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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>
    <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>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Understanding public perceptions of shared e-scooters: An investigation from rider and non-rider perspectives</title>
      <link>https://trid.trb.org/View/2696188</link>
      <description><![CDATA[The rapid growth of e-scooter sharing schemes has sparked both enthusiasm and controversy, prompting cities to develop new regulations to address safety, accessibility, and public space management. The attitudes and behaviours of both riders and non-riders can determine the success or otherwise of shared e-scooter services, rendering public perceptions of these schemes a key source of information for policymakers and practitioners. Using data from an online survey of riders (N = 401) and three non-rider focus groups (N = 24) across three trial locations, this paper examines public perceptions of shared e-scooters from the perspective of both riders and non-riders. The analysis explores the themes of awareness of shared e-scooters, perceived benefits of shared e-scooter use and perceived barriers of use. We then focus solely on riders and explore rider satisfaction (including latent class modelling), motivations for use and future intentions to use shared e-scooters. Findings reveal clear distinctions in perceptions between riders and non-riders of shared e-scooters. Riders generally have a positive view of the shared e-scooter trial and are likely to continue their use. Disparities in gender, age, and income among riders highlight the need for inclusive design of shared schemes. The perception among non-riders is shaped by both their level of awareness of the scheme and their indirect experiences with the vehicles, with concerns related to levels of awareness of the trial scheme, uncertainty about riding rules, safety issues, and difficulty distinguishing between shared and privately owned e-scooters.]]></description>
      <pubDate>Wed, 29 Jul 2026 09:16:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2696188</guid>
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    <item>
      <title>A quality assessment method for recycled coarse aggregate based on image operations</title>
      <link>https://trid.trb.org/View/2691685</link>
      <description><![CDATA[A two-parameter quality evaluation method based on image recognition was proposed to quantitative evaluation of the weak mortar layer on the surface of recycled coarse aggregate (RA). The accuracy of traditional image recognition technology used in the interface recognition between mortar and RA is improved by constructing a clustering algorithm based on color space conversion. Thus, the accurate measurement of the mortar adhesion rate and shape coefficient based on the quantitative index of the natural aggregate particle type characteristics is realized. Results show that: (1) the clustering algorithm successfully solves the problem of the color and shadow interference between RA and mortar; (2) this method has the advantages of non-contact, low cost, automation. It can build two application modes of the online detection system and on-site portable detection equipment; (3) the quantitative evaluation system was established and can provide a scientific basis for the classification and utilisation of RA.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:50:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691685</guid>
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    <item>
      <title>Physical and virtual space: a critical review of accessibility concepts and measurements</title>
      <link>https://trid.trb.org/View/2719386</link>
      <description><![CDATA[This study revisits the concept of accessibility amid the expanding role of virtual and hybrid spaces. As digital platforms increasingly shape how people engage with jobs, services, and goods, traditional models that emphasise spatial proximity and travel costs no longer reflect how access operates today. Drawing on the four core components of accessibility – transportation, land use, temporal, and individual – this study reviews recent conceptual and empirical work that measures access in digitally mediated settings. It evaluates infrastructure-based, location-based, and person-based approaches, with particular attention to equity concerns. The results point to persistent variation in access, driven by differences in broadband infrastructure, digital literacy, and the spatial coverage of online platforms. The study highlights the need for more detailed and context-aware methods of measuring accessibility and calls for planning tools and future works that incorporate both virtual and physical constraints in urban systems.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2719386</guid>
    </item>
    <item>
      <title>Online monitoring and safety assessment of heavy-haul distributed power trains: Technical strategies and application practices in China</title>
      <link>https://trid.trb.org/View/2683120</link>
      <description><![CDATA[With the significant increase in tractive tonnage of heavy-haul railway transportation, the deterioration of the dynamic performance of long-marshaled heavy-haul trains during long-term operation has become increasingly prominent. Therefore, the online monitoring and performance evaluation of the operation status and running safety of heavy-haul distributed power (DP) trains under service complex environments become particularly important. This paper systematically reports the online monitoring technologies and safety assessment strategy of heavy-haul DP trains in China. A multi-layered integrated monitoring system for heavy-haul DP trains is developed, which encompasses multi-dimensional parameter monitoring including longitudinal train dynamics, vibration characteristics of locomotives and wagons, wheel-rail contact status, and train pneumatic brake performance. Leveraging distributed sensor networks and 5G dual-mode communication technology, the system achieves multi-sectional data acquisition and rapid synchronous transmission across ultra-long train formations. The engineering application practices on the Shuozhou-Huanghua Railway demonstrates that this technical framework can significantly enhance proactive safety protection capabilities for long heavy-haul trains, providing replicable solutions for efficient operation and maintenance under complicated working conditions. Future studies should focus on optimizing measurement point layouts, dynamic threshold configurations, and cross-system data fusion mechanisms to promote sustainable development of safer heavy-haul railways.]]></description>
      <pubDate>Mon, 29 Jun 2026 09:12:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683120</guid>
    </item>
    <item>
      <title>Explainable Data-Driven Multi-filter Framework for Bot Detection in Incentivized Online Surveys</title>
      <link>https://trid.trb.org/View/2714318</link>
      <description><![CDATA[Online surveys have become increasingly popular for academic research due to their cost-effectiveness and ability to reach large populations. However, the use of monetary incentives to encourage participation has led to widespread infiltration by automated bots designed to complete surveys fraudulently. This study presents a transparent, multi-filter framework to detect and remove bot responses, using an incentivized online transportation survey on cycling preferences as a case study. The survey received 12,020 responses over 94 days, with clear evidence of bot activity including 3951 submissions (32.9%) concentrated on a single day. To secure the dataset, the authors developed an 11-filter pipeline spanning four categories: platform risk scores, duplicate identity detection, behavioral interaction patterns, and device consistency. The multi-filter pipeline removed 94.8% of the submissions. Sensitivity analyses reveal that while platform risk scores (reCAPTCHA, fraud score) screen the bulk of automated traffic, behavioral timing and device checks are essential for catching sophisticated bots. To establish ground-truth performance, the authors conducted a blind expert review on a data subsample, achieving an 88.9% agreement rate between the automated pipeline and independent human judgment. Finally, to audit the internal coherence of the rules, the authors trained an explainable XGBoost classifier. The model independently recovered the filter decisions with an F1 score of 0.94 for the human class (precision 0.90, recall 0.98), proving the pipeline captures statistically separable behavioral clusters rather than arbitrary noise. This open-source framework provides researchers with a generalizable, evidence-based template for ensuring data integrity in online surveys.]]></description>
      <pubDate>Tue, 23 Jun 2026 13:50:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714318</guid>
    </item>
    <item>
      <title>How accessible are transport surveys? A scoping review of current practice and gaps</title>
      <link>https://trid.trb.org/View/2706469</link>
      <description><![CDATA[Online surveys have become a central tool in travel behavior research, offering efficient and scalable ways to collect data. However, the extent to which these surveys are designed to be accessible for people with disabilities remains unclear. This paper addresses this gap through a narrative scoping review that examines how accessibility is considered and reported in transport studies that use online surveys. The review is guided by three questions: first, to what extent do transport studies report the use of accessibility measures; second, what types of adaptations are used to support participation among people with visual, cognitive, and learning disabilities; and third, what recommendations can be drawn from existing studies to guide more inclusive survey design in future transport research. The review of 38 studies published between 2019 and 2025 indicates limited reporting of accessibility considerations within survey practice. Only a small number of studies explicitly describe accessible recruitment approaches, survey adaptations, or compatibility with assistive technologies. Even in studies that include disabled participants, the reporting of accessibility measures is inconsistent or absent. These patterns suggest that accessible online survey design is not systematically integrated within transport research methodologies. To support the development of more inclusive practices, the paper synthesizes the review findings into an accessibility evaluation metric comprising elements such as: overall accessibility adaptations, inclusive recruitment strategy, survey tool adaptations, pilot testing for accessibility, multiple access modes, assistive technology support, and accessibility modifications presented. The paper further provides a set of practical, evidence-based dimensions to guide more inclusive online data-collection practices, positioning accessibility as a core methodological requirement rather than an optional enhancement.]]></description>
      <pubDate>Thu, 18 Jun 2026 16:34:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706469</guid>
    </item>
    <item>
      <title>Online multi-modal evacuation during passenger flow outburst in urban transit system: A heterogeneous multi-agent reinforcement learning framework</title>
      <link>https://trid.trb.org/View/2599190</link>
      <description><![CDATA[With growing demand straining urban transit systems’ resilience in managing outburst passenger flows, existing approaches focused on offline and single-modal evacuations remain limited. This study proposes an online multi-modal evacuation framework that coordinates on-duty taxis, buses, and metros while minimizing impact on their regular services. We develop a data-driven agent-based environment to update multi-modal transit data and stranded passenger information in real time. Two coordination strategies are introduced: (1) an independent strategy using a decentralized training and distributed execution algorithm, and (2) a collaborative strategy using a hybrid centralized training and distributed execution algorithm. To dynamically assess evacuation effectiveness, we design a resilience framework with three metrics: robustness, rapidity, and resourcefulness. These metrics are transformed into demand-responsive feedback at each time step, enabling agents to proactively generate resilient evacuation plans. In a real-world case study triggered by a railway disruption, our approach outperforms genetic algorithms and multi-agent deep deterministic policy gradient algorithms in computation time and solution quality under offline conditions. Simulated new environments further validate its online applicability, demonstrating its potential for real-world deployment.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599190</guid>
    </item>
    <item>
      <title>Pricing policy and queue-length disclosure in on-demand service platforms</title>
      <link>https://trid.trb.org/View/2607001</link>
      <description><![CDATA[Online service platforms, such as ride-hailing and freight exchanges, generate revenue and profits through commissions. To attract users and maximize profit while managing platform costs, these platforms strategically implement different pricing and queue-length disclosure policies. Dynamic pricing based on queue length can increase revenue but may also reduce user loyalty, leading to higher platform costs. The choice of queue-length disclosure policy influences customer balking behavior: revealing queue lengths may deter users from joining if they perceive the wait as too long, while not disclosing the queue length leads customers to decide probabilistically, driven by uncertainty about the wait time. We analyze a two-sided queueing model in which both customers and suppliers arrive randomly, queue separately, and engage in immediate matching at the front of the queue. We examine different pricing and queue-length disclosure policies to maximize the platform’s expected profit. Optimizing the underlying semi-Markov decision process requires solving a non-convex quadratically constrained quadratic program. Through uniformization, we derive and solve the optimality equations, and then compare the resulting optimal prices, profits, and throughput. Our findings indicate that pricing and queue-length disclosure policies are complementary. Specifically, dynamic pricing and visible queue lengths both increase expected profit, while static pricing and invisible queue lengths both increase throughput. These outcomes are driven by changes in the average transaction price under different policies. We identify unique thresholds that determine the preferred pricing and queue-length disclosure policies. The choice of pricing policy depends on the extra cost of implementing dynamic pricing compared to a static price, while the selection of queue-length disclosure policy depends on customer sensitivity to service delay.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2607001</guid>
    </item>
    <item>
      <title>Joint online update of model structure and parameters for battery equivalent circuits using impedance spectroscopy and machine learning</title>
      <link>https://trid.trb.org/View/2706491</link>
      <description><![CDATA[Accurate battery state estimation is a crucial function of the battery management system in electric vehicles. Model-based estimation methods, particularly those employing equivalent circuit models, are widely used due to their favorable trade-off between simplicity and accuracy. However, as the battery ages, both the model structure and its parameters can change, leading to reduced estimation reliability. Traditional online parameter update methods, such as filter-based or recursive least squares approaches, are limited by high computational demands, sensitivity to noise, and their inability to adapt the model structure. Electrochemical impedance spectroscopy offers detailed insight into internal battery processes and is commonly used in laboratory settings for model identification. It also shows great potential for onboard applications, particularly in light of recent improvements in compact impedance measurement hardware and the associated cost reductions. However, effective algorithms for utilizing impedance data in onboard applications remain underexplored.This paper presents a hybrid machine learning framework that jointly performs structure selection and parameter identification of equivalent circuit models using impedance data for onboard application. An impedance dataset was generated from a battery aging study using dynamic cycling profiles that reflect real-world electric vehicle usage under varied conditions. Each spectrum was labeled with the best-suited equivalent circuit model to support framework development. The proposed framework integrates an extreme gradient boosting classifier for model structure selection and structure-specific feed-forward neural networks for parameter identification. The results demonstrate high modeling accuracy and strong potential for onboard implementation.]]></description>
      <pubDate>Thu, 11 Jun 2026 09:29:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706491</guid>
    </item>
    <item>
      <title>Digitalization of Maritime Transportation Disputes: Legal Harmonization and Procedural Gains through Online Dispute Resolution</title>
      <link>https://trid.trb.org/View/2706171</link>
      <description><![CDATA[The maritime sector faces increasing pressure to modernize dispute resolution systems as digitalization exposes known gaps in enforceability, procedural consistency, contractual comprehension, and cross-border risk, while also introducing uncertainties linked to emerging technological and legal challenges. This study evaluates the functionality of current maritime resolution systems and the limited uptake of the Rotterdam Rules—despite their objective to provide legal certainty and uniformity for multimodal carriage since 2009—highlighting their relevance to digital processes. It situates online dispute resolution (ODR) within maritime law by examining doctrinal compatibility with admiralty jurisprudence and established arbitration frameworks, including high-court interpretations of party autonomy, fairness, and evidence standards. The research adopts an institutional–organizational perspective to position the proposed political-institutional paradigm within broader public, private, and compliance-governance structures that guide system integrity and mitigate risks of noncompliance and embedded bias. It clarifies jurisdictional limits and liability transitions along end-to-end transport chains to support structured, platform-ready ODR pathways for multimodal disputes. The analysis also notes that existing treaty frameworks do not preclude the use of electronic processes, offering interpretive space for digital adjudication. The model emphasizes coordinated standard-setting by the International Maritime Organization, the Baltic and International Maritime Council, and the United Nations Commission on International Trade Law to ensure neutral, legally harmonized, and technically reliable ODR protocols. In line with cooperative principles reflected in instruments such as the Law of the Sea Convention, this study affirms ODR as a complementary and forward-looking mechanism. Analysis of 194 maritime cases shows ODR can yield nonarbitrary, efficient, and cost-effective outcomes, complementing the gradual evolution of instruments such as the Rotterdam Rules.]]></description>
      <pubDate>Wed, 27 May 2026 10:48:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706171</guid>
    </item>
    <item>
      <title>Enhanced H-Gasa Algorithm for Efficient Path Optimisation in Online Ride-Hailing Carpooling</title>
      <link>https://trid.trb.org/View/2666430</link>
      <description><![CDATA[Online ride-hailing carpooling services often need help with bottlenecks, such as delayed response times and low computing efficiency, which negatively impact user experience and platform operation. Current path optimisation algorithms also need help managing real-time dynamic requests and large-scale computing challenges. In this respect, this paper proposes a bi-directional path-based online taxi carpooling optimisation model that considers road network conditions and time window constraints. It minimises operating and passenger travel costs under multiple constraints. The fitness assessment and acceptance criteria are optimised based on a genetic algorithm, combined with the temperature regulation mechanism of simulated annealing, and a hybrid genetic-simulated annealing algorithm (H-GASA) is proposed. In addition, this paper brings the parallel repair mechanism and accelerates the solution repair process using modern multi-core processors and parallel computing framework, significantly improving the solution efficiency. The experimental results show that the H-GASA algorithm substantially reduces the passenger travelling time and vehicle operating cost under multiple time windows, which is better than the existing algorithms and effectively solves the common premature convergence problem of genetic algorithms. The study verifies the efficiency and reliability of the algorithm in practical applications and provides strong technical support for optimising online carpooling services.]]></description>
      <pubDate>Tue, 26 May 2026 09:41:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666430</guid>
    </item>
    <item>
      <title>Intelligent scheduling framework for EV fast charging with waiting time reduction under charger availability constraints</title>
      <link>https://trid.trb.org/View/2647020</link>
      <description><![CDATA[The growing shortage of charging stations and escalating power consumption are resulting in extended wait times for electric vehicles (EVs) at charging locations. The effective scheduling of electric vehicle charging to save operational expenses and minimize waiting times in settings with restricted charger access is a significant optimization challenge. A novel improved Highest Response Ratio Next algorithm integrated with the Walrus Optimization Algorithm (IHRRN-WaOA) is proposed to address the scheduling challenge under constraints imposed by limited charging infrastructure. The proposed approach is structured as a two-step optimization framework, where the first step solves the charger allocation problem to minimize wait times, and the second step optimizes charging schedules to reduce both charging costs and battery degradation costs while satisfying EV energy demands. A dynamic online scheduling mechanism is introduced, leveraging the schedulable time of EVs and real-time fluctuations in energy demand to achieve optimal scheduling decisions. Experimental results demonstrate that the proposed IHRRN-WaOA method significantly reduces both total waiting time and station operating costs. Specifically, the method achieves a 19.47% reduction in waiting time compared to First-Come-First-Serve (FCFS) and a 14.89% reduction compared to the Highest Response Ratio Next technique. Additionally, the proposed method lowers the operational costs by 8.88% compared to FCFS and by 6.401% compared to HRRN, making it highly effective for both low- and high-incoming EV traffic scenarios.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647020</guid>
    </item>
    <item>
      <title>Standardizing the User Experience in Urban Geoportals: An Integrated Model for Urban Experience</title>
      <link>https://trid.trb.org/View/2657002</link>
      <description><![CDATA[Urban geoportals are gaining ground globally. In this regard, integrating the ideals of user experience (UX) or UX with the urban geoportals would possibly usher in an era of better experiences and provisioning of services. We studied the fundamental theories of user experience, geoportals, and map visualization and proposed a way for their integration. The integrated model for urban experience is proposed as the integrated module for enhancing user experience and satisfaction. It would amplify the experiential quotient of the user by enabling accessibility, usefulness, usability, emotive responses and visual efficacy. Besides, all these also make service provisioning and emergency response faster and more efficient. However, the integration suffers from some hindrances, mostly extrinsic. Resolving these obstacles promises a prosperous future for the UX-urban geoportal alignment.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2657002</guid>
    </item>
    <item>
      <title>Understanding the determinants of user choice in ride-hailing motorcycle services: evidence from Indonesia</title>
      <link>https://trid.trb.org/View/2643196</link>
      <description><![CDATA[The expansion of ride-hailing motorcycle services has transformed urban transportation in Indonesia, offering convenience and affordability. However, misalignment between service features and user expectations remains a challenge. This study employs conjoint analysis to identify the most valued attributes among users of online motorcycle taxi platforms. A total of 200 respondents evaluated 12 orthogonal stimuli based on nine key attributes: timeliness, delivery speed, fare, vehicle cleanliness, payment options, driver communication, courtesy, travel insurance, and application interface. Results indicate that users prefer services that include penalties for late pickup, drivers selecting optimal routes, standardized cleanliness, eight payment methods, a fare of USD 0.11/km, mandatory communication, and a courteous driver demeanor. The driver courtesy requirement was the most influential factor, followed by cleanliness, communication, and punctuality. While preferred levels were consistent across genders, variations in importance values were observed. This study contributes to the body of knowledge by highlighting the cultural and operational factors shaping user preferences in emerging ride-hailing markets, offering insights that extend beyond Indonesia’s context. It provides empirical evidence for integrating user-centric attributes into service design to enhance adoption and retention.]]></description>
      <pubDate>Wed, 25 Mar 2026 15:50:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643196</guid>
    </item>
    <item>
      <title>Comparative Analysis of UI/UX Design in Flight Ticket Booking: A Case Study of Traveloka vs Tiket.com</title>
      <link>https://trid.trb.org/View/2664542</link>
      <description><![CDATA[In today’s digital era, online travel platforms serve as essential tools for users to conveniently book flights, with UI/UX design playing a crucial role in shaping user perceptions and interactions. As the competition between online travel agencies (OTAs) intensifies, platforms like Traveloka and Tiket.com are constantly improving their user interfaces and experiences to attract and retain users. This research aims to explore how UI/UX design affects user satisfaction and perceived usability in flight ticket booking services by conducting a comparative analysis between these two leading Indonesia OTAs. Using a quantitative approach, this study employed usability testing followed by the UMUX-LITE questionnaire to measure user perceptions on both platforms. From the responses of 31 participants, we found that while Tiket.com scores slightly higher in ease of use, Traveloka offers greater usefulness due to its more extensive filter options, such as student tickets and refundable flight. Overall, Traveloka achieved UMUX-LITE score of 79.570 (grade A-) compared to Tiket.com 77.957 (grade B+), showing that better functionality can positively impact the overall experience. However, Tiket.com cleaner and simpler interface led to more users (54.8%) to prefer it overall. These highlight the importance of balancing simplicity and functionality in UI/UX design, and offer insights for improving the user journey in digital travel platforms.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664542</guid>
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