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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>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Effects of Vertical-Axial Dominant and Multi-Axial Vibration on Postural Stability</title>
      <link>https://trid.trb.org/View/2680884</link>
      <description><![CDATA[This repeated-measures laboratory study characterized the relative impacts of vertical-axial dominant and multi-axial Whole-Body Vibration (WBV) exposures on postural stability. Eleven healthy participants were exposed to field-measured vibration profiles collected from on-road commercial (vertical-dominant WBV) and off-road mining vehicles (multi-axial WBV) for four hours on two different days. Before and after the exposure, postural stability was evaluated while participants performed sit-to-stand tasks followed by static standing tasks. Overall, the study results indicate that off-road, multi-axial WBV may compromise postural stability more so than on-road, vertical-dominant WBV. These findings may suggest that off-road vehicle operators are at a greater risk of fall-related injuries. Therefore, there is a critical need to develop more effective vibration control measures among off-road vehicle operators.]]></description>
      <pubDate>Sat, 02 May 2026 15:47:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680884</guid>
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    <item>
      <title>Wind-Tunnel Study of the Traffic-Wake Impacts for Road-Vehicle Aerodynamics</title>
      <link>https://trid.trb.org/View/2692025</link>
      <description><![CDATA[When driving in traffic, the wakes of leading vehicles reduce the wind speed experienced by a following vehicle, lowering its drag relative to isolated driving. These wake effects can persist to large inter-vehicle distances, on the order of hundreds of meters, while lateral convection due to cross winds can influence vehicles in adjacent lanes. Wind tunnel testing was conducted at 30% scale for light- and heavy-duty-vehicle models in a large wind tunnel with a traffic-wake simulation system, expanding upon a previous study that examined only heavy vehicles. Three variants of the DrivAer model, four variants of the AeroSUV model, and three variants of a zero-emission heavy-duty-truck model were tested with a range of simulated wake conditions that varied the type, forward distance, and lane position of the wake-source vehicle(s), for a range of yaw angles up to 11°. Results show drag reductions of up to about 10% for the heavy-duty-truck model, and up to about 20% for the passenger-vehicle models. Surface-pressure measurements provide insights about the sources of drag reduction in wake effects, highlighting the balance between strongly-varying forward-surface pressure differences and mild base-pressure increases.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:39:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692025</guid>
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    <item>
      <title>MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC)</title>
      <link>https://trid.trb.org/View/2663009</link>
      <description><![CDATA[Commercial availability of vehicle automation has become mainstream. Most of today’s new vehicles can perform longitudinal car following autonomously via Adaptive Cruise Control (ACC). Field experiments demonstrate that today’s commercially available ACC vehicles provide similar headways and capacities as human-driven vehicles on freeways under steady-state and free-flow conditions. However, field tests also demonstrated that the design of today’s commercially available ACC vehicles can lead to further capacity reduction when operating in non-steady-state conditions where queues are present and speeds frequently fluctuate. These experiments generated MicroSimACC, a comprehensive set of field data that encompasses full speed range car following with interruptions from lane change manoeuvres. This will benefit the research community by providing benchmark data for developing models to be integrated into microscopic simulations for more prospective analyses and planning.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663009</guid>
    </item>
    <item>
      <title>Identifying Research Gaps Through Self-Driving Car Data Analysis</title>
      <link>https://trid.trb.org/View/2659129</link>
      <description><![CDATA[There are currently around thirty companies testing self-driving cars in San Francisco, CA, effectively creating a living laboratory. Of these companies, only Waymo is engaged in commercial operations, while Zoox conducts routine driverless testing operations in San Francisco. Despite these successes, federal investigations have been opened into both companies for safety concerns, and Cruise is attempting to reinstate its permit after a near-fatal pedestrian crash. An analysis of these three companies’ crash data from required reporting illustrates that many areas of self-driving need improvement. The most significant crash type for Waymo and Zoox are struck-from-behind events, while Cruise struggled most with unexpected actions by others. Computer vision systems are very brittle and likely play an outsized role in crashes. Self-driving cars also struggle to reason under uncertainty, and simulations are not effectively bridging the physical-to-real-world testing gap. This analysis underscores that research is lacking, especially for artificial intelligence involving computer vision and reasoning under uncertainty.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659129</guid>
    </item>
    <item>
      <title>Towards a Real-Time Automated Eco-Driving Algorithm Based on Human Cognition With Drivability Constraints</title>
      <link>https://trid.trb.org/View/2659126</link>
      <description><![CDATA[Driving automation offers a great potential for reducing environmental impact of road transports. Automated eco-driving, i.e. adapting vehicle behaviour in order to reduce energy consumption is a way of achieving it. However, for an eco-driving algorithm to be implemented in a commercial vehicle some constraints on drivability, safety and computing power are to be addressed. In this paper, we propose an acceleration maneuver model allowing to explicitly consider drivability constraints. The model is based on many empirical studies on Physiology and Ergonomics and has been verified using real driving recordings. Then we propose an Automated Eco-driving algorithm, allowing to minimize driving energy consumption while meeting drivability and safety constraints. The algorithm is able to adapt to changes in the driving scenario and its architecture is compatible with a real-time implementation.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659126</guid>
    </item>
    <item>
      <title>Assessing urban curbside parking for commercial vehicles: Simulation and policy insights</title>
      <link>https://trid.trb.org/View/2686816</link>
      <description><![CDATA[As e-commerce and urban deliveries spike, there is an increasing demand for curbside loading/unloading space. However, commercial vehicle drivers face numerous challenges while navigating dense urban road networks. These challenges can lead to conflicts with other road users, congestion, illegal parking, and parking time violations. While existing research often highlights pedestrian and bicyclist safety in urban environments, far less attention has been given to the experience and perspective of the truck drivers themselves, who are central to urban goods movement. Moreover, previous research on how commercial vehicle drivers make choices about when and where to park is limited. Available data often comes from field studies where only limited situations can be observed, with no experimental controls and a lack of known drivers’ characteristics. To address this gap, this study used the Oregon State University heavy vehicle driving simulator to examine the behavior of commercial vehicle drivers in various parking and delivery situations while accounting for key variables. A fully counterbalanced, partially randomized, factorial design was chosen to explore four independent variables: number of lanes (2-lane and 4-lane roads), with/without bike lane, available/unavailable passenger vehicle parking, and commercial vehicle loading zone (none, occupied, and unoccupied CVLZ). Driver speed, eye tracking, and parking behavior were used as performance measures. Data from 33 commercial driver’s license (CDL) holders yielded 792 observations across 24 scenarios. The findings from speed, eye movement, and parking behavior support more effective curb management strategies that improve delivery efficiency while recognizing the operational problems faced by truck drivers.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:18:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686816</guid>
    </item>
    <item>
      <title>Driving behavior recognition and scoring: A Bayesian approach to driving simulator data analytics</title>
      <link>https://trid.trb.org/View/2686764</link>
      <description><![CDATA[Safety is a key factor in operating commercial motor vehicles (CMVs). Advanced driving assistance systems are designed to assist CMV drivers enhance driving safety and reduce the risk of accidents. This study proposes a framework for driving style recognition and introduces statistical features that enable modeling the behavioral risk of drivers in real-time. These features include main aspects such as speed, throttle, and steering wheel as well as the those surrounding traffic conditions. A full-scale, high-fidelity driving simulator is used to generate the driving data. The driving records are clustered into different groups and a Bayesian classifier is trained the training portion of data to compute the probability of belonging to aggressive or safe classes. The framework is then extended, under normality assumption and using the distance from the mean, to one that provides driving score based on proximity to the boundary between safe and risky driving. Finally, the accuracy and effectiveness of the framework are evaluated by calculating the confusion matrices and AUCs. The experimental results demonstrate that the proposed framework for driving style recognition achieves accuracy rates of 88% to 91% in the test portion of the driving simulator data set.]]></description>
      <pubDate>Mon, 27 Apr 2026 17:01:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686764</guid>
    </item>
    <item>
      <title>Economic Analysis of Cargo Transport Life-Cycle in European Union</title>
      <link>https://trid.trb.org/View/2579699</link>
      <description><![CDATA[The use of trucks in the European Union is an essential component of the supply chain, ensuring the transportation of goods from manufacturers to consumers. The European Union has set ambitious targets for emission reductions, banning internal combustion engines, and transitioning to climate neutrality, including offering various programs to promote the use of more environmentally friendly transport solutions, such as electromobility and alternative fuel usage. Trucks often play a key role in the broader logistics chain during freight transportation. In this phase, it is crucial that cargo is transported while adhering to safety requirements and complying with all legal regulations and industry standards. Recent years have also highlighted the need for everyone to change their mindset and usage habits, aligning with sustainable and environmentally friendly practices. This includes addressing issues such as fuel efficiency (selecting and using high fuel efficiency vehicles and alternative fuel types for freight transportation), as well as planning emission reductions by implementing measures to reduce CO2 emissions and other harmful pollutants. The purpose of this article is to conduct an economic analysis of the use of trucks in supply routes.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579699</guid>
    </item>
    <item>
      <title>Design for Circularity in Commercial Vehicles: A Framework for Bridging Circular Economy Concepts and Design for X</title>
      <link>https://trid.trb.org/View/2683930</link>
      <description><![CDATA[The increased interest in the Circular Economy (CE) bears great potential for the commercial vehicle (CV) industry. However, the complex discipline of CE consists of various concepts, terms, and different approaches that hamper its application beyond individual, isolated projects. Also, existing CE tools are only applicable to a limited extent in a CV-specific environment. Therefore, this paper presents the development of a framework that combines the concepts of circular business models (CBMs), CE strategies, and Design for X (DfX) approaches in a CV industry context. Furthermore, the framework enables CV component experts to identify adequate CE Strategies and derive meaningful DfX recommendations by providing the user with a brief CE introduction, guiding the user through binary decision trees, and hinting at starting points of implementation. For evaluation, ten expert interviews with CV component experts of a German CV OEM were conducted. The gained industry insights emphasize that there is no universal CE solution for diverse CV components. However, certain DfX approaches obtain particularly promising results. Overall, the developed framework is perceived as an intuitive, quick, and insightful tool and is the first guide to provide adequate CE recommendations, useful for the CV industry and similar sectors.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683930</guid>
    </item>
    <item>
      <title>Simulation and optimisation of commercial vehicle brake disc based on thermal-structural coupling characteristic</title>
      <link>https://trid.trb.org/View/2691728</link>
      <description><![CDATA[Commercial vehicle brake discs carry enormous thermal energy and load, and their strength and stability have always been of great concern. During braking, the temperature and stress fields of the brake disc interact, embodying thermal-structural coupling characteristic. In this paper, the material properties of grey cast iron and compacted cast iron were tested from 20°C to 1000°C. Grey cast iron has advantages in specific heat capacity, thermal conductivity and coefficient of thermal expansion, while compacted cast iron has advantages in Young’s modulus and strength, at the same temperature. Secondly, an anti-coning disc and a standard disc, were compared in combination with two materials. It was found that the heat transfer coefficient of the anti-coning disc could exceed that of the standard disc for ideal inlet air conditions. Under emergency braking conditions, the maximum temperatures of the anti-coning discs made of grey cast iron and compacted cast iron were reduced by 70.9°C and 87.0°C, respectively, compared to the standard discs of the same material. The crack initiation life of the anti-coning and the standard discs made of grey cast iron were 5.47 times and 1.2 times higher than that of the compacted cast iron discs with the same structure. Finally, the optimisation of the vented channels showed that the use of rhombus and drop shaped ribs increased the crack initiation life by more than 11%, whereas circle shaped ribs had a negative effect.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:58:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691728</guid>
    </item>
    <item>
      <title>An exploration of active safety technologies for commercial vehicles: Research on on-road driving risk identification based on alarm and other multi-source data</title>
      <link>https://trid.trb.org/View/2692418</link>
      <description><![CDATA[In accident analysis and prevention, passive vehicle safety technologies ensure the lower limit of driving safety, while active safety technologies determine the upper limit. This study aims to provide suggestions for the active safety management of commercial vehicles by identifying high-risk on-road scenarios. Firstly, taking regular-route passenger buses as the research object, based on multi-source data fusion technology, this study integrates driving alarm data, vehicle trajectory data within 5 min before the alarm, driver video data within 10 s before the alarm, and driving record video data to extract key features and construct a driving risk identification variable set. Secondly, Pearson correlation coefficient and variance inflation factor (VIF) are used sequentially to conduct collinearity tests and eliminate redundant variables. Considering that the variables include both continuous and discrete heterogeneous data, the K-prototype hybrid clustering method is adopted, and the optimal number of clusters (K = 4) is finally determined. Thirdly, an integrated method of ’multi-source heterogeneous data fusion–hybrid variable clustering–Ordered Logit modeling–SHAP interpretability analysis’ is constructed. In an effort to explore active safety technologies, this study attempts to map the identified driving patterns to ordinal risk levels based on key vehicle kinematic parameters. Subsequently, the Ordered Logit model is applied to quantitatively analyze the marginal effects of significant variables. Finally, combined with the variable distribution characteristics of the clustering results and SHAP interpretability analysis, the core features and key incentives of the four risk levels are systematically characterized, and targeted active safety management suggestions are generated with the assistance of Large Language Models (LLMs). This study intends to provide certain insights for the research on vehicle active safety and offer references and suggestions for the dynamic monitoring and management of commercial vehicles.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:57:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692418</guid>
    </item>
    <item>
      <title>Short Review: Optimization Formulations for Enhancing Electric and Hybrid Electric Powertrain Performance</title>
      <link>https://trid.trb.org/View/2580013</link>
      <description><![CDATA[This paper presents a concise review of objective function formulations employed for optimizing the sizing of powertrain components in electric and hybrid electric powertrains, within the scope of the EU-funded Horizon Europe ESCALATE project. The objective is to analyze the techniques used to achieve improved performance and efficiency for powertrains. Efficient utilization of available energy sources, improved range, reduced GHG emissions, and overall system performance are crucial goals. Objective function formulations serve as essential tools for achieving these objectives. A broad spectrum of optimization techniques is employed in the objective function formulations for electric and hybrid electric vehicles (EVs/HEVs). These include multiple objective functions which simultaneously optimize conflicting/complementary goals, allowing for trade-offs and Pareto-optimal solutions. The review explores the key parameters considered during the optimization process, with a focus on the sizing of electric powertrain components. The goal is to identify the optimal combination of these variables to achieve an optimal powertrain design that maximizes energy efficiency while minimizing cost and environmental impact. Furthermore, the review delves into the challenges and prospects of objective function formulations in the context of electric and hybrid electric powertrains, including the potential to focus on sustainability of designs which has not previously been researched.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:55:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580013</guid>
    </item>
    <item>
      <title>Closed-loop characteristics of generalized optimal preview-follower incorporating coupled roll dynamics</title>
      <link>https://trid.trb.org/View/2686674</link>
      <description><![CDATA[This paper proposed a novel generalized preview-following methodology integrating coupled suspension roll characteristics for vehicles. The road geometry is described via a parametric time-dependent cubic spline, which represents road direction, curvature, and curvature rate. The ideal preview trajectory transfer function is derived, and the future lateral position of the vehicle is defined by a third-order polynomial. By minimizing the deviation between the preview path and the vehicle’s future lateral position within an objective function, the effective road preview input is determined. A distinctive correction function is introduced based on an equivalent handling dynamics model that incorporates coupled suspension roll characteristics. Experimental validation of the closed-loop system is carried out, through comparative data analysis with the ISO 3888-1 double lane change maneuver at 80 km/h. Furthermore, the impact of roll motion on trajectory tracking precision, quantified by dedicated total variance metrics, is systematically assessed across varying vehicle speeds. The minimum total variance values of trajectory tracking are 0.21 and 0.16 at the first and rear suspensions, respectively. The results demonstrate that the proposed method effectively optimizes suspension roll dynamics to enhance the lane-keeping performance in commercial vehicles, especially under conditions where suspension-roll effects are pronounced.]]></description>
      <pubDate>Mon, 20 Apr 2026 09:22:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686674</guid>
    </item>
    <item>
      <title>Breaking Down Commercial Motor Vehicle Crashes: What are the Main Causes?</title>
      <link>https://trid.trb.org/View/2693726</link>
      <description><![CDATA[This study examines commercial motor vehicle (CMV) crash severity in Idaho state from 2014–2023 by linking several state and federal databases to create an integrated analysis dataset. After filtering for completeness, 13,701 CMV-involved crashes were modeled using binary logistic regression to estimate the association between temporal, roadway, environmental, workzone, vehicle, and driver factors and the odds of high-severity outcomes. Key findings include elevated fatal-crash odds in specific weather, during time of day, in certain roadway conditions, and in particular lighting conditions. The study translates these results into actionable mitigation strategies for Idaho, including infrastructure changes, technologies, public campaigns, and educational efforts. A dedicated section outlines a continuous data quality framework to support ongoing evaluation.]]></description>
      <pubDate>Fri, 17 Apr 2026 08:55:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2693726</guid>
    </item>
    <item>
      <title>Achieving 70% Urban Fuel Consumption Reduction: An Opposed-Piston Engine-Based Mild-Hybrid Powertrain Architecture for Light Commercial Vehicles (JLA-2/JLA-T)</title>
      <link>https://trid.trb.org/View/2692254</link>
      <description><![CDATA[This paper proposes a novel powertrain architecture for the urban Light Commercial Vehicle (LCV) segment, leveraging the compact JLA-2 opposed-piston (OP) engine paired with the reconfigurable JLA-T mild-hybrid architecture. Within SAE literature, OP engines are consistently associated with simplicity. As highlighted by Tom Ryan III (2008 SAE President) in the foreword of Opposed Piston Engines: Evolution, Use, and Future Applications, this architecture is characterized by its manufacturing simplicity” and described as a “relatively simple, robust, and cost effective” power unit solution. The present work builds on this established view. The JLA-2 engine solves traditional packaging constraints by reducing the block width by 30% for horizontal installation and is volumetrically self-sufficient, eliminating external compressors. Although the gear train required for crank synchronization introduces design challenges, explicitly accounted for in our model, the elimination of the cylinder head and valve train reduces component count. The study utilizes a comprehensive computational methodology—incorporating 0D/1D thermodynamics, 3D CFD, and FEA—to evaluate the system against a standard Ford Escape baseline. The JLA-T module mechanically blends torque using a planetary gear-set and a low-voltage 48V electric assist, capturing electrification benefits without the high costs and safety complexities of high-voltage systems. Simulation results suggest significant performance improvements, notably achieving a sub-9-second 0-100 km/h acceleration and enabling Zero Emission Vehicle (ZEV) compliance in restricted zones. Most significantly, the analysis indicates that this platform delivers up to a 70% reduction in urban fuel consumption when operated as a PHEV, driven by the system’s modularity and optimized energy recovery. This paper presents the system architecture, control logic, and performance comparisons, demonstrating a feasible technical pathway for decarbonizing urban transport fleets. (Note: “JLA” serves as the proprietary designation for the engine and electromechanical hybrid system series proposed by the authors).]]></description>
      <pubDate>Tue, 14 Apr 2026 15:11:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692254</guid>
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