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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>Bridging the behavioral valuation gap: A prosumer perspective on discrepancies between willingness to accept and willingness to pay in shared parking</title>
      <link>https://trid.trb.org/View/2685548</link>
      <description><![CDATA[Amid rising car ownership and limited urban parking, shared parking has emerged as a promising solution to address mismatches between parking supply and demand. However, the widespread adoption of shared parking services remains limited, primarily due to a divergence in valuation between providers and users within the sharing economy. This study explores the adoption behaviors of prosumers of shared parking from both the provider and user perspectives, aiming to address the behavioral mechanisms with the willingness to accept (WTA)-willingness to pay (WTP) discrepancy. A sequential stated preference survey was conducted among current shared parking prosumers in Seoul, Korea, where each respondent completed both provider and user scenarios in randomized order to capture role-specific preferences. The mixed logit model approach with latent variables (social and hedonist innovativeness) is employed to account for unobserved heterogeneity. Model results reveal that providers are more strongly influenced by social factors than users, and social innovativeness has a larger behavioral impact than hedonist innovativeness across both roles. For deeper insights, this study applies personalized taste weights to enable the identification of heterogeneous discrepancies in WTA-WTP across individuals. A notable discrepancy was found between WTA and WTP, and a personalized taste weights approach reveals substantial variability in the magnitude of valuation asymmetries among individuals, especially concerning shared parking time usage. Notably, this gap was mitigated among those with higher personal innovativeness, indicating an impact of social and hedonist innovativeness in reducing the discrepancy. These findings necessitate a shift from simplistic financial incentives to strategies that harness social influence and cater to diverse psychological profiles, emphasizing the importance of addressing the WTA-WTP discrepancy through comprehensive incentive structures and social recognition mechanisms to foster broader participation in shared parking services.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685548</guid>
    </item>
    <item>
      <title>A mean–variance approach for shared parking operations considering the risk of slot matching</title>
      <link>https://trid.trb.org/View/2673501</link>
      <description><![CDATA[Shared parking, utilizes the idle parking slots owned by residents, hotels, and companies to satisfy the insufficient demands requested by parking demanders, has received widespread attention in recent years. It allows greater flexibility in parking choices and encourages more efficient parking slot usage. Despite its merits in tackling parking challenges, several uncertainties such as the uncertainty in slot matching hinder the shared parking development. This poses potential risks for the shared parking platform operations. Motivated by this, we identify the impact of the endogenously slot matching risk on shared parking platform operations using the mean–variance (MV) approach. Six MV-based parking models are formulated based on two platforms’ risk preferences, i.e., risk-neutral and risk-averse, and three supply–demand scenarios, i.e., supply–demand balance, demand exceeds supply, and supply exceeds demand. Equilibrium outcomes regarding the parking price, the profit of the shared parking platform, the surplus of the parking demanders, and social welfare can be derived from these models. Results show that the risk of slot matching will harm the platform’s profit and parking demands in the supply exceeds demand scenario but will increase parking demands in the supply–demand balance scenario and the demand exceeds supply scenario. These findings were verified by a case study based on the shared parking data from Nanjing. Policy implications are further proposed to mitigate the adverse effects of the risk of slot matching.]]></description>
      <pubDate>Wed, 24 Jun 2026 13:22:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673501</guid>
    </item>
    <item>
      <title>Understanding willingness to participate in private shared parking under incentive and disincentive policies</title>
      <link>https://trid.trb.org/View/2654638</link>
      <description><![CDATA[While shared parking offers a promising solution to alleviate urban parking challenges, its adoption in private parking spaces, particularly in residential neighborhoods, is lagging due to low market participation. Successful implementation of private shared parking mainly hinges on understanding the factors that motivate individuals to participate in sharing programs. Existing research has preliminarily investigated parking space owners’ and users’ attitudes toward private shared parking, but has often overlooked the impact of policy interventions on willingness to participate (WTP), as well as the complex nonlinear effects and interaction relationships of influencing factors. To address these gaps, formal survey data on WTP in private shared parking programs are first collected from parking space owners and users under varying monetary-linked incentives and disincentives in China. Then, the nonlinear and interaction effects of influencing variables on WTP are uncovered using XGBoost and SHAP interpretable machine learning techniques. The results reveal that compared with the baseline methods, the adopted model demonstrates superior performance in predicting WTP in private shared parking; Personal attributes, along with rewards and penalties, emerge as the most influential factor categories and exhibit significant nonlinear and interaction effects; The effect of key factors, such as reward bonus, penalty payment, education, average monthly income, parking space idle duration, concerns about sharing revenues, weekly driving frequency, having used shared parking, varies substantially across unwilling, neutral, and willing attitudes of parking space owners and users. The findings could help provide valuable insights for government agencies and management operators to further improve private shared parking initiatives and expand their markets.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2654638</guid>
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    <item>
      <title>Manage the Curb: Optimization of Time-Varying Parking Zones in Micromobility Systems</title>
      <link>https://trid.trb.org/View/2616178</link>
      <description><![CDATA[Station based and free floating are the two established parking regimes of micromobility systems. The former restricts pickup and drop-off to designated stations, which is less convenient for users but reduces the nuisance of sloppily parked rental bikes and scooters. Free-floating micromobility allows users to use any public parking space within the operating area, which increases user flexibility but creates organizational overhead to deal with improperly parked vehicles. Time-varying parking zones, realized via curbside management software (CMS) and geofencing technology, promise a reasonable compromise in the convenience-clutter trade-off. Based on spatiotemporal information, the city administration can either permanently (e.g., pedestrian zones) or temporarily (e.g., weekly farmers’ market) block certain urban areas in their CMS. The micromobility providers, also having access to the CMS, must ensure that vehicles are not returned to undesignated areas with digital fences during the announced times. This paper introduces an optimization approach for micromobility providers to plan time-varying parking zones, given the dynamic municipal parking limitations. Opening and closing urban areas for parking not only requires a digital reaction (i.e., (un)blocking via geofencing) but also produces costs (e.g., removing the remaining scooters of previous periods from the market square). Hence, our optimization task aims to minimize the total costs associated with dynamic parking zones, whereas representative user trips are guaranteed travel within a given time budget. Based on this setting, we show that most urban stakeholders can profit from time-varying parking zones (compared with a static operating area). Our case study based on Berlin-Mitte shows that dynamic parking zones reduce urban space usage at decreasing service costs and only slight user concessions regarding their convenience.]]></description>
      <pubDate>Mon, 02 Feb 2026 09:33:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2616178</guid>
    </item>
    <item>
      <title>Expanding the Public Supply of Parking Through the Conversion of Privately Owned Lots into Public-Private Facilities</title>
      <link>https://trid.trb.org/View/2613656</link>
      <description><![CDATA[The Metro Crenshaw/LAX rail-transit line is currently under construction and planned for completion in 2019. The rail-transit line will connect the Metro Expo Line to the Los Angeles Airport. Installation of the project will require road surface space at some segments and as a result, it will run at-grade in the Park Mesa Heights Neighborhood of South Los Angeles. Construction on the commercial Crenshaw Boulevard from 48th Street to Slauson Boulevard requires the removal of over 300 parking spaces. Business owners along the corridor fear that the loss of parking will create barriers for employees and customers to access their establishments. This report examines shared parking as a parking management treatment that can increase the supply of parking without building more of it. Shared parking comes in multiple forms, but this report uses "shared parking" as the following: A business with off-street parking contracts with a private parking operator to charge non-customers for parking in the lot; The parking operator manages the parking lot and shares the parking revenue with the business owner; Some businesses, such as banks, make the parking lot available to the public during non-business hours; Businesses with consistent vacant spaces during business hours will have the parking operator make these spaces available to the paying public even when the business is open; and The process is facilitated through a contract between business owners and a private parking operator. The report assesses the technical and political feasibility of a shared parking program.]]></description>
      <pubDate>Sat, 13 Dec 2025 17:00:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613656</guid>
    </item>
    <item>
      <title>A multidimensional analysis of potential suppliers’ behavioral intentions in shared parking: Insights from SEM, NCA, and fsQCA</title>
      <link>https://trid.trb.org/View/2611511</link>
      <description><![CDATA[Residential shared parking has garnered growing interest as a strategy to alleviate parking scarcity and enhance space utilization. However, private parking space suppliers hesitate to participate in shared parking programs due to the trade-offs between benefits and risks. Therefore, understanding the motives behind the reluctance of potential suppliers is crucial for incentivizing their participation. This study integrates the technology acceptance model (TAM) and expectation confirmation theory (ECT) to investigate the formation mechanisms of behavioral intentions. A three-step analytical approach is employed, comprising structural equation modeling (SEM), necessary condition analysis (NCA), and fuzzy-set qualitative comparative analysis (fsQCA). SEM is used to validate the causal relationships and net effects among variables within TAM and ECT, while NCA is used to identify the key prerequisites of potential supplier participation. Finally, fsQCA examines how different configurational effects shape behavioral intentions. The SEM findings suggest that although potential suppliers accept shared parking technology, high decision-making costs (e.g., time and maintenance) reduce their satisfaction and willingness to participate. Further multigroup analyses reveal heterogeneous decision-making motivations in which owners are more risk-averse, whereas renters prioritize stable returns. Additionally, NCA and fsQCA reveal that owners’ behavioral intentions are driven by confirmation and perceived availability, while renters’ intentions depend on confirmation, expectation, satisfaction, and social influence. Nevertheless, perceived risk and low availability are the principal obstacles for both groups. By integrating TAM and ECT, this study enriches the theoretical understanding of shared parking and provides practical recommendations for enhancing potential supplier participation.]]></description>
      <pubDate>Tue, 11 Nov 2025 09:25:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2611511</guid>
    </item>
    <item>
      <title>Long-term effects of China’s three-year dynamic Zero-COVID policy on shared parking usage, resilience, and development: Empirical evidence from Guangzhou, China</title>
      <link>https://trid.trb.org/View/2597159</link>
      <description><![CDATA[China maintained the world’s strictest and most enduring COVID-19 containment policy, the dynamic Zero-COVID policy, which enforced a zero-tolerance to infections from 2020 to 2022. Although studies have shown significant effects of pandemic policies on shared mobility services, the influence of China’s distinctive policy on shared parking, an emerging shared mobility mode, remains poorly understood. Most existing research has focused only on the short-term impacts of the initial 2020 outbreak, neglecting long-term effects for the whole period of dynamic Zero-COVID policy. This study uses empirical data from AirParking, China’s largest shared parking platform, covering November 2018 to October 2022, to examine the long-term impacts of the dynamic Zero-COVID policy on shared parking. Event study results reveal that each COVID-19 outbreak led to a sharp decline in shared parking usage yet an increase in average parking duration. Clustering via the Partitioning Around Medoids (PAM) algorithm further indicated a shift in trip purposes toward office-related long-term parking and a reduction in shared parking use within residential areas. In-depth interviews with Airparking senior managers and urban planners revealed that user’s loyalty and internal platform operations were unaffected, but the policy considerably disrupted on-site management of shared parking lots. These findings enhance understanding of the resilience of shared parking under stringent public health control measures and provide practical insights for policy design and operational strategies in future health emergencies affecting shared and overall mobility.]]></description>
      <pubDate>Mon, 13 Oct 2025 13:52:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2597159</guid>
    </item>
    <item>
      <title>Predicting and explaining parking space sharing behaviors using LightGBM and SHAP with individual heterogeneity considered</title>
      <link>https://trid.trb.org/View/2561687</link>
      <description><![CDATA[Shared parking plays a crucial role in alleviating parking pressure, but the heterogeneity of potential suppliers’ intentions was often ignored. This study addresses this gap by adopting an interpretable Machine Learning (ML) framework to investigate parking space sharing intentions, considering individual differences. A survey with 383 respondents from mainland China was conducted, and a Latent Class Model (LCM) identified three distinct groups of potential suppliers. The Light Gradient Boosting Machine (LightGBM), outperforming other ML models, was used to quantify factors influencing sharing behaviors. The SHapley Additive exPlanation (SHAP) approach revealed that influential factors vary across different latent classes. These findings provide insights for shared parking operators to encourage potential suppliers’ participation in shared parking.]]></description>
      <pubDate>Thu, 21 Aug 2025 09:19:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2561687</guid>
    </item>
    <item>
      <title>Enhanced Benders decomposition approach for shared vacant private parking spaces allocation method considering uncertain parking duration of demanders</title>
      <link>https://trid.trb.org/View/2543903</link>
      <description><![CDATA[The authors study a shared vacant private parking spaces allocation problem that considers the uncertain parking duration of demanders. To solve the problem, they first formulate a stochastic programming model (P model). The objective is to maximize the weighted sum of the total expected profits from the platform parking revenue, overload cost and idle cost. On this basis, they reformulate the P model into the UPDA model based on the sample average approximation. Unlike the traditional construction of Benders cut using the dual problem, they construct a new Benders cut based on the lower bound of the subproblem, and then propose an efficient enhanced Benders decomposition (EBD) algorithm for solving the UPDA model. Finally, the performance of the algorithm is verified by numerical experiments. The experimental results show that the enhanced Benders decomposition algorithm outperforms both the Benders decomposition algorithm and commercial solver, and can effectively solve large-scale problems with high complexity. The experimental results also show that the uncertainty in the parking duration of the demander has negative impact on the system performance.]]></description>
      <pubDate>Fri, 23 May 2025 15:35:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2543903</guid>
    </item>
    <item>
      <title>Private parking space owners’ choice behavior of different sharing modes: hybrid choice model using justified latent variables</title>
      <link>https://trid.trb.org/View/2533959</link>
      <description><![CDATA[Private parking spaces account for a large proportion of potential parking resources, whose utilization rate could be raised by sharing them. To investigate private parking space owners’ sharing choice behavior, this paper applies a framework of Combined Technology Acceptance Model and the Theory of Planned Behavior for a more comprehensive consideration of psychological attitudes on these suppliers in urban residential areas. A web-based survey was conducted to collect data. The justified factors are then incorporated in hybrid choice model (HCM) as latent variables. HCM results showed that incorporation of latent variables such as perceived risk provides better fitting effect than traditional multinominal models, and that revenues and community participance are influential factors for sharing choice. The authors' findings indicate behavioral intention framework could serve as argumentation of rational selection of latent variables. These findings could also support better implementation of shared parking from managerial and operational perspectives.]]></description>
      <pubDate>Wed, 30 Apr 2025 16:59:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2533959</guid>
    </item>
    <item>
      <title>Do residential areas require shared parking? A case study of Tianjin, China</title>
      <link>https://trid.trb.org/View/2519462</link>
      <description><![CDATA[Shared parking has shown great potential in alleviating the shortage of parking spaces, particularly within residential areas with high parking demand. However, studies on shared parking's effectiveness in meeting nighttime parking demand remain limited. This study investigates whether shared parking facilities, integrating existing resources, can effectively alleviate nighttime parking shortages in residential areas. Using empirical data from Tianjin, China, the spatiotemporal patterns of potential shared parking demand are analyzed. The research results indicate that approximately 70 % of nighttime shortages in residential areas can be addressed through shared parking resources provided by surrounding buildings. Additionally, this study explores the nonlinear relationship between the built environment and shared parking demand, providing a quantitative analysis. Explainable machine learning techniques reveal that the built environment factors have obvious nonlinear effects and threshold effects on demand for shared parking. The important thresholds that significantly affect the demand for shared parking vary across different built environment factors. The identification of these threshold values can be beneficial for providing tailored policy to integrate existing parking facilities into shared parking, aligning with varying resource availability and residential area demands.]]></description>
      <pubDate>Wed, 19 Mar 2025 16:58:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2519462</guid>
    </item>
    <item>
      <title>The distribution of shared parking use in time and space: A case study in Guangzhou, China</title>
      <link>https://trid.trb.org/View/2506268</link>
      <description><![CDATA[Shared parking enables private parking owners to share their parking spaces during idle time. In recent years, increasingly more research investigated people’s intentions to participate in shared parking schemes as well as optimization algorithms to match shared parking supplies and demands. However, little research has investigated the distribution of shared parking use in time and space in implementation. To fill this gap, this study uses the transaction records of 121 shared parking lots in Guangzhou, China, and applies a quasi-Poisson regression model to analyze the influence of a set of explanatory factors on the total number of transactions. The results show that the number of parking transactions is significantly influenced by implemented duration, parking lot capacity, land use of shared facility, number of POIs (point of interest), and transit stations within a range of 750 meters from the shared parking lot. This study also applies a linear regression model to analyze the effect of a set of explanatory variables on the average parking duration at shared parking lots. The results show that the average parking duration is significantly influenced by the land use of a shared facility, number of office buildings within 750 meters from the shared parking lot, and peak time of the shared parking lots.]]></description>
      <pubDate>Thu, 13 Feb 2025 17:25:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2506268</guid>
    </item>
    <item>
      <title>Research on shared parking allocation considering the heterogeneity of parking slot providers’ temporary parking demand</title>
      <link>https://trid.trb.org/View/2464695</link>
      <description><![CDATA[Studies on the allocation of parking demand during the sharing period primarily focus on public parking users, ignoring parking slot providers’ temporary parking demand with heterogeneity. Therefore, this paper takes the allocation of parking slot providers’ temporary parking demand as the research object and establishes a differentiated parking allocation (DPA) model to maximize the platform’s net profit. The model is solved using the ant colony optimization (ACO) algorithm and compared with the First-Come-First-Served (FCFS) algorithm. Then, the platform adopts differentiated or undifferentiated charge measures when charging for the parking slot providers’ temporary parking demand. The numerical analysis is performed to select three indicators for evaluation: 1) the utilization rate, 2) the net profit, and 3) the degree of time fragmentation. Results show that the ACO algorithm has an excellent optimization effect in allocating, and the differentiated allocation-undifferentiated charges for the parking slot providers’ temporary parking demand is feasible.]]></description>
      <pubDate>Mon, 27 Jan 2025 15:39:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2464695</guid>
    </item>
    <item>
      <title>Making the most of your private parking slot: Strategy-proof double auctions-enabled staggered sharing schemes</title>
      <link>https://trid.trb.org/View/2453857</link>
      <description><![CDATA[Platform-intermediated Private Parking Slot Sharing (PPSS) is broadly deemed a viable avenue to alleviate parking problems in metropolises. Despite a captivating future where PPSS will be as convenient as public parking today, tension is mounting in practice concerning how to efficiently match and price self-interested suppliers and demanders with incomplete information. To reconcile this tension, this paper delves into the nuances of PPSS operations and proposes double auction-based solutions that embed staggered sharing to integrate fragmented non-commute-driven demand. Confronting the intertwined difficulties of temporally heterogeneous and incompatible demands imposed by staggered sharing on auction mechanism design, the authors first propose a Demand Classification-based Trade Reduction (DCTR) auction mechanism that teases apart the conflated demands through the idea of “divide and conquer”. The authors prove theoretically that the DCTR auction mechanism satisfies Strategy-Proofness (SP), Budget Balance (BB), and Individual Rationality (IR) in general, and Asymptotic Efficiency (AsE) when demand categories are finite. To cut down the welfare loss due to distributed trade reduction in the DCTR auction mechanism when demands are diversified, the authors propose a family of Group Buying-based Trade Reduction (GBTR) auction mechanisms that unify demands through a preceding grouping process and conduct one unified trade reduction only. The authors contrive alternative group bid determination and trade reduction rules to accommodate distinct market conditions. To strengthen privacy preservation and relieve the strategy identification burden of cognitively limited bidders, the authors further design the Double-Clock implementations of the GBTR auction mechanisms (DC-GBTR) that additionally satisfy Unconditional Winner Privacy (UWP) and Obvious Strategy-Proofness (OSP). A hybrid mechanism is further designed to enable the integration of mechanisms that could induce budget deficits and orchestrate different auctions by automatically selecting the proper one depending on market conditions while ensuring BB in expectation. Extensive experimental results highlight the merits of incorporating staggered sharing in auction design, shed light on how to choose among alternative auctions to cater to distinct market conditions, showcase the superiority and potential of hybridization, and deduce managerial insights from the perspectives of different stakeholders to facilitate the navigation of PPSS marketplaces.]]></description>
      <pubDate>Wed, 27 Nov 2024 13:42:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2453857</guid>
    </item>
    <item>
      <title>On the service differentiation for parking sharing</title>
      <link>https://trid.trb.org/View/2450548</link>
      <description><![CDATA[This paper models and optimizes a two-sided market of shared parking where the parking sharing platform rents spare parking spaces from owners and provides them to parkers. Different parkers may derive a different utility or benefit from renting and using a parking space from the platform and their willingness-to-pay for the parking sharing service may differ. In this context, the authors consider that the platform can provide differentiated services to parkers, i.e., priority and normal services. The priority service will secure the rights to be matched with the parking supplies firstly, but may involve a higher service price. The authors model the parking supply–demand equilibrium for such a two-sided market with differentiated services and compare it against that under single-type (homogeneous) service. The authors also analyze how the supply–demand equilibrium varies with the platform’s pricing strategies (service prices and rent paid to parking owners). Then, the authors discuss and compare the parking sharing platform’s pricing strategies under different economic objectives (i.e., maximize net revenue or social benefit) and under different service structures (i.e., single-type service or differentiated services). The authors found that differentiated services can help improve platform revenue and social welfare.]]></description>
      <pubDate>Wed, 20 Nov 2024 12:00:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2450548</guid>
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