<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <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>
    </image>
    <item>
      <title>Resilient RoRo fleet scheduling for mixed EV and ICEV transport demand: An optimization framework for EV dedicated service strategy</title>
      <link>https://trid.trb.org/View/2663819</link>
      <description><![CDATA[The surge in electric vehicles (EVs) is causing a structural disruption to high-density, short-sea Roll-on/Roll-off (RoRo) transportation, driven by stricter safety regulations and unique transport protocols. Operators like those in China’s Qiongzhou Strait have implemented an ‘EV Dedicated Service’ (EVDS) strategy. This strategy involves a complex coordination problem between dedicated EV-carrying vessels and separate vessels for transporting drivers. However, this emerging scheduling paradigm has been insufficiently studied. This paper proposes a multi-objective mixed integer programming model for the RoRo fleet scheduling with a novel methodological approach to formulate EVDS mechanism. Additionally, we develop an Adaptive Large Neighborhood Search − based heuristic algorithm, featuring novel problem-specific neighborhood structures. Realistic instances validated the algorithm’s performance against benchmark methods. The results also revealed the balance between economic efficiency and service levels across three different demand scenarios (Low-Season, Normal-Day, and Peak-Season). Furthermore, the analysis reveals the strategic value of flexible deployment for EV-certified vessels. We also introduce a method to quantify operational resilience by analyzing the impact of elastic capacity planning on alleviating port congestion. The findings provide a robust decision-support framework for RoRo operators and policymakers navigating the surge in EV transport demand.]]></description>
      <pubDate>Thu, 19 Mar 2026 08:57:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663819</guid>
    </item>
    <item>
      <title>Does one size fit all? Examining heterogeneous pathways to electric vehicle adoption readiness</title>
      <link>https://trid.trb.org/View/2667080</link>
      <description><![CDATA[The readiness of automotive dealerships plays a pivotal role in advancing electric vehicle (EV) adoption, particularly in emerging economies such as Indonesia. This study explores internal organizational determinants that influence the preparedness of Indonesian automotive dealerships to adopt EVs, taking into account variations in brand origins and organizational structures. Drawing on data from a cross-sectional survey of 1,136 dealership branches and 170 head offices, the research applies Structural Equation Modeling (SEM) to uncover that transformational leadership is a key driver of adoption readiness in traditional dealerships where structured support systems and managerial autonomy coexist. In contrast, dealerships associated with Korean brands and those emphasizing hybrid vehicles are more dependent on resource coordination and knowledge absorption due to their limited strategic flexibility. The study introduces the HETER EV Framework to demonstrate how different combinations of organizational support, leadership, resource utilization, and knowledge management create distinct pathways to readiness. The results challenge the notion of universal strategies and underscore the necessity of tailoring interventions to specific brand structures and strategic contexts. By focusing on the Indonesian dealership landscape, the study adds to the Resource-Based View and Dynamic Capabilities Theory, while advocating for more localized and brand-specific approaches to support the EV transition. Further research is encouraged to examine dealerships in other countries to assess the global applicability of these insights.]]></description>
      <pubDate>Wed, 18 Mar 2026 09:00:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2667080</guid>
    </item>
    <item>
      <title>Mode choice in metropolitan areas: Impacts of automation and electrification</title>
      <link>https://trid.trb.org/View/2634084</link>
      <description><![CDATA[Urban mobility patterns might radically change due to electrification and automation. This paper investigates mode choice in Sweden when introducing electric and automated private cars, electric and autonomous buses in regular service, and private electric bikes. Mode choice is investigated by using a multinomial logit model of short-distance trips in metropolitan areas calibrated to the Swedish National Travel Survey. The model considers relationships between trip length, travel speed and access-egress times for all modes and is used for analysing future scenarios up to 2050. The new technologies affect driving costs, travel time costs, travel speed and access times, which in turn impact mode choice. The results show that when autonomous technology is used within a transport system similar to the current one (e.g., mainly private car ownership and a required license to drive), the effect on modal shares of trips and passenger-kilometres is limited. For example, the distance modal share of car drivers increases from 55.3 % to 61.3 % in 2050. The limited impact can partly be explained by the fact that the impact of new technology on generalised travel cost is limited, and partly by the fact that the multinomial logit model yields mode-specific constants, which causes the model to be relatively insensitive to changes in technology. Finally, the turn-over rate in a car fleet is typically lower than for both buses and bikes. Overall, it seems unlikely that mobility patterns with radically change with electric and autonomous cars without additional changes to ownership structures and car accessibility.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2634084</guid>
    </item>
    <item>
      <title>The method to verify the impact of EV range variation on its travel time</title>
      <link>https://trid.trb.org/View/2621139</link>
      <description><![CDATA[The development of electromobility is associated with a number of challenges related to route planning, effective use of charging stations and the variability of electric vehicle range. This article analyzes existing solutions in the field of route optimization of electric vehicles and identifies research gaps, such as insufficient consideration of various types of charging stations or the impact of range variability on travel time. On this basis, a simplified optimization model was developed, using a genetic algorithm implemented in the MATLAB environment. The model allows the selection of the shortest connection time between two points, taking into account the location of charging stations, their type (fast or slow) and the variability of range resulting from external conditions. The research analyzed the impact of range limitations on the total travel time, as well as on the number and distribution of charging stops. The results show a clear relationship between the decrease in range and the need to use chargers more often, which significantly extends the travel time. The proposed approach can be a starting point for more advanced analyses of real routes and the development of systems supporting travel planning for electric vehicles.]]></description>
      <pubDate>Fri, 09 Jan 2026 14:44:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2621139</guid>
    </item>
    <item>
      <title>The use of the Preference Vector Method – Vector Space of Increments (PVM–VSI) in supporting the consumer decision related to the purchase of an electric car from the mini–segment</title>
      <link>https://trid.trb.org/View/2630187</link>
      <description><![CDATA[The article presents the potential application of the PVM–VSI (Preference Vector Method – Vector Space of Increments) approach to support decision–makers in solving decision–making problems involving the selection of one alternative from among several options. The decision alternatives are evaluated based on both quantitative and qualitative criteria. Consequently, it is essential to possess a body of knowledge regarding the considered alternatives. Equally important is that the evaluation of the alternatives in the analysed decision problem remains independent of the decision–maker’s personal preferences and opinions, thereby ensuring a relatively objective assessment. In this study, the PVM–VSI [4,14] method was applied to support the decision–making process related to the selection of a mini–segment electric vehicle by developing a ranking of such vehicles available on the Polish automotive market. The objective of the resulting ranking is to identify which vehicle best satisfies the utility requirements defined by the decision–maker, while also aligning with their preferences regarding both exterior and interior design.This article pursues two primary objectives. The first is to examine the current offering within the mini segment of the rapidly evolving electric vehicle market. The second objective is to identify the electric vehicle within this segment that best meets the utility requirements and aesthetic preferences defined by a hypothetical consumer.The first objective was achieved through an analysis of the electric vehicle market, which revealed a limited availability of models in the mini electric car segment. Possible reasons for this situation are discussed in the conclusions. The second objective was addressed using the PVM-VSI method to investigate consumer preferences and to establish a ranking of selected alternatives within the aforementioned segment. The analysis indicated that the Fiat 500 most effectively fulfilled the consumer’s expectations with respect to the evaluation criteria.]]></description>
      <pubDate>Fri, 09 Jan 2026 14:44:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630187</guid>
    </item>
    <item>
      <title>An assessment of consumer preferences for electric cars-case Delhi, India</title>
      <link>https://trid.trb.org/View/2626035</link>
      <description><![CDATA[Studies on consumer preferences for electric cars (E-cars) and heterogeneity in individuals' preferences for E-car attributes are relatively scarce. This paper contributes to addressing the research gap through an unlabeled stated preference study conducted in Delhi. The stated choice experiment incorporates rarely considered features such as car loan interest rates and purchase subsidies, and the analysis identifies the effects of vehicle characteristics, socio-demographics and psychological attitudes. A latent class multinomial logit (LC-MNL) model is estimated in the paper, with class allocation identified based on individuals' income, motorized two-wheeler ownership, the number of cars owned in the past, and attitudinal factors. The model results identified two distinct classes of consumers – Rational consumers and Impulsive consumers - who are distinct in terms of household income, vehicle ownership, and attitude towards battery information. Rational consumers are found to be more sensitive to purchase price than impulsive consumers. The broader implications of study findings suggest that manufacturers' interventions to improve the range of EVs can be a strategy applicable to the heterogenous consumer base in Delhi. However, the monetary-based schemes must be based on an understanding of the consumer's background.]]></description>
      <pubDate>Wed, 17 Dec 2025 08:49:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2626035</guid>
    </item>
    <item>
      <title>Enhanced Cooling Strategy of YASA Axial Flux Permanent Magnet Motor for Electric Automobile Application</title>
      <link>https://trid.trb.org/View/2604018</link>
      <description><![CDATA[Addressing the thermal management challenges associated with the stator and rotor system of yokeless and segmented armature (YASA) motors, this article proposes an enhanced cooling strategy for the stator and rotor. Taking a dual-rotor single-stator YASA motor as the research subject, the volume of fluid (VOF) model is employed to evaluate the cooling performance of the existing advanced oil cooling technique. Subsequently, the stator bracket is perforated to enable cooling oil to flow into the air gap area for direct heat exchange with the stator and rotor system. By investigating the impact of the number of holes on both the motor’s cooling performance and oil friction loss, the optimal hole configuration is determined to be a direct cooling solution with hole of  $1\times 1.5$  mm. Compared with the existing cooling scheme, the maximum temperatures of windings, stators, permanent magnets, and rotors under rated conditions are reduced by 29.14%, 28.53%, 51.67%, and 50.21%, respectively. Through the comparison of temperature rise experiments, the accuracy of thermal simulation modeling and the efficiency of the cooling system are further verified, which provides a new method for the design of efficient cooling system of YASA motor.]]></description>
      <pubDate>Wed, 10 Dec 2025 16:01:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604018</guid>
    </item>
    <item>
      <title>Beyond the Buzz: Electric cars and the German health public budget</title>
      <link>https://trid.trb.org/View/2554319</link>
      <description><![CDATA[This study explores the impact of electric cars on public health expenditures by considering several scenarios and using the Generalized Structural Equation Model (GSEM) estimator. The analysis utilizes a dataset covering 16 Federal States of Germany from 2008 to 2021.The dataset includes data on electric car adoption, public health expenditures, road infrastructure, and socio-economic and demographic indicators. The main findings suggest that the relationship between electric cars and public health expenditures in Germany is complex, shaped by various socio-economic factors. The positive impact of electric cars on public health expenditures is mainly driven by traffic collisions from state roads that require more hospital units, including additional beds. In contrast, traffic collisions from county roads show a stronger negative correlation with hospital bed demand, indicating less pressure on the public health budget due to a reduced need for new hospital units. In summary, the electric cars may increase traffic collisions in Germany, particularly on state and county roads. In this context, traffic collisions on state roads appear to result in greater demand for new hospitals with additional beds and potentially rising healthcare costs, especially considering the severity of accidents on these roads. However, traffic collisions from county roads show a negative correlation with hospital beds, being higher in amplitude than those on state roads. This indicates that local traffic characteristics, the improved safety of electric cars, and efficiencies in healthcare (e.g., outpatient care) contribute to a reduction in the need for hospitalization and help mitigate the financial impact. Additionally, healthcare spending is influenced by factors such as unemployment, GDP growth, an ageing population, and the number of doctors. However, the healthcare system's capacity to efficiently manage hospital resources and transition to outpatient care could mitigate the financial strain caused by traffic incidents related to electric cars.]]></description>
      <pubDate>Thu, 05 Jun 2025 14:01:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2554319</guid>
    </item>
    <item>
      <title>Proud to go electric: Overcoming perceived functional barriers to EV adoption through congruent messaging frames</title>
      <link>https://trid.trb.org/View/2558515</link>
      <description><![CDATA[Growing reports indicate a slowdown in electric vehicle (EV) sales, particularly among consumers yet to embrace this sustainable transportation option. A key functional barrier to adopting EVs relates to infrastructure, maintenance, and range anxiety issues. This study explores how marketing can address this barrier by framing messages to evoke anticipated pride in owning an EV, thus reducing range anxiety, charging inconvenience, and ultimately increasing purchase intentions. Grounded in construal level theory and affect-as-information theory, the study employs an online experiment with 223 Australian consumers yet to purchase an EV. Results reveal that concrete, self-targeted messages yield greater purchase intentions, driven by increased anticipated pride in ownership and reduced perceived functional barriers. These findings underscore the importance of framing in marketing messaging to encourage EV adoption and offer practical implications for EV brands and policymakers.]]></description>
      <pubDate>Thu, 05 Jun 2025 14:01:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2558515</guid>
    </item>
    <item>
      <title>A continuous approximation model for the optimal design of mixed free-floating and station-based car-sharing systems</title>
      <link>https://trid.trb.org/View/2411202</link>
      <description><![CDATA[One-way car-sharing systems have become a popular urban transportation mode in many cities worldwide. First pilot implementations were originally station-based, so that trips needed to be station-to-station. This configuration created implementation difficulties in many cities and higher infrastructure costs for operating agencies. The appearance of free-floating on-street systems eased these limitations and implied an important growth of car-sharing implementations. In spite of these, free-floating systems are not free of planning and operative difficulties, which if not addressed carefully, might imply the economical unsustainability of the system. The idea of mixed systems, where a free-floating system and a station-based system complement each other, is new. The objective is to exploit the potentialities of both designs, while limiting their respective drawbacks. This paper presents a parsimonious model from which to derive the optimal strategical design variables for mixed car-sharing systems (i.e. the vehicle fleet size, the number of stations and the required intensity of rebalancing operations). This requires an integrated view of the system, allowing the optimization of the trade-off between the costs incurred by the operating agency and the level of service offered to users. The approach is based on the modelling technique of continuous approximations, which requires strong simplifications but allows obtaining very clear trade-offs and insights. The model has been applied to a case study taking the parameters from the city of Barcelona. Results prove the profitability of mixed car-sharing systems, which in particular contexts, is higher than that of pure free-floating or pure station-based systems on their own. Furthermore, if electrical cars are used, results show that battery recharging will not imply an active restriction to the system configuration. In conclusion, the proposed modeling approach represents a tool for the strategic design of car-sharing systems in the planning phase and provides guidelines for their adequate development, contributing to a more sustainable urban mobility.]]></description>
      <pubDate>Wed, 18 Sep 2024 09:41:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2411202</guid>
    </item>
    <item>
      <title>Consumer Monitor 2023 European Alternative Fuels Observatory EU Aggregated Report</title>
      <link>https://trid.trb.org/View/2399819</link>
      <description><![CDATA[The European Green Deal aims for a 90% reduction of greenhouse gas emissions for transport by 2050. Different policies are in place to achieve this goal, including standards on CO₂ vehicle emissions, public procurement rules, or the recently adopted Alternative Fuels Infrastructure Regulation (AFIR). Nevertheless, in 2019, the transport sector was responsible for around one-quarter of the EU’s total CO₂ emissions, 60.6% of which were emitted by passenger cars. The passenger car is still the main transport mode and has continued to increase its share since the year 2000. Replacing existing fleets with zero-emission vehicles is one of the key measures identified for this purpose. Important efforts have been made to promote electric cars, and therefore, identifying the main hurdles and needs of (potential) battery electric drivers can support the design and implementation of tailored strategies, policies and solutions to stimulate the demand for this type of vehicle. For more than a decade, three main barriers have been identified regarding the mass up-take of passenger battery electric vehicles (BEVs): purchase price, driving range and availability of recharging infrastructure. There have been significant advances: battery costs have dropped by 90%, vehicle range has increased from 100-150 km up to 400+ km, and the recharging infrastructure network is expanding. Nevertheless, BEVs represent only 1.68% of the total passenger cars fleet in the EU, and the recharging infrastructure coverage is still limited in some countries and urban areas. This report highlights the main findings of the 2023 EAFO Consumer Monitor survey and presents the results for Belgium.]]></description>
      <pubDate>Wed, 31 Jul 2024 10:48:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2399819</guid>
    </item>
    <item>
      <title>A Machine Approach for Field Weakening of Permanent-Magnet Motors</title>
      <link>https://trid.trb.org/View/1787569</link>
      <description><![CDATA[The commonly known technology of field weakening for permanent-magnet (PM) motors is achieved by controlling the direct-axis current component through an inverter. Without using mechanical variation of the air gap, a new machine approach for field weakening of PM machines by direct control of air-gap fluxes is introduced. The demagnetization situation due to field weakening is not an issue with this new method. In fact, the PMs are strengthened at field weakening. The field-weakening ratio can reach 10:1 or higher. This technology is particularly useful for the PM generators and electric vehicle drives.]]></description>
      <pubDate>Mon, 15 Jul 2024 16:09:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1787569</guid>
    </item>
    <item>
      <title>Kinematic simulations and design of a steering upright for a single seater electric car</title>
      <link>https://trid.trb.org/View/2373893</link>
      <description><![CDATA[This work discusses a systematic approach for design and analysis of a steering upright based on suspension hardpoint analysis. The steps followed would ensure anticipated performance of a vehicle in terms of ride comfort and handling. The suspension hardpoints were determined using LOTUS™ Shark suspension analysis software based on kinematic simulations. The geometric model of the upright was then created in accordance with the hardpoints obtained. Static structural analysis was performed on the preliminary upright design and design modifications were done to reduce the weight. Further, a suitable material was selected for the upright based on a comparison of values of stress, deformation, safety factor and mass for different upright materials. In addition, fatigue analysis was performed to compute the life of the upright. The manufactured uprights were assembled with other suspension assembly components and were tested under different on road conditions to observe for any failure.]]></description>
      <pubDate>Mon, 15 Jul 2024 09:09:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2373893</guid>
    </item>
    <item>
      <title>Optimizing routing and scheduling of shared autonomous electric taxis considering capacity constrained parking facilities</title>
      <link>https://trid.trb.org/View/2392333</link>
      <description><![CDATA[This paper focuses on routing and scheduling of autonomous electric vehicles to provide reservation-based shared ride services, while a set of parking facilities with limited capacity are used for vehicle intermittent charging. A mixed-integer linear program model is formulated in the form of a vehicle routing problem with satellite facilities (VRPSF), subject to a series of additional time and capacity-related constraints. The objective of the model is to minimize the total operating costs of the system, including those related to vehicle miles traveled and the deployed vehicle fleet size. The number of vehicles inside each parking facility is tracked so as to ensure that the capacity is never exceeded throughout the service horizon. A customized solution method based on an adaptive large neighborhood search algorithm with an explicit treatment of parking facility choices is developed. A series of numerical experiments, consisting of both hypothetical examples and a real-world case study in Hangzhou, China, have been conducted to evaluate the effectiveness and applicability of the proposed model and algorithm. The results demonstrate that ride-sharing services and parking facilities have the potential to significantly reduce the total vehicle energy consumption and operating costs for a shared autonomous electric taxi (SAET) operator in practical scenarios.]]></description>
      <pubDate>Thu, 11 Jul 2024 13:53:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2392333</guid>
    </item>
    <item>
      <title>A New Class of Devices: Magnetic Gear Differentials for Vehicle Drivetrains</title>
      <link>https://trid.trb.org/View/2201125</link>
      <description><![CDATA[Mechanical differentials are essential drivetrain components of automobiles and other wheeled vehicles, allowing the outer drive wheel to rotate faster than the inner drive wheel during turns. This article presents a comprehensive description of a novel and recently patented alternative based on magnetic gears (MGs), which achieves the same functionality while providing distinctive advantages such as reduced maintenance, absence of lubrication, and high efficiency. This article describes the operation principle of such MG differential and two alternative constructive options, provides a dynamic model, which allows the study of the device in driving conditions, presents a description of a prototype, and validates finite-element (FE) simulations with experimental results.]]></description>
      <pubDate>Fri, 28 Jun 2024 14:01:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2201125</guid>
    </item>
  </channel>
</rss>