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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>Assessment of Trans Banyumas Services Based on the Opinions of Female Passengers from a Promotional Point of View</title>
      <link>https://trid.trb.org/View/2686166</link>
      <description><![CDATA[Public transportation is a fundamental element significantly influencing smart cities and smart mobility within communities. Banyumas Regency is currently one of the regions implementing the smart city concept in its urban development. One of the tangible proofs of this implementation by the Banyumas Regency government is the introduction of BRT Trans Banyumas, aimed at increasing public interest in using public transportation, facilitating more effortless mobility, reducing air pollution, and boosting the local economy. Evaluating public transportation services is essential to attract public interest, particularly regarding the intelligent public transport system (IPTS) aspects. This study evaluates Trans Banyumas services to analyze the level of IPTS implementation from the perspective of female passengers. Female passengers' perceptions are used because women have unique mobility patterns, making them an essential indicator for assessing smart mobility. The method used in this research is General Linear Model ANOVA. Data collection was conducted qualitatively with 357 respondents. The test results show that demographics significantly influence the intelligent public transport system aspects: ICT, IoT, integration, safety and security, and smart accessibility and mobility. The result can be used to develop recommendations for improvements in the Trans Banyumas service related to intelligent public transportation system technology. However, implementing an intelligent public transport system in the Trans Banyumas service cannot be done individually. Therefore, there needs to be cooperation from both the government and the private sector to promote sustainable transportation, reduce the use of private vehicles, and minimize environmental impacts.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:29:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686166</guid>
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    <item>
      <title>Service Level Requirements for Real Life–Sized Bicycle Sharing Systems</title>
      <link>https://trid.trb.org/View/2686229</link>
      <description><![CDATA[This paper presents a two-step approach to managing service level requirements (SLRs) in real-life bicycle sharing systems (BSSs). SLR is a general concept that broadly describes how to effectively manage a BSS to improve user satisfaction while minimizing system operation costs. The two steps consist of two proposed problems: First, the target-level problem computes target bicycle quantities for stations, maximizing trip satisfaction. Second, the bicycle rebalancing problem designs vehicle routes to adjust bicycle quantities. The SLR literature includes several variants of these problems, but to our knowledge, very few exact approaches such as the one we propose can successfully handle real-life BSS, which comprise thousands of stations, tens of thousands of bicycles, and nearly 100,000 daily trips. We gather data from real-life BSSs from Boston, Chicago, Madrid, Mexico City, Montreal, New York, San Francisco, Toronto, and Washington, DC. From a managerial perspective, our numerical results provide the decision makers of BSSs with several insights related to bicycle and station usage throughout the network of stations.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:03:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686229</guid>
    </item>
    <item>
      <title>Evaluation of Walk Access Environment around Metro Stations from Pedestrians’ Perspectives Using an Integrated Revised IPA Fuzzy c-Means Clustering Technique</title>
      <link>https://trid.trb.org/View/2683156</link>
      <description><![CDATA[The current study employs an integrated revised importance-performance analysis (IPA) and fuzzy c-means clustering approach to evaluate user perceptions and identify priority areas for enhancing the walk access environment around metro stations in Delhi, India. Targeting commuters who walk to metro stations, the study gathered responses from 466 users through face-to-face interviews using smart tablets. The survey respondents rated their perceived importance and satisfaction toward 12 selected service attributes on a six-point Likert scale. The derived importance of service attributes was estimated, and the fuzzy 𝘤-means clustering technique was used to generate factor structures and management scheme clusters. These clusters helped identify critical areas for intervention. The study also suggested a priority order for judicious allocation of resources to improve attributes affecting walking as an access mode to metro stations. The research outcomes indicated that Universal design considerations, followed by Illumination, Safety and security, and Extreme weather conditions, required immediate resource allocation for improvement. Footpath availability performed optimally and needed resources only for maintenance. Meanwhile, Walking comfort, Footpath width, Signage, and Access time were relatively at a lower priority for resource allocation. This study can offer valuable insights for urban planners, policymakers, and transport officials to develop strategies to enhance walk accessibility to metro stations and promote active transportation.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683156</guid>
    </item>
    <item>
      <title>Belief updating in the low-altitude economy: safety information, presentation context, and willingness to pay</title>
      <link>https://trid.trb.org/View/2681477</link>
      <description><![CDATA[When a new service is introduced, business success hinges on how consumers perceive its risks. This study examines public attitudes toward low-altitude Passenger Transport (PT) and Goods Delivery (GD), focusing on perceived safety, willingness to participate, and willingness to pay (WTP). We field an online survey experiment with a mixed design: a within-subject contrast (Pre-Info → Post-Info) to assess updating after targeted safety statistics, and between-subject factors contrasting Single-project framing (SPF) versus Multi-project framing (MPF) and PT versus GD. Safety information increased perceived safety across all groups, and perceived safety was positively correlated with WTP both Pre-Info and Post-Info, with the association modestly stronger Post-Info. Presentation context also mattered: MPF yielded more favorable WTP distributions than SPF overall, with the strongest gains for GD. For PT, MPF reduced safety concern relative to SPF in Pre-Info comparisons, but its incremental Post-Info effect was small and not statistically significant in regressions. Across conditions, GD was viewed as safer and more acceptable than PT. These findings suggest that framing a new low-altitude service within a broader portfolio and providing concise safety statistics can enhance acceptance—especially for GD—while PT may require additional, service-specific assurances as part of a phased introduction strategy.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:54:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681477</guid>
    </item>
    <item>
      <title>An integrated data mining and multi-criteria decision models for assessing service quality in the airline industry</title>
      <link>https://trid.trb.org/View/2681292</link>
      <description><![CDATA[Traditional airline service quality research often faces limitations due to restricted survey sample sizes, hindering comprehensive passenger sentiment capture. This study seeks to overcome such constraints by leveraging big data and artificial intelligence (AI) methodologies. A novel, scientifically rigorous evaluation framework is proposed and applied for analysis of extensive unsolicited textual passenger feedback from diverse channels. Using advanced text mining and Natural Language Processing (NLP) techniques, including aspect-based sentiment analysis, textual comments are systematically transformed into quantifiable indicators reflecting key service dimensions. A robust Multi Criteria Decision Making (MCDM) model is integrated to objectively assess actual passenger perceptions and levels of satisfaction. The goals are to identify the service factors most critical to passenger satisfaction or dissatisfaction, uncover the fundamental drivers behind these sentiments, and generate actionable data-driven service improvement recommendations. Grounded in real-world passenger feedback, this framework provides a more accurate, objective, and scalable assessment method, empowers airlines to strategically enhance service quality, boost passenger satisfaction, and strengthen market competitiveness. The method is validated through correlation with operational metrics and expert evaluation.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:54:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681292</guid>
    </item>
    <item>
      <title>How to rate the vehicle cockpit seat usage experience? A computational method based on embodied cognition theory</title>
      <link>https://trid.trb.org/View/2708650</link>
      <description><![CDATA[Background: Vehicle cockpit seats are an important part of a car's interior. A superior vehicle cockpit seat usage experience plays a vital role in enhancing consumers’ driving experience. Objective: The objective of this study is to identify the factors influencing the vehicle cockpit seats usage experience, clarify the importance of each factor, and develop a quantitative evaluation model. Methods: Based on the theory of embodied cognition, this study develops a dynamic experience system for vehicle cockpit seats and divides the experience of vehicle cockpit seats into comfort experience, safety experience, functional experience and interaction experience. This study used semi-structured interviews to investigate the factors influencing the usage experience of vehicle cockpit seats among 50 experienced users. Finally, by comprehensively applying the hierarchical analysis method, the Delphi method, and D-number theory, we constructed an evaluation model of vehicle cockpit seats based on expert opinion and experience and analyzed the importance of each influencing factor. Results: The results showed that seat safety experience had the greatest impact on vehicle cockpit seat usage experience followed by the comfort experience. The seat structure, seat mechanical performance, preventive protection and physical buttons were found to have relatively strong effects. Conclusion: The study underscores the design and optimization of vehicle cockpit seats should prioritize safety and comfort, as these factors are critical to enhancing the overall experience for drivers and passengers. Car manufacturers and designers can use these insights to improve seat ergonomics, usability, and protection features, ultimately contributing to a more comfortable and secure driving environment.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2708650</guid>
    </item>
    <item>
      <title>Improved NSGA-II Algorithm-Based SDVRP Considering Simultaneously Pickup and Delivery of Multi-Commodity</title>
      <link>https://trid.trb.org/View/2617895</link>
      <description><![CDATA[In the process of goods delivery, it is often necessary to split and deliver (pick-up and delivery) multiple products from multiple orders. How to economically and reasonably formulate vehicle delivery routes is a challenge. Firstly, the order splitting and vehicle delivery path formulation was analyzed from the perspective of enterprises. Meanwhile, the impact of order splitting and delivery on customer satisfaction was analyzed from the perspective of consumers. Based on the above analysis, a multi-objective optimization model was established with the objectives of minimizing costs and maximizing customer satisfaction. Then, an improved NSGA-II algorithm was proposed to solve the model. In this algorithm, K-means and ant colony algorithm were used to obtain the optimal paths for two objectives, respectively. Then, the customer satisfaction problem caused by splitting was quantified using the information entropy TOPSIS method. Subsequently, the improved VNS algorithm was used to expand the solution sets of the two optimal paths for dual objective optimization. The experimental results show that the algorithm obtained Pareto front and achieved ideal experimental results.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617895</guid>
    </item>
    <item>
      <title>Usage intensity and passenger satisfaction in mixed formal-informal public transport systems: Evidence from Dar es Salaam</title>
      <link>https://trid.trb.org/View/2717092</link>
      <description><![CDATA[Research on public transport satisfaction often assumes that repeated exposure to service strain, such as delays, crowding, and irregular headways, reduces satisfaction over time through cumulative perceptual wear (“service fatigue”). However, this assumption remains largely untested in mixed formal-informal systems, where regulated services such as Bus Rapid Transit (BRT) operate alongside informal paratransit, including Daladala minibuses. Using survey data from 5449 passengers collected in 2024 and 2025, this study examines how usage intensity shapes satisfaction in Dar es Salaam across an operational BRT corridor and corridors under development where Daladala services remained dominant. During the study period, the network functioned as a mixed regime: Corridor 1 operated as a formal BRT trunk service under capacity constraints, while Corridors 3 and 4 were served primarily by informal Daladala operations. Satisfaction was assessed across four dimensions, service quality, availability, reliability, and ticketing, and aggregated into a composite index. Results reveal a clear gradient: occasional users report the lowest satisfaction, weekly users the highest, and daily users' intermediate levels. ANOVA and generalised ordinal logistic models confirm these differences after controlling for corridor type and socio-demographic factors. The findings challenge a simple service fatigue narrative, indicating that satisfaction is more strongly shaped by familiarity, exposure timing, and operating conditions, with occasional users more vulnerable to service variability. Accounting for usage intensity is therefore critical for interpreting satisfaction and improving performance in evolving mixed public transport systems.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717092</guid>
    </item>
    <item>
      <title>From fuel to electric: Mobility patterns and perceptions of commercial motorcycle operators in Nairobi, Kenya, evidence from a before-and-after field study (2023)</title>
      <link>https://trid.trb.org/View/2708335</link>
      <description><![CDATA[We assess how switching from internal combustion engine (ICE) to electric motorcycles could affect commercial motorcycle operators, drawing on insights from 9 operators in Nairobi, Kenya. Using a field-based before-and-after design, the study employed georeferenced operational data and structured surveys to examine changes in day-to-day riding performance, energy use and costs, and operator perceptions before and after the transition. Results indicate that typical operating patterns were broadly maintained after electrification, while energy use per kilometer and associated operating costs declined substantially. To interpret operator experiences beyond technical metrics, the paper applies an expectation-disconfirmation lens to compare pre-transition beliefs with post-transition satisfaction and continuance intention. Most operators reported continued willingness to use electric motorcycles despite transition challenges, but reported issues indicate that reliability risk can be decisive when service availability and income generation are disrupted. The analysis further disaggregates the transition issues encountered across EV charging configurations, contrasting plug-in and Battery-as-a-Service (BaaS) motorcycle models.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2708335</guid>
    </item>
    <item>
      <title>On the satisfaction function of random utility models: A theoretical review with new developments in weibit-based choice models</title>
      <link>https://trid.trb.org/View/2623431</link>
      <description><![CDATA[This study presents a theoretical review of the satisfaction function, the expected maximum utility or minimum disutility of travel choices, which plays an important role in the random utility theory and has wide applications in transportation system analyses. New developments in the satisfaction function of the recently developed weibit-based multiplicative random utility models are discussed and compared with the extensively studied logsum-type satisfaction function derived from logit-based models. A characterization of weibit-based choice probabilities is established based on the weibit-based satisfaction function, which is shown to be a multiplicative analogue of the well-known relationship between logit-based choice probabilities and logsum-type satisfaction functions. A comparison with the conventional logit-based satisfaction function is made, from which we show that the weibit-based satisfaction function is inherently more appropriate for reflecting the percentage variation in disutility. Furthermore, potential applications of the weibit-based satisfaction function are illustrated, including weibit-based choice probability generation, utility-based accessibility measurement, and accessibility-based vulnerability analysis.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:31:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623431</guid>
    </item>
    <item>
      <title>Contextualizing asymmetric drivers of older passengers’ satisfaction with rapid transit: A mixed-methods approach</title>
      <link>https://trid.trb.org/View/2712763</link>
      <description><![CDATA[Population aging is reshaping transit demand, yet transit service design often remains based on average-passenger perspectives that overlook older passengers’ needs. Moreover, there is limited evidence on the nonlinear effects of service attributes on transit satisfaction; existing research is predominantly quantitative, with little qualitative context. To address these gaps, this study investigates older passengers’ satisfaction with metro and BRT services in Chengdu (China) using a mixed-methods approach. Drawing on survey data from 928 older passengers, which yielded 1,068 mode-specific observations, we integrated gradient boosting decision tree models with impact-asymmetry analysis to identify key drivers of overall satisfaction and their asymmetric effects. We further interviewed 30 older passengers to contextualize the observed asymmetric patterns. The results show that most service attributes exert nonlinear and asymmetric effects on overall satisfaction, with key attributes varying across transit modes. For metro service, ease of transfer, information at stops, and transfer time require priority attention; for BRT, seat availability, waiting time, and transfer time are most critical. Overall, this study demonstrates the value of combining nonlinear modeling with qualitative evidence to better understand older passengers’ satisfaction and to inform targeted, age-friendly transit improvements.]]></description>
      <pubDate>Tue, 23 Jun 2026 13:51:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712763</guid>
    </item>
    <item>
      <title>Modeling and optimizing routing problems with customer satisfaction under stochastic travel times</title>
      <link>https://trid.trb.org/View/2599072</link>
      <description><![CDATA[Customer satisfaction is crucial in fostering loyalty and trust, serving as a fundamental pillar in contemporary business strategies. However, in routing problems, achieving high customer satisfaction often incurs significant operating costs. Delivery time, defined as the moment when services are provided to customers, emerges as a vital component influencing the satisfaction level. This paper introduces a novel delivery rule and formulates a model incorporating a chance constraint. The proposed model optimizes the total operational costs while maintaining high customer satisfaction levels in the vehicle routing problems with random travel times. Furthermore, this paper considers that the relationship between the delivery time and the satisfaction level is nonlinear. We employ the piece-wise linear techniques to approximate the nonlinear satisfaction function, thus improving realism and tractability. Moreover, we extend our model to include considerations for the vehicle waiting time and overtime, which enhances vehicle resource utilization. We use the sample average approximation method to address the proposed stochastic model. Subsequently, we develop a tailored solution procedure based on the Large Neighborhood Search (LNS) algorithm to solve the resulting large-scale mixed integer problem. Numerical experiments demonstrate the efficacy of our proposed model and the computational efficiency of our tailored LNS-based algorithm.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599072</guid>
    </item>
    <item>
      <title>Evaluating Passenger Satisfaction in Electronic Customs Declarations: An Expectation Disconfirmation Model Approach</title>
      <link>https://trid.trb.org/View/2676049</link>
      <description><![CDATA[Since July 2022, Indonesia’s Electronic Customs Declaration (ECD) system has replaced traditional paper-based forms for international arrivals. Although intended to enhance efficiency and user convenience, the system has generated considerable dissatisfaction, with 83.14% of recorded complaints citing technical or usability challenges. This study examines the determinants of passenger satisfaction with the ECD system through an integrated framework that combines the Expectation-Disconfirmation Model (EDM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the DeLone & McLean Information Systems Success Model. A cross-sectional survey of 207 Indonesian international passengers at Soekarno-Hatta International Airport was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), suitable for evaluating latent constructs and mediation effects in complex models. The results indicate that effort expectancy, drawn from UTAUT, significantly influences perceived system quality and Disconfirmation, both of which serve as critical mediators of user satisfaction. System Quality, based on usability, reliability, and interface design, exerts an indirect effect through Disconfirmation, as conceptualized in EDM and DeLone and McLean’s framework. Collectively, the variables explain 86.3% of the variance in satisfaction, with all key paths statistically significant (p < 0.001). These findings underscore the importance of expectation alignment, ease of use, and perceived system quality in shaping satisfaction with digital public services and provide practical insights for user-centered design and implementation of government technologies.]]></description>
      <pubDate>Wed, 17 Jun 2026 12:23:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2676049</guid>
    </item>
    <item>
      <title>Pattern-Guided Implicit Sentiment Analysis: Knowledge-Augmented Prompting with Aspect-Sentiment Joint Extraction for Automotive User Feedback</title>
      <link>https://trid.trb.org/View/2706200</link>
      <description><![CDATA[Implicit sentiment analysis of automotive user feedback is crucial for understanding user opinions. Automotive user feedback often express opinions in an indirect way and are accompanied by a dense array of industry terms. Therefore, without costly fine-tuning, both aspect identification and sentiment analysis are rather difficult. We propose a Pattern-Guided pipeline for implicit sentiment analysis to achieve the joint extraction of aspect and sentiment. This pipeline first performs Pattern Anchoring, mapping colloquial expressions and slang to the standardized vehicle component knowledge system. Then, using Knowledge-Augmented Prompting, these domain rules are injected into well-designed prompt templates. In this pipeline, the large language model (LLM) is applied to output JSON records suitable for comprehending, including aspects, sentiments, confidence levels, and brief reasons. To enhance stability, we employ an improved prompt and consistency-driven confidence fusion to generate multiple JSON records with confidence-building rules. The generated JSON records further enter the Attribution & Aggregation layer, which is used to cluster negative feedback, merge synonymous expressions, and generate traceable query summaries and priority signals. On a corpus containing 2,062 Chinese samples, the 7B open-source model qwen1.5-7b-chat achieved an accuracy rate of 94.7%, outperforming supervised fine-tuning at 93.1% and direct classification at 92.7%, and approaching qwen-plus at 95.7%. In a case study focusing on the Volkswagen Magotan, this method compressed 137 negative comments into traceable and sortable problem clusters. The code and data are available at https://github.com/ppg94/Implicit-Sentiment-Joint-Extraction-Automotive.]]></description>
      <pubDate>Tue, 16 Jun 2026 07:28:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706200</guid>
    </item>
    <item>
      <title>Smart and Innovative Solutions for Maximizing Public Transport Ridership and Passengers’ Satisfaction: Case Study of the City of Žilina</title>
      <link>https://trid.trb.org/View/2580107</link>
      <description><![CDATA[Public transport and shared mobility services are widely acknowledged as the backbone of sustainable urban transportation in terms of reduction of traffic congestion, air pollution and noise and increasing traffic safety. These services play pivotal roles in achieving the objectives of EU Cities Mission and the European Green Deal ambition of net zero greenhouse gas emission by 2050. Alongside this, the evolution of emerging mobility concepts is also transforming the future of mobility landscape, which impose a paradigm shift towards smarter carbon-neutral mobility services. Therefore, development of smart sustainable mobility solutions and ensuring improvement of customized mobility services for all citizens are key challenges for the cities of tomorrow. All of these require experimentation besides nudging people’s mobility behavior towards sustainable and climate-friendly choice of transport modes especially in Central and East European cities with high tendency for car ownership and use of private car for daily commuting. With a twofold objective of raising public transport ridership and passengers’ level of satisfaction with collective and public transport systems, this paper focuses on presenting various mobility-related solutions and measures and the implementation of the most promising ones through utilizing co-creation process for improvement of public transport service features and their smart integration with existing shared mobility services. The case study is provided for the city of Žilina as one of the twining cities in the Horizon Europe SPINE “Smart Public transport Initiatives for Climate-Neutral cities in Europe” Innovation Action project.]]></description>
      <pubDate>Fri, 29 May 2026 15:36:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580107</guid>
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