utilizes performance indicators, such as queue length and total cycle time. A case study conducted at Itapoá Port, Brazil, indicates that the infrastructure can be used as an efficient congestion management strategy, since it has the potential to reduce the total cycle time of full containers by 15.69% for import flows and 18.43% for export flows. Findings suggest that the proposed solution can mitigate congestion, enhance operational efficiency, and contribute to more sustainable port logistics.]]></description>
      <pubDate>Thu, 14 May 2026 17:04:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663321</guid>
    </item>
    <item>
      <title>Car Parking in Indian Cities: A Review of the Impediments to Sustainable Mobility</title>
      <link>https://trid.trb.org/View/2581522</link>
      <description><![CDATA[Irrespective of how little pollution is emitted by cars or their fuel efficiency, it is required to park cars somewhere. Poorly designed parking policies can induce vehicle ownership, urban sprawl, and less patronage for public transport. The goals it should fulfil hence come from the greater agenda of sustainable urban development that usually includes a strong and vibrant economy supported by a proficient transport system, clean urban environment, better accessibility, a safe environment, and a more equitable society. In India, a country with rising urbanization level and the concomitant induced derived demand for mobility, scanty research has been undertaken on the implications of parking policies. This study attempts to understand the current enabling policy and legal environment, institutional mechanism, existing parking strategies, and pricing and its impact on average generalized cost of trip in Indian cities and it also probes the possible policy implications for the future. This study relies on exploratory research methods based on secondary data available with various institutions and organizations and focused group discussions with different stakeholders. The study finds that India is depending on Generic Minimum-based parking approach that doesn’t consider transit proximity, popularity of a particular establishment, walkability, income and parking management practices like availability of public parking lots, parking pricing, and overall peak demand. There is an urgent need to provide efficient legal support for the creation of institutional mechanism, unbundling of parking pricing, adoption of smart growth parking policies.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581522</guid>
    </item>
    <item>
      <title>Evaluating the Parking Characteristics and Parking Demand of On-Street Parking in Silchar City</title>
      <link>https://trid.trb.org/View/2579814</link>
      <description><![CDATA[Silchar is a major city in Cachar district, Assam with a population of 2,72,709 and an area of 26.88 km2. Parking is an issue that creates high traffic congestion in city areas. The vehicle needs sufficient street space for parking for the smooth movement of traffic. With the expanding population and automobiles, parking has become a significant issue (Manville, Shoup, Bacon, 2005). The scarcity of parking space in the city has increased the demand for it, particularly in critical business areas. A thorough examination of parking demand and characteristics is carried out to control parking activities, which will be helpful to the site visitors, engineers, and town planners. Two roads have been chosen for this study, i.e., Central Road and Shyamaprasad Road, which have insufficient parking spaces. Surveys are being conducted at those two locations to determine the parking accumulation, occupancy profile, demand and supply of parking (Parmar, Das, Dave, 2019; Chen, Wang, Pan, 2015; Tong, Wong, Leung, 2004). Linear regression analysis is also used to build a parking demand model using the statistical package for the social science (SPSS) software. The R-square values for Central and Shyamaprasad Roads are found to be 0.97 and 0.98, respectively.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:21:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579814</guid>
    </item>
    <item>
      <title>Disabled People and “Mobility”. Proposal for Infrastructures Intended to Prevent Parking in Disabled Spaces and Their Pilot Application in the City</title>
      <link>https://trid.trb.org/View/2579539</link>
      <description><![CDATA[In recent years, the issue of accessibility for people with mobility difficulties, more and more “aggressively” introduced to all scales of urban planning, but also of its legal interpretation. Even if the “poverty” of the existing infrastructure is another factor that makes this development difficult, for the Greek standards, the design findings of recent years are at least encouraging, albeit in an embryonic stage. Despite this fact, there are daily phenomena in which even these elementary infrastructures become the object of exploitation or/ and violation of elementary rules of civil behavior as well as an indication of civilization. Even if the fact that the specific reality has clear origins of elementary rules and level of education, urban planning must take further measures to deal with such everyday phenomena, by planning and constructing “smart” applications to prevent related phenomena. This article attempts to propose a specific, intelligent, low-cost infrastructure, to prevent parking, in places reserved for people with mobility difficulties. The aim of the specific applications is not prevention with, police-type, countermeasures but the highlighting and social “targeting” of vehicles and users who resort to such methods. The user of the vehicle who will park in this type of spaces, which objectively are few to minimal in Greek cities, will be perceived, with the use of the specific infrastructures, in that the place that he parked his vehicle was not foreseen. Therefore, the specific “violation” will also be noticed by passers-by or users of the land uses of adjacent buildings.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579539</guid>
    </item>
    <item>
      <title>Promoting Public Transport with a Discount on City Centre Shops at Large Cities</title>
      <link>https://trid.trb.org/View/2579510</link>
      <description><![CDATA[This study advocates for promoting public transportation to alleviate traffic congestion and emissions in city centers. It introduces a zoning plan with designated parking at four points around each zone. Those using public transport from farther parking spots would get discounts at city center shops, and the parking ticket would grant access to city services. This aims to reduce congestion, pollution, and enhance public transport efficiency. The proposed model focuses on implementing this strategy in the greater area of Thessaloniki, dividing the city into three zones. Each zone will offer varying discounts of 5% (Zone 1), 10% (Zone 2), and 15% (Zone 3), with the highest discount reserved for Zone 3, situated farthest from the city center. To validate the effectiveness of our approach, the future plan is to construct a detailed model and conduct a comprehensive survey of stakeholders. The insights gained from the survey will contribute valuable data to support the efficacy of the proposed zoning strategy. By implementing this innovative solution, a positive impact on the overall urban environment is anticipated, with reduced traffic congestion, lower pollution levels, and improved public transportation utilization.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579510</guid>
    </item>
    <item>
      <title>Multi-objective optimisation of parking capacities in urban areas</title>
      <link>https://trid.trb.org/View/2682147</link>
      <description><![CDATA[Cars remain the most widely used mode of transport today. However, in many urban areas, high car usage leads to negative externalities such as congestion, pollution, and inefficient land use. Optimising parking policies in cities is a promising approach to reduce these externalities, though it often involves trade-offs; for example, reducing parking space can increase the time drivers spend searching for a spot. We present a model to optimise parking capacities in urban areas using a multi-objective framework that simultaneously minimises (1) travel time, (2) distance travelled by car, and (3) the number of parking spaces. We address this problem using a bi-level programming framework as parking capacity decisions (upper level) influence driver route and parking choices (lower level), which in turn affect the objective values. Our main methodological contribution lies in enhancing the upper level optimisation through a novel mutation operator, which helps achieve lower objective values. We apply our model to the city of Delft, the Netherlands, demonstrating that a diverse set of solutions with low objective values can be obtained. Moreover, we show through an example within this case study that our model can help policy-makers assess trade-offs in the conflicting objectives.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2682147</guid>
    </item>
    <item>
      <title>Assessment of Truck Parking Demand and Safety During Normal and Severe Weather Conditions in Nebraska</title>
      <link>https://trid.trb.org/View/2690988</link>
      <description><![CDATA[This project examined truck parking capacity, demand, and utilization patterns along I-80 in Nebraska. The objectives were to (1) document the capacity of public and private truck parking facilities along I-80, (2) analyze spatial and temporal trends in parking demand, (3) develop models to predict occupancy at parking facilities, (4) identify clusters of undesignated parking during inclement weather, and (5) assess whether truck parking shortages contribute to truck-involved crashes. Within a one-mile buffer of I-80, 21 public facilities and 49 private facilities were identified. The spatiotemporal analysis of these public and private truck parking facilities using the National Agriculture Imagery Program and Google Earth Imagery data between 2010 and 2022 showed a higher parking occupancy rate at private facilities, with several private facilities experiencing 100% occupancy or higher. Public facilities near Omaha had a consistently high occupancy rate. To enable the Nebraska Department of Transportation (NDOT) to estimate the occupancy rate of a facility, public or private, expansion factors were first developed using the 2022 American Transportation Research Institute (ATRI) Global Positioning System (GPS) data. The number of trucks parked at public and private facilities was then estimated by multiplying the number of GPS-identified trucks that remained stationary for more than 60 minutes by the corresponding expansion factor. Building on these estimates, a hybrid Bayesian modeling framework was developed to predict occupancy. Parking facilities were clustered based on their inter-facility distances, resulting in groups containing either single or multiple facilities. Accordingly, a dynamic time series model was developed for individual facilities, while a panel model with time fixed effects and distance-based spatial lags was developed for multi-facility clusters. Results indicate that lagged occupancy is the strongest predictor, with spatial effects also significant in the panel model. Both models achieved strong predictive performance. During inclement weather, trucks were found to park in four locations: facility entry and exit areas, off-road sites, ramps, and shoulders. Lastly, statistical analysis showed no significant relationship between truck-involved crashes and parking shortages.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:28:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2690988</guid>
    </item>
    <item>
      <title>Emergency Truck Parking Location Modeling</title>
      <link>https://trid.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://trid.trb.org/View/2684216</guid>
    </item>
    <item>
      <title>A Data-driven Approach in Improving Truck Parking Efficiency</title>
      <link>https://trid.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://trid.trb.org/View/2684213</guid>
    </item>
    <item>
      <title>Develop a multi-criteria methodology to evaluate and recommend the best sustainable option of public parking infrastructure planning in the Eastern Asia downtown</title>
      <link>https://trid.trb.org/View/2655503</link>
      <description><![CDATA[The public parking system is a vital component of urban infrastructure, playing a crucial role in regulating traffic demand, reducing congestion, and supporting multimodal transportation. This study proposes a multi-criteria decision-making (MCDM) approach to evaluate and recommend sustainable public parking infrastructure planning in three cities in Eastern Asia: Thu Dau Mot, Thuan An, and Di An. The methodology integrates the Analytic Hierarchy Process (AHP) with Weighted Aggregation (WA) and traffic simulation modeling using PTV Visum. Various planning scenarios are assessed based on functional, economic, social, environmental, and feasibility criteria. The findings highlight the importance of optimizing parking locations, enhancing multimodal transport integration, and balancing stakeholder interests. Results indicate that strategic planning can significantly improve parking efficiency while minimizing environmental and economic costs. The study provides policy recommendations to guide sustainable urban parking development, emphasizing data-driven decision-making and public-private partnerships for long-term urban mobility solutions.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:20:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655503</guid>
    </item>
    <item>
      <title>Locating stations of shared e-scooters with integrated SWARA and maximal covering location problem</title>
      <link>https://trid.trb.org/View/2669890</link>
      <description><![CDATA[The increasing usage of shared e-scooters has brought the issue of improper parking to the forefront. Research has shown that when parking areas are provided, the problem of improper parking can be prevented. This study aims to determine optimal parking locations for shared e-scooters in the Kadıköy district of Istanbul. A two-stage integrated approach involving Stepwise Weight Assessment Ratio Analysis (SWARA) and the maximal covering location model was employed to achieve this goal. In the first stage, e-scooter parking demand was identified, and in the second stage, 150 stations were placed that maximize the demand. The model results were compared with real data to validate the model. Decision-makers and other stakeholders can benefit from the suggested method in cases where data is unavailable or when shared e-scooter systems are being set up for the first time.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669890</guid>
    </item>
    <item>
      <title>Urban parking challenges and solutions: a case study</title>
      <link>https://trid.trb.org/View/2666111</link>
      <description><![CDATA[Urbanization and an increase in vehicle ownership have intensified the need for efficient parking solutions and have made parking services a critical component of urban mobility. Despite this, however, researchers have not fully explored the diverse factors that influence customer satisfaction with parking services but have relied on previous studies that primarily focused on broader transportation services, such as public transit, bike-sharing, and rail. This paper aims to investigate the complexities and uncover the key determinants of customer satisfaction with the goal of offering policy recommendations. To this end, a comprehensive survey was conducted of a college campus community and an ordinal logistic regression analysis was performed of 873 responses. The results highlight that shorter search times, easier access to parking spaces, reasonable parking costs, and effective communication and enforcement of parking rules are crucial for higher satisfaction levels. While technological innovations such as AI-powered parking apps show potential, their impact on satisfaction was not statistically significant. Based on this information, we recommend enhancing the availability and distribution of parking spaces, implementing real-time information systems, and maintaining transparent and fair pricing policies. Clear communication about parking regulations and consistent enforcement practices are also essential for improving user satisfaction. These recommendations are likely to significantly enhance user satisfaction and improve the overall campus environment, as they offer practical ways that university administrators and policymakers can improve campus parking experiences, ultimately supporting broader urban development goals.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666111</guid>
    </item>
    <item>
      <title>Parking-and-Charging-as-a-Service: Online admission and allocation policies for an integrated parking and charging reservation system</title>
      <link>https://trid.trb.org/View/2636188</link>
      <description><![CDATA[With a substantial increase in public charging facilities globally, the world has witnessed a significant surge in support for electric vehicles (EVs), making them more accessible and sustainable. However, EV drivers still struggle to find available charging spaces, which are often occupied by non-charging vehicles. While prohibiting parking in charging spaces can mitigate this issue, it can lead to underutilization of charging spaces when charging demand is low but parking demand is high. Existing studies often treat parking and charging management as separate issues, overlooking the fact that most charging spaces are located in parking facilities and jointly operated with parking spaces to serve both parking and charging needs. In this context, coordinated management of parking and charging spaces is essential for improving operational efficiency. This paper proposes an integrated Parking-and-Charging-as-a-Service (PCaaS) reservation system that jointly manages parking and charging demand through admission and allocation controls. Specifically, users submit parking and charging requests in advance, and the system dynamically determines whether to accept each request and, if accepted, allocates a parking or charging space accordingly. We model this sequential decision-making problem as a Markov decision process. Since deriving the optimal policy is computationally intractable, we introduce a bid price control policy to guide request admission and space allocation. Two decomposition methods are developed to compute bid prices efficiently. Using real-world parking facility data, we evaluate the performance of the proposed policies across varying problem scales, levels of dynamism, demand scenarios, and parking facility configurations. The results demonstrate that the proposed policies substantially enhance overall revenue and capacity utilization compared to current practices. The insights gained provide guidance for the planning and operation of public parking facilities.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2636188</guid>
    </item>
    <item>
      <title>Parking Standard for South Korea Based on Parking Difficulty</title>
      <link>https://trid.trb.org/View/2646026</link>
      <description><![CDATA[In South Korea, although parking problems are highly serious, the legal standards for parking facilities have not been updated since 1996. This study analyzes parking and survey data using an ordinal logistic regression model to identify the factors influencing perceived parking difficulty among residents of multifamily residential complexes. It also examines how parking difficulty varies with the actual parking supply rate. Based on the findings, we propose an evidence-based parking standard for multifamily residential areas.]]></description>
      <pubDate>Thu, 12 Mar 2026 16:30:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646026</guid>
    </item>
    <item>
      <title>No Such Thing as Free Parking: Construction Costs in 17 U.S. Cities</title>
      <link>https://trid.trb.org/View/2669545</link>
      <description><![CDATA[Across the United States, zoning codes require new developments to provide a minimum number of parking spaces, which carry substantial construction costs. In this report, we use 2025 construction cost estimates from Rider Levett Bucknall (RLB) to calculate the cost per space in 17 U.S. cities and combine these data with local minimum parking requirements to estimate how parking mandates increase total construction costs across building types. We find that parking construction costs have risen substantially faster than inflation since 2012 and that required parking can account for a large share of total project costs—adding tens of thousands of dollars per housing unit and, in some cases, increasing total construction costs by more than 50%. These findings can help inform evaluations of the economic and development impacts of maintaining minimum parking requirements.]]></description>
      <pubDate>Thu, 26 Feb 2026 09:15:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669545</guid>
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