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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <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>The Impact of Vehicle Lane Changing Behavior on Road Capacity Based on VISSIM Simulation</title>
      <link>https://trid.trb.org/View/1897465</link>
      <description><![CDATA[Vehicle lane changing behavior is an important factor affecting the road capacity. This paper explores the influence of the disturbance wave generated by lane changing behavior on travel speed and headway of the fleet and proposes a calculation model of the road capacity reduction coefficient. As the frequency of lane changes influences road capacity, this paper analyzes the range of disturbance propagation, the average speed of the fleet and the average headway of two-lanes in the same direction. It further examines the multiple “no influence” and “influential” lane-changing cases and examines the relationship between lane changing actions. Using VISSIM simulation platform, experimental data is obtained. The results show that there is only 4.6% error between the numerical value calculated by the model and the simulation result measured by the VISSIM, which verifies the proposed method.]]></description>
      <pubDate>Tue, 25 Jan 2022 17:29:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/1897465</guid>
    </item>
    <item>
      <title>Impact of Community Severance for Safety of Local Activities Around a Multi-Lane Highway</title>
      <link>https://trid.trb.org/View/1635701</link>
      <description><![CDATA[In order to evaluate safety impact for small area surface but not served by a multi-lane highway, community severance caused by a multi-lane highway with high speed and controlled access is studied and assessed. Conflicts between local traffic and traffic on the highway would aggravate. A comprehensive assessment method would be implemented to value the impact for local trips' safety caused by community severance. The negative benefit or efficiency of the safety problems caused by detour, heavy traffic, high speed etc. will be measured in quantitative or categorical variable, in order to evaluate convenience and safety impact of various access management perspectives. The aim of the research is to remind designers, planners or decision-makers to consider the community severance problems for local trips.]]></description>
      <pubDate>Tue, 03 Sep 2019 11:44:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/1635701</guid>
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    <item>
      <title>A Study on Efficient Operation of Expressway HOV Lane System Through the Analysis of Driving Pattern of Vans</title>
      <link>https://trid.trb.org/View/1517454</link>
      <description><![CDATA[This study attempted to derive the optimum standard to allow vans to use the HOV lane. As such, this study analyzed the traffic volume-speed relationships on the HOV lane and the general lane, respectively, as well as the effect of traffic congestion in the general lane on the HOV lane. The analysis result showed that if the speed of vehicles on the general lane decreased, the ratio of the vans on the HOV lane significantly increased. When the speed on the general lane decreased to less than 60 km/h, the vans changed the lane to the HOV lane, which made the traffic volume of the vans greater than the traffic volume of the buses on the HOV lane. The result of lane travel cost calculation showed that the total travel cost is minimized when the van inflow rates are 75% (v/c=0.8) and 55% (v/c=1.0).]]></description>
      <pubDate>Fri, 29 Jun 2018 16:33:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1517454</guid>
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    <item>
      <title>Micro-Level Analysis on Traffic Flow Parameters at Work-Zone Road Section Using Vehicular Trajectory Data</title>
      <link>https://trid.trb.org/View/1496881</link>
      <description><![CDATA[The research work is carried out to examine microscopic and macroscopic traffic parameters at work zone on high speed urban roads. Due to construction of elevated metro rail project over the study section, having five-lanes in one direction, two-lanes are reduced (since past six months). The traffic data are collected using videography, later, trajectory data is extracted using semi-automated image processing software, under different flow conditions, for with and without work zone scenarios. Time-space plot for with and without work zone scenarios clearly indicates substantial decrement in slope due to construction work zone. Longitudinal speeds of the vehicles under work zone scenarios is decreased significantly, compared to without work zone scenarios. Further, lane utilization behavior under different flow conditions also shows vehicles movement closer to work zone side lane is highly affected under low flow conditions. Hysteresis plot of leader-follower vehicles also shows the increased cautiousness of the drivers at work zone location, as they maintain consistent relative velocity with respect to its leader to avoid rear-end crashes. The concept of perceiving time for driver is propose in the present study with its basis from hysteresis plot which furthers, assessment of chances rear-end crashes. It is found that bikes (motorized two-wheeler) are most vulnerable to rear-end crashes at work zone scenario. Finally, speed-flow relationship developed using Van Aerde model for two scenarios, shows reduction in capacity by about 43%, due to lane drops. It is expected that, outcome of the present study may be useful in exploring traffic operations at the location of work zone, more precisely.]]></description>
      <pubDate>Thu, 22 Feb 2018 09:18:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1496881</guid>
    </item>
    <item>
      <title>What Characterizes a Vehicle as Follower on Two-Lane Intercity Highways under Heterogeneous Traffic Conditions</title>
      <link>https://trid.trb.org/View/1489162</link>
      <description><![CDATA[The presence of a high proportion of vehicles in the following condition indicates that a particular roadway facility is performing poorly. Due to lack of related standard guidelines, planners and engineers in India use the same definition presented in U.S. Highway Capacity Manual regarding following vehicles, which may not be appropriate because of the heterogeneity in Indian traffic conditions. After performing graphical analysis, it was concluded that the previously used methodologies cannot be used for the present study because it could mislead the final findings. Hence, a new method was introduced to identify following vehicles in which speed difference (SD) and gap threshold value are used instead of the headway between two consecutive vehicles. It was found that after a cut-off gap threshold of 10 s, all the vehicles, irrespective of their categories, started traveling in the nonfollowing condition. A SD limit of −4 to +10  km/h was used to identify the following vehicles below the cut-off gap threshold value of 10 s. By using the acceptance curve method, different cut-off gap values ranging from 1.9 to 4.4 s were observed at all study sites, beyond which probability of not following (PNF) increased. After validation of the results, two-way traffic volume was identified as the dominating parameter that affects the cut-off gap value.]]></description>
      <pubDate>Wed, 24 Jan 2018 09:20:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/1489162</guid>
    </item>
    <item>
      <title>Outflow of Traffic from the National Capital Kuala Lumpur to the North, South and East Coast Highways Using Flow, Speed and Density Relationships</title>
      <link>https://trid.trb.org/View/1442377</link>
      <description><![CDATA[The functional relationships between flow (veh/km), density (veh/h) and speed (km/h) in traffic congestion have a long history of research. However, their findings and techniques persist to be relevant to this day. The analysis is pertinent, particularly in finding the best fit for the three major highways in Malaysia, namely the KL-Karak Highway, KL-Seremban Highway and KL-Ipoh Highway. The trans-logarithm function of density–speed model was compared to the classical models of Greenshields, Greenberg, Underwood and Drake et al. using data provided by the Transport Statistics Malaysia 2014. The results of regression analysis revealed that the Greenshields and Greenberg models were statistically significant. The trans-logarithm function was also tested and the results were nonetheless without exception. Its usefulness in addition to statistical significance related to the derived economic concepts of maximum speed and the related number of vehicles, flow and density and the limits of free speed were relevant in comparing the individual levels of traffic congestion between highways. For instance, KL-Karak Highway was least congested compared to KL-Seremban Highway and KL-Ipoh Highway. Their maximum speeds, based on three lanes carriage capacity of one direction, were 33.4 km/h for KL-Karak, 15.9 km/h for KL-Seremban, and 21.1 km/h for KL-Ipoh. Their corresponding flows were approximated at 1080.9 veh/h, 1555.4 veh/h, and 1436.6 veh/h.]]></description>
      <pubDate>Thu, 19 Jan 2017 09:12:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/1442377</guid>
    </item>
    <item>
      <title>Identification of Factors that May Affect the Discharge Flow at a Bottleneck</title>
      <link>https://trid.trb.org/View/1411517</link>
      <description><![CDATA[This study investigates various factors that cause the reduction of discharge flow at a bottleneck on an urban expressway. The current worst bottleneck on Tokyo Metropolitan Expressway Network seems to be combined complicate factors that affect the discharge flow at the bottleneck. Five causing factors, merging ratio, longitudinal gradient, duration time involved in congestion, environment of backlight and brightness are considered, and the impact of these five causing factors are investigated. Then the results supported the hypothesis that all of the five causing factors affect the discharge flow rate.]]></description>
      <pubDate>Thu, 28 Jul 2016 10:04:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1411517</guid>
    </item>
    <item>
      <title>The Impacts of Heavy-Duty Vehicle Platoon Spacing Policy on Traffic Flow</title>
      <link>https://trid.trb.org/View/1392278</link>
      <description><![CDATA[Spacing policy of heavy-duty vehicle (HDV) platoons determines the inter-vehicle distance between HDVs in steady state. It plays an important role in traffic throughput. For example, an HDV platoon with small spacing policies saves space on the highway so that it can accommodate more vehicles. Therefore, the traffic efficiency and highway capacity may be improved by applying small spacing policies on HDV platoons. Conversely, an HDV platoon with larger spacing policies requires more space on highways and thus has a negative impact on capacity. This paper specifically focuses on two commonly used spacing policies in HDV platooning, constant vehicle spacing (CVS) and constant time gap (CTG) and investigates respective impacts on traffic flow. The speed-density relation of mixed traffic flow is formulated as a function of traffic density, percentage of HDVs on highway and spacing policy of HDV platoon. In order to investigate the effects of HDV platooning to vehicle interaction, the speed-density relation is derived from car-following model. Numerical results show that HDV platooning with CVS policy yields the most significant improvement on highway capacity, compared with no HDV platooning scenario and HDV platooning with CTG policy. However, it has worse performance in heavily-congested traffic flows than CTG policy. A mixed CVS-CTG policy is therefore proposed in this study, in order to combine the benefits from CVS and CTG policies to traffic flow. This mixed spacing policy could be a promising alternative to the single spacing policy.]]></description>
      <pubDate>Thu, 24 Mar 2016 10:51:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1392278</guid>
    </item>
    <item>
      <title>Framework to Assess Multiclass Continuum Traffic Flow Models</title>
      <link>https://trid.trb.org/View/1392892</link>
      <description><![CDATA[Since the beginning of this millennium, many models of multiclass continuum traffic flow have been proposed. A set of qualitative requirements is presented for this type of model, including nonincreasing density–speed relationships and anisotropy. The requirements are cast into a framework that applies a generalized model of deterministic multiclass kinematic wave traffic flow. A step-by-step plan is developed to apply the framework to models that fit into the generalized model. The plan could be developed only with the Lagrangian formulation of the generic model but could also be applied to models in the traditional Eulerian formulation. It was concluded that only a few models known from the literature satisfied all requirements unconditionally. The step-by-step plan can furthermore be applied in the development of new models, the adaptation of existing models, and the calibration of model parameters.]]></description>
      <pubDate>Mon, 29 Feb 2016 16:56:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1392892</guid>
    </item>
    <item>
      <title>Conceptual Approach for Estimating Dynamic Passenger Car Units on Urban Arterial Roads by Using Simultaneous Equations</title>
      <link>https://trid.trb.org/View/1392810</link>
      <description><![CDATA[This study demonstrates that passenger car unit (PCU) values for a vehicle are not static and vary with traffic volume and composition. Data collected at eight urban arterial roads in India were analyzed to explain the dynamic nature of the PCU factor. All vehicles in the traffic stream were divided into five categories, and simultaneous equations were developed to determine the speed of a vehicle type from information on traffic volume and composition. These equations were used to show the variation in PCU values with traffic volume and composition on a road. The change in PCU values was explained on the basis of the relative interaction of vehicle type in the traffic stream at different volume levels. A proposed range of PCU values for big vehicles was from 1.47 to 1.65 for big cars and for heavy vehicles from 5.51 to 6.54, respectively, when their proportions in the mix remained within an observed range in the field. Similarly, a range of PCU values for motorized three-wheelers of 0.99 to 1.01 and a set of PCU values for motorized two-wheelers of 0.20 to 0.23 were obtained. Accuracy of the PCU values estimated through simultaneous equations was checked by comparing the estimated values with those calculated directly from the field data. Statistical testing showed that there was no significant difference between field-estimated and model-predicted PCU values. Further, the speed–volume relationships developed by using two sets of PCU factors yielded the capacity values with a difference of less than 2%; this result indicates the correctness of the methodology in this study.]]></description>
      <pubDate>Mon, 29 Feb 2016 16:56:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/1392810</guid>
    </item>
    <item>
      <title>Estimating Capacity of Bicycle Path on Urban Roads in Hangzhou, China</title>
      <link>https://trid.trb.org/View/1337236</link>
      <description><![CDATA[Bicycle path capacity is of significance for bicycle facilities planning, design and management. With the rapid increase of electric bicycles (e-bikes), the heterogeneous traffic composed with conventional bikes and e-bikes, which use conventional bicycle path, will bring some efficiency issues. This paper proposed a method to derive bicycle path capacity by fitting a relationship between the three fundamental traffic variables: flow, speed, and density. The field data of eleven bicycle path sections were collected in Hangzhou, China in the case study. The results indicated that the mean capacity is about 2512 bicycles/h per meter, and the capacity per meter is not related to bicycle path width. Four important factors of mixed bicycle traffic, e-bikes percentage, male percentage, young rider percentage, and carrying things percentage were introduced to analyze their effect on capacity. It is found that the estimated bicycle path capacity will increase with the increase of the e-bikes percentage or the decrease of carrying things percentage. These findings are valuable to support future studies for design and management of bicycle path under the condition mixed with bicycles and e-bikes traffic flow.]]></description>
      <pubDate>Thu, 26 Feb 2015 10:05:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1337236</guid>
    </item>
    <item>
      <title>Vehicular networks using the IEEE 802.11p standard: An experimental analysis</title>
      <link>https://trid.trb.org/View/1342539</link>
      <description><![CDATA[The IEEE 802.11 working group proposed a standard for the physical and medium access control layers of vehicular networks called 802.11p. In this paper the authors report experimental results obtained from communication between vehicles using 802.11p in a real scenario. The main motivation is the lack of studies in the literature with performance data obtained from off-the-shelf 801.11p devices. The study characterizes the typical conditions of an 802.11p point-to-point communication. Such a study serves as a reference for more refined simulation models or to motivate enhancements in the PHY/MAC layers. Field tests were carried out varying the vehicle's speed between 20 and 60 km/h and the packet length between 150 and 1460 bytes, in order to characterize the range, throughput, latency, jitter and packet delivery rates of 802.11p links. It was observed that communication with vehicles in motion is unstable sometimes. However, it was possible to transfer data at distances over 300 m, with data rates sometimes exceeding 8 Mbit/s.]]></description>
      <pubDate>Wed, 11 Feb 2015 09:20:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1342539</guid>
    </item>
    <item>
      <title>Traffic Volume Estimation using Probe-Car Data</title>
      <link>https://trid.trb.org/View/1322973</link>
      <description><![CDATA[Effective urban transportation planning requires clarification of the actual traffic demand in city. A probe car can effectively collect data on the traffic conditions of roads where traffic detectors have not been installed. The probe car detects the travel time, but it does not directly measure the traffic volume on the road. Therefore, a method to estimate traffic volume using probe-car data is expected to be useful for determining the actual traffic volume of all roads in a city. The authors describe here a traffic volume estimation method that uses speed-density-flow models and the data collected from a probe car. The models are calculated for some representative roads, and the traffic volumes of roads for which the traffic volume cannot be directly observed are estimated using a model of a road with similar features. The authors evaluated the estimation accuracy of this method in Tokyo, Japan and Hanoi, Vietnam and found that the traffic volume was estimated with a mean error rate of approximately 30% using this method.]]></description>
      <pubDate>Thu, 25 Sep 2014 09:03:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1322973</guid>
    </item>
    <item>
      <title>Vehicle Class-wise Speed Volume Model for Three-lane Undivided Urban Roads</title>
      <link>https://trid.trb.org/View/1280006</link>
      <description><![CDATA[Two or three lane two-way undivided roads are a ubiquitous presence in any city in India, and they are typically mixed traffic roads with vehicles of widely varying static and dynamic characteristics and with poor or no lane discipline. Hence multi-class speed flow equations are more relevant to these types of facilities rather than single class flow speed models. In addition, the available research for the operation of these types of facilities in India is very limited. Hence this paper aims to study the traffic flow in a three-lane two-way undivided road in the city of Chennai through developing multi-class speed-flow relationships using both linear and Bureau of Public Roads (BPR) models. It has been found from the study that models with total volume perform the same irrespective of units used being vehicles or PCU and models with class-wise (with and without direction) consistently perform better than total volume models. It was also found that linear models work better than other models for all vehicle classes modelling 2-wheeler speeds and two-wheelers, cars and LCVs have the greatest influence on the speeds of almost all the category of vehicles and the stream. One of the other important conclusions from the study is that an optimum use of class-wise and class and direction-wise models can offer models of better fit than two individual class and class-direction models.]]></description>
      <pubDate>Wed, 15 Jan 2014 09:29:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/1280006</guid>
    </item>
    <item>
      <title>Impact of Traffic Dynamics on Macroscopic Fundamental Diagram</title>
      <link>https://trid.trb.org/View/1240571</link>
      <description><![CDATA[Literature shows that – under specific conditions – the macroscopic fundamental diagram (MFD) describes a crisp relationship between the average flow (production) and the average density in an entire network. The limiting condition is that traffic conditions must be homogeneous over the whole network. Recent works describe hysteresis effects: systematic deviations from the MFD as result of loading and unloading.  This article proposes a two dimensional generalization of the MFD, the so-called GeneralizedMacroscopic Fundamental Diagram (GMFD), which relates the average flow to both the average density and the (spatial) inhomogeneity of density. The most important contribution is that we show this is a continuous function. Using this function, we can describe the mentioned hysteresis patterns. The underlying traffic phenomenon explaining the two dimensional surface described by the GMFD is that congestion concentrates (and subsequently spreads out) around the bottlenecks that oversaturate first. We call this the nucleation effect. Due to this effect, the network flow is not constant for a fixed number of vehicles as predicted by the MFD, but decreases due to local queuing and spill back processes around the congestion ”nuclei”. During this build up of congestion, the production hence decreases, which gives the hysteresis effects.]]></description>
      <pubDate>Fri, 22 Feb 2013 10:29:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1240571</guid>
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