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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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      <title>Factors Influencing Drivers’ Tolerance for Large Vehicle Proportions</title>
      <link>https://trid.trb.org/View/2666439</link>
      <description><![CDATA[To enhance road traffic safety, this study develops a classification model to assess drivers’ tolerance of large vehicle proportions under varying road conditions. It explores how personal and socioeconomic factors influence this tolerance. Six road scenarios were designed with differences in large vehicle proportion, driving time, vehicle types and road types. Behavioural and willingness surveys collected drivers’ demographics and choices. K-means clustering segmented drivers into “low”, “medium” and “high” tolerance groups, accounting for 6.77%, 51.13% and 42.10%, respectively. Based on clustering results, an ordered logistic regression model further analysed factors influencing large vehicle tolerance. Tolerance correlated positively with household vehicle usage, annual household income, driving duration and weekly driving frequency, and negatively with urban GDP, vehicle ownership and peak congestion index, with age showing no significant effect. Additionally, linear trends were observed for urban peak congestion index, urban vehicle ownership, age and driving duration. In contrast, urban GDP, weekly driving frequency, annual household income and household vehicle usage showed curvilinear effects with gradually diminishing rates of change.]]></description>
      <pubDate>Tue, 26 May 2026 09:41:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666439</guid>
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    <item>
      <title>Assessment of the stopping for right-turning large vehicles policy in Nanjing: Effectiveness and determinants</title>
      <link>https://trid.trb.org/View/2604565</link>
      <description><![CDATA[This study evaluates the effectiveness of Stopping for Right-Turning Large Vehicles Policy in Nanjing, designed to mitigate accidents attributed to blind spots and delayed braking of large trucks at intersections. Using high-resolution conflict data from four signalized intersections in Jiangning District, collected via unmanned aerial vehicles (UAVs) and roadside video, the research employs K-means clustering for conflict severity classification and binomial Logit regression to identify critical determinants. Results reveal the policy exhibited limited statistical significance in reducing severe conflicts (p > 0.05). Regression analysis quantified four critical determinants: absence of motorized/non-motorized segregation (OR=1.82, + 81.6% severity odds), elevated stop-line speeds (OR=1.32, + 31.9%), failure to yield (OR=2.45, + 145%), and crossing the street within the zebra crossing (OR=0.19, -81.0%). The analysis demonstrates that infrastructural deficiencies and behavioral non-compliance outweigh the policy's standalone impact. Based on these findings, the study proposes a holistic optimization framework integrating physical separation measures, enhanced signage, dynamic traffic signal adjustments, and data-driven enforcement strategies. Methodologically, this study innovatively combines unsupervised learning for conflict categorization, providing a scalable framework for evaluating urban traffic policies. This research underscores the necessity of multi-dimensional interventions-spanning infrastructure, enforcement, and public education-to achieve sustainable improvements in intersection safety. The findings offer actionable insights for policymakers to refine regulatory measures and enhance road safety in rapidly urbanizing environments.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604565</guid>
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      <title>Modelling of integrated bio-dynamic human model with full car using bond graph for IRC:99-1988 bump</title>
      <link>https://trid.trb.org/View/2566940</link>
      <description><![CDATA[One of the most intriguing topics for researchers in the area of vehicle dynamics is the use of vehicle vibration to analyse dynamic behaviour. The primary goal of this research is to examine the dynamic behaviour of a road vehicle under various road conditions. In this study, an integrated computer model is developed through the bond graph methodology to analyse the dynamic behaviour of a large road vehicle. The initial stage is to create the 3D models of each vehicle base, suspension unit, tyre, seat, and joint as bond graph elements with power ports for physical connections. This work demonstrates the dynamic behaviour of the 4 DOF lumped human biomechanical model coupled with an 11 DOF full-car vehicle model using the bond graph simulation technique. Ride comfort conditions as per ISO 2631:1997 standards are used to validate the dynamic response of the bio-dynamic human coupled with a full car. Various other dynamic responses in the time domain have been captured in simulation for the conditions where the vehicle passes over different bumps of the same height and width of 1 m, 2 m and 3.7 m with a 40 km/h speed. Additionally, RMS responses have been studied for different vehicle velocities. The results presented in the paper show the fascinating behaviour of full-car vehicles.]]></description>
      <pubDate>Wed, 17 Sep 2025 10:56:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2566940</guid>
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    <item>
      <title>Optimizing the University of Wisconsin's Parallel Hybrid-Electric Aluminum Intensive Vehicle</title>
      <link>https://trid.trb.org/View/1787266</link>
      <description><![CDATA[The University of Wisconsin - Madison FutureCar Team has designed and built a lightweight, charge sustaining, parallel hybrid-electric vehicle for entry into the 1999 FutureCar Challenge. The base vehicle is a 1994 Mercury Sable Aluminum Intensive Vehicle (AIV), nicknamed the “Aluminum Cow,” weighing 1275 kg. The vehicle utilizes a high efficiency, Ford 1.8 liter, turbo-charged, direct-injection compression ignition engine. The goal is to achieve a combined FTP cycle fuel economy of 23.9 km/L (56 mpg) with California ULEV emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a full-size car. Strategies to reduce the overall vehicle weight are discussed in detail. Dynamometer and experimental testing is used to verify performance gains.]]></description>
      <pubDate>Mon, 02 Dec 2024 12:49:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1787266</guid>
    </item>
    <item>
      <title>Analyzing injury severity of rear-end crashes involving large trucks using a mixed logit model: A case study in North Carolina</title>
      <link>https://trid.trb.org/View/1948246</link>
      <description><![CDATA[As one of the most frequently occurring crashes, rear-end crashes often result in injuries and property damage, especially when large trucks are involved. To investigate the contributing factors and the unobserved heterogeneity in such factors, a mixed logit model is developed to analyze rear-end crashes involving large trucks. A dataset containing 7,976 rear-end crashes involving large trucks is collected from Highway Safety Information System (HSIS) in North Carolina between 2005 and 2013. Driver, roadway, and environmental related characteristics are considered in the analysis. Speed limit over 50 mph is found to be better modeled as a random-parameter at specific injury severity levels. Results also indicate that driving under the influence of alcohol or drugs, rural roadways, dark light condition, grade roadway configuration, speed limit over 50 mph will significantly increase the injury severity of large truck involved rear-end crashes. Roadway with traffic control will significantly decrease the injury severity of such crashes. The findings in this study can greatly help traffic agencies and truck companies develop better large truck-involved rear-end crash prevention strategies.]]></description>
      <pubDate>Tue, 21 Jun 2022 10:31:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1948246</guid>
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    <item>
      <title>Pedestrian deaths and large vehicles</title>
      <link>https://trid.trb.org/View/1869720</link>
      <description><![CDATA[Traffic fatalities in the US have been rising among pedestrians even as they fall among motorists. Contemporaneously, the US has undergone a significant shift in consumer preferences for motor vehicles, with larger Sport Utility Vehicles comprising an increased market share. Larger vehicles may pose a risk to pedestrians, increasing the severity of collisions. The author uses data covering all fatal vehicle collisions in the US and exploit heterogeneity in changing vehicle fleets across metros for identification. Between 2000 and 2019, the author estimates that replacing the growth in Sport Utility Vehicles with cars would have averted 1,100 pedestrian deaths. The author finds no evidence that the shift towards larger vehicles improved aggregate motorist safety.]]></description>
      <pubDate>Thu, 07 Oct 2021 16:59:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/1869720</guid>
    </item>
    <item>
      <title>The Rising Tide of Transport Gluttony</title>
      <link>https://trid.trb.org/View/1770861</link>
      <description><![CDATA[Are some people over-consuming transport, creating negative impacts and outweighing the benefits of active transport interventions? There is growing consensus about the need to increase the proportion of people walking, cycling and using public transport. This is for a range of objectives including climate breakdown, physical and mental health, air quality, congestion, economic vitality etc. However, the other side of the coin – the need to restrain cars – although much talked about is not sufficiently implemented. The paper will look specifically at transport gluttony: the over-consumption of transport, with adverse consequences for other transport users. Examples include: • using cars for very short trips – a third of car journeys in London are for trips under 2km, contributing to poor air quality, congestion and unpleasant conditions for active modes; • the rising use of large vehicles in urban areas (one in three cars sold in Europe is an SUV) – SUVs are twice as likely to kill pedestrians by inflicting greater upper body and head injuries; and • driver behaviours such as excessive speed, driving through red lights, parking on the footway and engine idling – these have a negative impact on people walking and cycling and can have a particularly severe impact on places such as schools. With the Coronavirus and lockdown, people have experienced a very different environment for walking and cycling this year. The paper will focus on ways in which this rising tide of transport gluttony can be turned. It will look at the policies and measures that can be taken to reduce such over-consumption to benefit active transport modes and to make towns and cities better places for everyone to live, drawing on examples where this is happening. It will also look at the political benefits that can come with such an approach to transport.]]></description>
      <pubDate>Fri, 26 Mar 2021 17:47:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1770861</guid>
    </item>
    <item>
      <title>Influence of major stream composition on critical gap at two-way stop-controlled intersections – a case study</title>
      <link>https://trid.trb.org/View/1678353</link>
      <description><![CDATA[Gap acceptance method used in the analysis of two-way stop-controlled intersections is based on the assumption that major street traffic is uninterrupted. However, the present study found a clear difference among the traffic characteristics of the major street at the intersection and upstream of it. The distributions of inter-arrival times and speeds of major street vehicles are significantly modified as they approach the intersection. Data collected from five intersections in India were used to estimate the critical gaps for motorized two-wheelers and cars executing two non-priority movements (right turn from major and minor streets). Critical gap, estimated using occupancy time method, was found to vary among intersections, even when they were similar in geometry. This is attributed to the proportion of large-size vehicles in the conflicting traffic. A statistically strong relation is found between the critical gap of a vehicle type and the proportion of large-size vehicles in the conflicting traffic.]]></description>
      <pubDate>Tue, 28 Jan 2020 09:42:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1678353</guid>
    </item>
    <item>
      <title>Auto Thieves Target Big Engines, Luxury Cars and Pickups, HLDI Shows in New Report</title>
      <link>https://trid.trb.org/View/1647100</link>
      <description><![CDATA[This article discusses the findings of a recent study by the Highway Loss Data Institute (HLDI) on the types of vehicles that are most likely to be stolen.  Two large cars with powerful engines (Dodge Charger HEMI and Dodge Challenger SRT Hellcat) are the most likely vehicles to be stolen.  Two of the vehicles least likely to be stolen are Tesla models; the author hypothesizes that these electric vehicles are usually parked in garages or close to a house with a power supply, thus may be more difficult to steal.  The study used claims per insured vehicle year to compare the relative risk of each vehicle, rather than using raw numbers of vehicles stolen (which therefore tends to be dominated by the most common vehicles on the road).  The article includes a chart of the 20 vehicles with the highest claim frequencies for whole-vehicle theft and a second chart with the 20 vehicles with the lowest claim frequencies for whole-vehicle theft (both charts cover 2016-2018 model years). Readers are advised to email researchpapers@iihs.org for a copy of the full report.]]></description>
      <pubDate>Fri, 23 Aug 2019 17:02:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/1647100</guid>
    </item>
    <item>
      <title>A Simulation Study of the Efficiency of Unmarked On-Street Parking and Vehicle Downsizing</title>
      <link>https://trid.trb.org/View/1495864</link>
      <description><![CDATA[Does unmarked on-street parking accommodate more cars—because smaller cars take less space? One would intuitively think so, but because of the mismatch effect of very small cars, unmarked spacing may not be more efficient. This study uses computer simulation where queues of randomly generated vehicles are assigned to marked and unmarked spaces. Simulation results show that unmarked parking is only more efficient when the curb is more segmented, or significantly different from the integer times of the optimal length of one marked space. Otherwise, marked parking or shorter marked parking under high demand is better. Unmarked parking also has higher requirement for considerate behavior. This simulation study also finds that vehicle downsizing only significantly improves parking efficiency when the vehicle is downsized to two-seaters that can vertically park. The study also proposes a new type of “block-based” parking that achieves some of the flexibility of unmarked parking while keeping mismatch-effect relatively low.]]></description>
      <pubDate>Thu, 22 Mar 2018 12:03:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/1495864</guid>
    </item>
    <item>
      <title>Do Demographics and Functional Abilities Influence Vehicle Type Driven by Older Canadians?</title>
      <link>https://trid.trb.org/View/1412059</link>
      <description><![CDATA[Candrive (the Canadian Driving Research Initiative for Vehicular Safety in the Elderly) baseline data (n = 928; aged 70 to 94; 62% were men) was examined in this study in order to determine whether driver characteristics (i.e., age, gender, height, weight, BMI) and certain functional abilities (i.e., Rapid Paced Walk, Timed Up and Go) were an influence on the types of vehicles driven. With respect to type of vehicle and mean driver age (F = 3.58, p = 0.003), height, (F = 13.32, p < 0.001), weight (F = 14.31, p < 0.001), and BMI (F = 4.40, p = 0.001), there were significant differences. Small and medium-sized cars, compared to larger ones, were driven by a greater proportion of drivers with osteoporosis (?2 = 21.23, p = 0.020) and osteo/rheumatoid arthritis (?2 = 21.23, p = 0.020). In order to examine older driver-vehicle interactions and the relationship to demographics and functional abilities, given the vulnerability of this age group to automotive-related injuries, further research is needed.]]></description>
      <pubDate>Mon, 01 Aug 2016 16:45:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1412059</guid>
    </item>
    <item>
      <title>Relationship between Subjective Loudness of Vehicle Acceleration Sound and the Vehicle Styling</title>
      <link>https://trid.trb.org/View/1282177</link>
      <description><![CDATA[In this study, an influence of vehicle styling impression on loudness of acceleration sound was investigated. Luxury or sporty vehicle images were presented to the subjects as the acceleration sounds were being replayed to investigate the influence. The results indicated that the subjects who drove vehicles frequently felt that the acceleration sound presented with the luxury vehicle image was louder than that with sporty vehicle image. But the loudness did not change largely in rarely driving subjects. Consequently, it was clarified that the subjective loudness changed depending on the vehicle styling and the driving frequency of the subject.現在まで，自動車の音質向上を目的に様々な定量化の試みが行なわれてきた．一方で，視覚情報の提示による聴覚的な印象変化についても近年研究が進められている．本研究では，自動車加速音の主観的な大きさを対象に，車両デザインの違いにより，音の大きさがどのように変化するのか，ということについて調査を行なった．]]></description>
      <pubDate>Fri, 28 Feb 2014 12:30:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1282177</guid>
    </item>
    <item>
      <title>Choosing the Right Design Vehicle for Urban Roundabouts</title>
      <link>https://trid.trb.org/View/987384</link>
      <description><![CDATA[The choice of a design vehicle for a modern roundabout has significant influence on the safety, geometry, capacity, and cost of the roundabout. Large design vehicles must be accommodated appropriately, but not necessarily equally in all cases. Other design vehicles - large and small - must also be considered.]]></description>
      <pubDate>Tue, 30 Nov 2010 07:49:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/987384</guid>
    </item>
    <item>
      <title>Car Size and Weight Are Crucial</title>
      <link>https://trid.trb.org/View/930593</link>
      <description><![CDATA[This article extends the crashworthiness studies of certain small cars by testing them in collisions with other vehicles that earn the same crashworthiness ratings and that are manufactured by the same automaker.  The authors note that most crashworthiness ratings are determined from offset collisions into deformable barriers.  However, a more-realistic front-to-front collision can provide information about the safety consequences of vehicle size and weight.  The article reports on a recent study by the Insurance Institute for Highway Safety (IIHS) in which a Honda Fit was crashed into a Honda Accord, a Smart Fortwo into a Mercedes C class, and a Toyota Yaris into a Toyota Camry.  These tests of paired cars reflect the physics of crashes, confirming that bigger, heavier cars are safer than their minicar counterparts.  The article briefly summarizes the findings of the crash tests.  Readers are referred to the Institute's website for consumer information about crashworthiness test ratings (iihs.org/ratings).]]></description>
      <pubDate>Thu, 16 Sep 2010 12:43:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/930593</guid>
    </item>
    <item>
      <title>Car Size and Weight are Crucial</title>
      <link>https://trid.trb.org/View/887921</link>
      <description><![CDATA[Head on crashes between a very small car and a medium size vehicle result in more damage and potential injury to occupants of the small car, according to tests conducted by the Insurance Institute for Highway Safety. The researchers paired small cars and mid-size vehicles, such as the Honda Accord and the Honda Fit. The Accord’s occupant compartment remained intact during the 40 mph frontal collision, while the survival space around the driver dummy of the Fit was compromised. Size, weight and physics dictate crash outcomes, according to the researchers. If a heavier car weighs twice as much as the lighter car, the forces on the lighter car and its occupants will be twice as great. The death rate in late model mini-cars involved in multi-vehicle crashes during 2007 were nearly two times as high as the rate in large cars. An additional section to the article looks at how fuel economy and safety can be simultaneously achieved. Issues discussed include fuel economy standards and travel speeds.]]></description>
      <pubDate>Thu, 30 Apr 2009 08:27:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/887921</guid>
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