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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>A Threat to Maritime Trade: Analysis of Piracy Attacks Between 2015 and 2022 and the Period of COVID-19</title>
      <link>https://trid.trb.org/View/2350427</link>
      <description><![CDATA[More than 80 percent of world trade is transported by sea. Maritime piracy negatively affects international maritime transport and trade. The aim of the study is to analyze maritime piracy attacks between 2015-2022 and during the coronavirus disease-2019 (COVID-19) period. In the study, a literature review, main reasons and statistics for piracy and armed robbery attacks, international efforts to combat maritime piracy were examined and maritime piracy attacks were analyzed in 2015-2022 and the COVID-19 period. The results of the main findings are as follows; the most piracy attacks occurred in 2015, the most attacks were occurred in March-April-May majority of attacks occurred between the hours 24: 00-04: 00, the most attacks occurred in South East Asia, the most types of attacks against to ships was boarded. Marshall Islands-flagged ships were the most attacked. There is a weak statistical relationship between the piracy attacks by months and regions and between the piracy attacks by years and type of attacks. There is no statistical relationship between other variables.]]></description>
      <pubDate>Fri, 28 Jun 2024 14:00:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2350427</guid>
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    <item>
      <title>Application of Queuing Theory to a Toll Plaza-A Case Study</title>
      <link>https://trid.trb.org/View/1974530</link>
      <description><![CDATA[Queuing areas are the junctions involving vehicles waiting in lines and are characterized by an arrival pattern, a service facility arranged in a particular manner and service time. Since the maximum capacity of roads and service facility (i.e. number of booths in case of tolls) are fixed for certain period (i.e. design period), it is necessary to measure the efficiency of a facility. In case of toll booths on highways/freeways which are attractors of vehicles from different origin presumes the flow to be continuous and the vehicle inter-arrival random, adding to this is variability in demand and service (service time in toll booths), poses a problem in optimizing the service facility. In the present study, an existing toll plaza on a 4-lane divided highway having two-way movement (N–S and S–N) is evaluated based on queuing theory. Parameters like traffic volume, space-mean speed and time headway are expressed in 1 h intervals. The vehicle arrival patterns on both directions are postulated to be Poisson distributed and the observed data were fitted to the Poisson distribution. In case of N–S movement, observed frequency and theoretical frequency are found out to be equal indicating the postulated Poisson distribution to be the true population distribution. The use of chi-square test as an index of the goodness of fit for significance level 5% with 10° of freedom justifies the postulated Poisson distribution can be used for future analysis of vehicle arrivals in the respective direction. Finally, the utilization factor indicates a single booth in N–S direction to be under steady-state condition during the study period.]]></description>
      <pubDate>Mon, 04 Dec 2023 15:45:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1974530</guid>
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    <item>
      <title>An automated driving systems data acquisition and analytics platform</title>
      <link>https://trid.trb.org/View/2155020</link>
      <description><![CDATA[In this paper, an automated driving system (ADS) data acquisition and analytics platform for vehicle trajectory extraction, reconstruction, and evaluation based on connected automated vehicle (CAV) cooperative perception are presented. This platform presents a holistic pipeline from the raw advanced sensory data collection to data processing, which is capable of processing the sensor data from multi-CAVs and extracting the objects’ Identity (ID) number, position, speed, and orientation information in the map and Frenet coordinates. First, the ADS data acquisition and analytics platform are presented. Specifically, the experimental CAVs platform and sensor configuration are shown, and the processing software, including a deep-learning-based object detection algorithm using LiDAR information, a late fusion scheme to leverage cooperative perception to fuse the detected objects from multi-CAVs, and a multi-object tracking method, is introduced. To further enhance the object detection and tracking results, high-definition maps consisting of point cloud and vector maps are generated and forwarded to a world model to filter out the objects off the road and extract the objects’ coordinates in Frenet coordinates and the lane information. In addition, to refine trajectories from the object tracking algorithms, a post-processing method is proposed. Given the objects’ information from the object detection and tracking and the world model, a Kalman filter and Chi-square test method are applied to reduce the noise and remove the outlier in the trajectories. Aiming at tackling the ID switch issue of the object tracking algorithm, a fuzzy-logic-based approach is proposed to detect the discontinuous trajectories belonging to the same object. Then, a vehicle-kinematics-based trajectory prediction method is used, and a forward–backward-smoothing technique is applied to reconstruct the trajectory between the discontinuous trajectories. Finally, results, including object detection and tracking and a late fusion scheme, are presented, and the improvements by the post-processing algorithm in terms of noise level and outlier removal are discussed, which confirm the functionality and effectiveness of the proposed holistic data collection and processing platform. In another aspect, the extracted objects’ information and generated HD maps can be used for several purposes in the transportation research community and ADS development community: analyzing the interaction between human-driven vehicles and ADS-equipped vehicles, car-following behavior analysis of ADS-equipped vehicles, traffic flow status analysis and modeling, and scenario generation for ADS testing.]]></description>
      <pubDate>Sat, 19 Aug 2023 15:06:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2155020</guid>
    </item>
    <item>
      <title>In-Depth Analysis of Pedestrian-Vehicle Accidents Based on Chi-Square Test and Logistic Regression</title>
      <link>https://trid.trb.org/View/1836422</link>
      <description><![CDATA[Taking the pedestrian-vehicle accidents in the China in-Depth Accident Study (CIDAS) database as a sample case, 13 accidents' morphological parameters were selected from three aspects: human, vehicle and environmental factors, and their depth analysis was carried out to obtain their distribution law through the card. The chi-square test and logistic regression method are used to analyze the correlation between the injury severity of pedestrians and other accidental morphological parameters in pedestrian-vehicle accidents. The results show that there is no significant correlation between gender/season and injury severity of pedestrians. The age of pedestrians and the collision speed is the strongest correlation with injury severity of pedestrians. When a pedestrian is over 65 years old, the pedestrian height is in the range of 160-170 cm, the collision speed is greater than 60 kilometers per hour, and the pedestrian speed is greater than 8 kilometers per hour, the probability of pedestrian injury is significantly increased.]]></description>
      <pubDate>Sun, 08 May 2022 16:20:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1836422</guid>
    </item>
    <item>
      <title>Exploring temporal interactions of crash counts in California using distinct log-linear contingency table models</title>
      <link>https://trid.trb.org/View/1874100</link>
      <description><![CDATA[Temporal trait of crashes has huge impact on road crash occurrence and a large proportion of research have considered different time periods to determine the causes and features of crash occurrence or frequency. Compared with other safety studies based on a single time interval, considerably less research has relied on the use of multiple time units, especially for the time intervals of less than one year. The research aims to fill the gap by investigating the temporal distribution of crash counts using multiple time spans including hour, weekday and month. To illustrate the most accurate results possible, both the Chi-square test and Cochran–Mantel–Haenzel tests were employed to explore the independence of various time units based on two-way and three-way contingency tables. Eight contingency table models were developed which can be classified into four groups including Complete Independence, Joint Independence, Conditional Independence and Homogeneous Association. Finally, a set of evaluation criteria were utilized for evaluation of the model performance. The results revealed the significant association existence in all time variables (hour, weekday, month) and the model with both main and all interactive effects of time variables provides best prediction performance. Also, the findings showed that Hour 18, weekdays 1, 6, 7 (Friday and Weekends), and month 8 (August) have the largest number of crash occurrences. It is suggested that both main and interactive effects of time variables should be included for model development, which otherwise might yield misleading information. It is anticipated that research results will benefit the safety professionals with better understanding of the temporal patterns of crashes with different time periods and allow the safety administrators to allocate the safety resources.]]></description>
      <pubDate>Thu, 28 Oct 2021 09:17:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/1874100</guid>
    </item>
    <item>
      <title>Hit-and-runs more common with pedestrians lying on the road: Analysis of a nationwide database in Japan</title>
      <link>https://trid.trb.org/View/1881753</link>
      <description><![CDATA[To determine the trends with fatally or otherwise injured pedestrians lying on the road and the relationship to hit-and-run incidents in Japan. The authors extracted data for 2012-2016 from the records of the Institute for Traffic Accident Research and Data Analysis, Japan, a nationwide traffic accident database. All the injured and fatally injured pedestrians were selected. The authors examined the levels of pedestrian injury, vehicle speed immediately before the collision, whether or not the pedestrian was lying on the road, and hit-and-run incidents. Chi-square test was employed to make a statistical comparison between the two groups. The database contained data on 286,383 pedestrian casualties and 7256 fatalities; 8.3% of fatalities (602 persons) and 0.6% of casualties (1827 persons) involved pedestrians lying on the road. The rates of fatalities and severe injuries were significantly higher for pedestrians who were lying on the road than for those who were not. Hit-and-run incidents were evident in 4.0% of casualties and 7.3% of fatalities. The rate of hit-and-run cases was also significantly higher among pedestrians who were lying on the road. Among fatally injured pedestrians not lying on the road, the rates with speeds of >=30 km/h did not differ significantly between hit-and-run and other cases. However, when the pedestrians were lying on the road, the rate was significantly increased in hit-and-run cases. This is the first report to focus on pedestrians lying on the road and being involved in hit-and-run incidents. In addition to preventing hit-and-run incidents, prevention of pedestrians lying on the road could also decrease fatalities.]]></description>
      <pubDate>Tue, 26 Oct 2021 14:30:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1881753</guid>
    </item>
    <item>
      <title>Examining Minimum Information Requirements for Electronic Aeronautical Charts</title>
      <link>https://trid.trb.org/View/1862935</link>
      <description><![CDATA[The purpose of this research was to identify a set of minimum information elements for user- configurable electronic aeronautical charts. The concept examined in this study is that pilots brief with a fixed chart but then fly with a user-configurable aeronautical chart, which may not include all the information elements that were briefed. The authors conducted a survey to identify a set of minimum information element requirements for this operational concept. They invited 1,351 transport, commuter, military, and general aviation pilots to participate; 326 responded (a 24% response rate), but only 267 pilots met the inclusion criteria. Of these, 229 pilots completed the survey (60 air transport pilots, 60 commuter pilots, 60 general aviation pilots and 49 military pilots). The survey was comprised of lists of information elements shown on four types of aeronautical charts: 1) Instrument Approach Procedure (IAP), 2) Enroute Instrument Flight Rules (IFR), 3) Standard Terminal Arrival Route (STAR), and 4) Standard Instrument Departure (SID). There were a total of 427 information elements across charts, so to prevent survey fatigue, the authors divided the information elements into two surveys. The first survey included information elements on IAP/Enroute IFR charts (221 information elements), and the second survey included information elements from SID/STAR charts (206 information elements). For each survey, participants were instructed to rate the importance of information elements for a new charting concept, which uses customizable electronic charts that are interactive and customized to display only information elements needed to execute the procedure. The authors analyzed the data using one-way chi-square tests and consulted with subject matter experts to identify a criticality level for each information element. Based on this analysis, the authors were able to categorize 85% of the information elements across all four chart types. The authors then developed prototype charts to visualize what the concept might look like.]]></description>
      <pubDate>Tue, 03 Aug 2021 15:31:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1862935</guid>
    </item>
    <item>
      <title>Comparative Analysis of Aggressive-Driving and Distracted-Driving Crashes Involving Commercial Motor Vehicles in Kentucky</title>
      <link>https://trid.trb.org/View/1856991</link>
      <description><![CDATA[Aggressive driving and driver distraction have widely been reported as the two main causes of traffic crashes. According to the police crash database for the years 2015–2019 in Kentucky, crashes affected by driver aggressive violations and distraction activities accounted for nearly 20% and 36% of the total crashes involving commercial motor vehicles (CMVs), respectively, while they were responsible for 31% and 41% of the total severe crashes, respectively. This study aims at comparing the injury severity outcomes (severe versus non-severe) concerning aggressive-driving and distracted-driving crashes under various circumstances. Recent five years of CMV-related crashes (2015–2019) were collected from the Kentucky Transportation Cabinet (KYTC). Separate Z-tests of proportions and chi-square tests of independence were, respectively, applied to identify the factors affecting the severity of crashes for each of aggressive-driving and distracted-driving CMV-involved crashes. The overall results of Z-test comparing the proportions of severe versus non-severe injuries showed that both aggressive- and distracted-driving crashes significantly increased injury severity. The test further demonstrated that, for all the significant variables, the proportion of severe injuries in aggressive-driving crashes was higher than that in distraction-related crashes. Interestingly, road segments with lanes equal to or less than 11 ft increased the risk of severe aggressive-related CMV crashes (odds ratio = 1.30), but reduced the risk of severe injuries in distraction-related CMV crashes (odds ratio = 0.77). Head-on crashes, use of alcohol or drugs, angle collisions, going straight ahead, and paved right shoulder were the top five factors increasing the risk of severe CMV-involved crashes caused by aggressive-driving and distraction behaviors. On the other hand, seatbelt use, sideswipe collisions, urban areas, at-fault CMVs, and annual average daily traffic (AADT) per lane greater than 10,000 were the top factors reducing the probability of severe injuries in CMV crashes related to driver aggressiveness and distraction. The study findings suggest that launching driving safety campaigns, removal of road distracting elements (e.g., billboards) at high crash risk spots, and intensifying traffic enforcement can reduce the severity of CMV crashes affected by aggressive-driving and driver-distraction acts.]]></description>
      <pubDate>Fri, 23 Jul 2021 15:26:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1856991</guid>
    </item>
    <item>
      <title>Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway</title>
      <link>https://trid.trb.org/View/1854299</link>
      <description><![CDATA[Detecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with a lower collision frequency but a higher percentage of injury and fatal collisions. This study developed systematic ways of detecting reproducible fatal collision locations (R) using the naïve Bayes approach and a continuous risk profile (CRP) that estimates the true collision risk by filtering out random noise in the data. The posterior probability of fatal collisions being reproducible at a location is estimated by the relationship between the spatial distribution of fatal-collision locations (i.e., likelihood) and the CRP (i.e., prior probability). The proposed method can be used to detect sites with the highest proxy measure of the posterior probability (PMP) of observing R. An empirical evaluation using 5-year traffic collision data from six routes in California shows that detecting R based on the PMP outperform those based on the SPF-based approaches or random selection, regardless of various conditions and parameters of the proposed method. This method only requires traffic collision and annual traffic volume data to estimate PMP that prioritize sites being R and the PMPs can be compared across multiple routes. Therefore, it helps government agencies prioritizing sites of multiple routes where the number of fatal collisions can be reduced, thus help them to save lives with limited resources of data collection.]]></description>
      <pubDate>Fri, 23 Jul 2021 15:26:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1854299</guid>
    </item>
    <item>
      <title>Can’t simply roll it out: Evaluating a real-world virtual reality intervention to reduce driving under the influence</title>
      <link>https://trid.trb.org/View/1850189</link>
      <description><![CDATA[Driving under the influence (DUI) increases the risk of crashes. Emerging technologies, such as virtual reality (VR), represent potentially powerful and attractive tools for the prevention of risky behaviours, such as DUI. Therefore, they are embraced in prevention efforts with VR interventions primed to grow in popularity in near future. However, little is known about the actual effectiveness of such DUI-targeting VR interventions. To help fill the knowledge gap, this study explored the effects of one VR intervention as delivered in the real world. Using pre and post test design, including an intervention group (n = 98) and a control group (n = 39), the intervention evaluation examined young drivers’ (aged 18 to 25, no known history of DUI) intention and self-reported behaviour three months after the intervention as compared to the baseline. The results did not provide evidence for statistically significant effects of the VR intervention on self-reported DUI behaviour during the three months post intervention and DUI intention at three months post intervention. Such results might be due to the fact that the recruited participants generally self-reported little DUI behaviour, i.e. positively changing behaviour that is already positive is inherently challenging. Nevertheless, the results question the utility of funding the roll-out of arguably attractive technologies without a thorough understanding of their effectiveness in particular settings. To improve the potential for future positive outcomes of such interventions, the authors provide suggestions on how VR software might be further developed and, subsequently, leveraged in future research to improve the likelihood for behavioural change, e.g. by collecting, analysing and presenting objective driving performance data. Alternatively, future endeavours might focus on participants with known DUI history and examine the effects of the VR intervention for this particular higher-risk group.]]></description>
      <pubDate>Fri, 23 Jul 2021 15:26:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1850189</guid>
    </item>
    <item>
      <title>Crash severity modelling using ordinal logistic regression approach</title>
      <link>https://trid.trb.org/View/1761187</link>
      <description><![CDATA[Road traffic accident is one of the major problems facing the world. The carnage on Ghana’s roads has raised road accidents to the status of a ‘public health’ threat. The objective of the study is to identify factors that contribute to accident severity using an ordinal regression model to fit a suitable model using the dataset extracted from the database of Motor Traffic and Transport Department, from 1989 to 2019. The results of the ordinal logistic regression analyses show that the nature of cars, National roads, over speeding, and location (urban or rural) are significant indicators of crash severity. Strategies to reduce crash injuries should include physical enforcement through greater police presence on Ghana's roads, as well as technology. There is also the need to train drivers to be more vigilant in their travels especially on the national roads and in the urban areas. The recommendation is that well thought-out and contextualised written laws and sanctioned schemes to monitor and enforce strict compliance with road traffic rules should be put in place.]]></description>
      <pubDate>Mon, 22 Feb 2021 10:17:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1761187</guid>
    </item>
    <item>
      <title>Exploring the factors affecting bike-sharing demand: evidence from student perceptions, usage patterns and adoption barriers</title>
      <link>https://trid.trb.org/View/1767838</link>
      <description><![CDATA[Shared mobility is an innovative transportation strategy defined as the shared use of a vehicle, bicycle or other mode which enables users to gain short-term access to transportation modes on an as-needed basis. Bike-sharing systems have rapidly expanded around the world with important implications for urban areas. Considering the benefits regarding cycling and implications deriving from bike-sharing services implementation, this paper presents an in-depth analysis to investigate a variety of determinants, barriers and motivation that can influence the willingness to cycling and join bike-sharing. The study focuses on a specific target group represented by university students and their preferences have been collected through a structured questionnaire in applying the Likert Scale. A statistical analysis has been realized based on a chi-squared test, deriving the difference between expected and observed frequencies for several combinations of the analyzed attributes. First results highlight the differences between the impact of economic, environmental and social factors for students cycling and provide useful suggestion to define the way for a well-thought-out design of a bike-sharing transport service.]]></description>
      <pubDate>Fri, 19 Feb 2021 10:31:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/1767838</guid>
    </item>
    <item>
      <title>Seatbelt Use among Vehicle Occupants in Fatal Crashes in the United States: Does Vehicle Type and Age Affect Injury Outcome?</title>
      <link>https://trid.trb.org/View/1759989</link>
      <description><![CDATA[Studies have shown that occupant’s injury severity increases with vehicle age and older model year vehicles when a traffic crash occurs. But, does vehicle occupant restraint use play a role in the injury outcome? The primary objective of this study was to determine the relationship between adult vehicle occupant’s seatbelt use, vehicle type and age, and injury severity using crash data from the Fatality Analysis Reporting System (FARS). Five-year crash data (2014 to 2018) were retrieved from FARS for all vehicle occupants involved in fatal crashes for 50 states and the District of Columbia. Chi-square analyses were conducted to test several hypotheses regarding adult seatbelt use. The results of the analysis showed a lower seatbelt use rate among occupants of older vehicles than occupants in newer vehicles. This finding was consistent across all the vehicle types: passenger cars, pickup trucks, and sport utility vehicle (SUV)-Minivans. Regardless of how old the vehicle was at the time of the crash (i.e., 1-6 years, 7-11 years, 12-15 years, and > 15 years) and the type of vehicle involved, the seatbelt use rates were consistently lower among fatally injured occupants than those who suffered no or possible/severe injuries. The findings in this study are important for the development of seatbelt use intervention programs that are persuasive and have the greatest potential for effectiveness.]]></description>
      <pubDate>Thu, 04 Feb 2021 16:48:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1759989</guid>
    </item>
    <item>
      <title>Victims of road accidents with serious injuries and dependence on some individual, climatic and infrastructure factors on federal highways in Brazil</title>
      <link>https://trid.trb.org/View/1730430</link>
      <description><![CDATA[Road or urban traffic accidents in Brazil have a large presence in external causes of mortality. The main goal of this study is to discover significant factors in the incidence of accidents on Brazilian highways based on a database with information on each person injured on federal highways in Brazil reported by the Federal Highway Police. Some factors are considered in the study as cause of the accident, type of accident, stage of the day, weather condition, highway type, highway facility, age of the victim, gender of the victim and type of vehicle. From the obtained results of chi-square tests and logistic regression models, it was observed statistical dependence (p < 0.05) of the occurrence of injured people with serious injuries and the factors cause of the accident, type of accident, day, highway type and vehicle type. Considering the dead victims, the covariates age, time of day, highway type, highway facility, gender and type of vehicle showed significance (p < 0.05). These results are of great interest for authorities to increase road enforcement, improve highway facilities and target the production of vehicles with better safety standards.]]></description>
      <pubDate>Tue, 22 Sep 2020 14:28:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1730430</guid>
    </item>
    <item>
      <title>Determinants of severe injury and mortality from road traffic accidents among motorcycle and car users in Southern Thailand</title>
      <link>https://trid.trb.org/View/1730422</link>
      <description><![CDATA[This study aimed to identify factors associated with severe injury and mortality from road traffic accidents (RTA) among motorcycle and car users in southern Thailand. The data were obtained from the Office of Disease Prevention and Control, Thailand, for years 2008–2013. Chi-squared tests were used to assess associations between determinants and outcomes and these associations were then estimated after adjusting for possible confounding with other factors using logistic regression. Severe injury and mortality contributed 11.6% and 5% to RTA of motorcycle users, and 14.3% and 7.5% for car users. Among motorcycle users, male gender, older age, and not wearing a helmet increased severe injury and mortality rates, whereas drivers had more severe injuries than passengers. Older car users had higher severe injury and mortality rates, whereas not fastening seat belts had higher mortality. Safety device use should be made mandatory for both drivers and passengers. Male motorcycle users and the elderly should be focused on.]]></description>
      <pubDate>Tue, 22 Sep 2020 14:28:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1730422</guid>
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