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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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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      <title>MONITORING TRAFFIC LOAD PROFILES WITH HETEROGENEOUS DATA SOURCE CONFIGURATIONS</title>
      <link>https://trid.trb.org/View/481256</link>
      <description><![CDATA[In this paper an approach is presented that incorporates in-vehicle information and information provided by local sensors into a unified state estimator system based on the Extended Kalman Filter.  It is shown that velocity information as provided from individual vehicles from varying road positions leads to a time-variant estimation problem.  It is also shown that the transmission of trip data to a downstream beacon may be treated as a special case of the general time-variant estimation problem.  To assess the information gain obtained from this kind of data source an analytical measure for the observability of such a measurement configuration is introduced and evaluated for different data flow rates.  It is shown how this measure can be used to draw conclusions for the quality of estimation results as well as for data rate specifications that guarantee a certain degree of reliability for the estimated traffic load profile. The benefit drawn from this additional data source is underlined by simulation results.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481256</guid>
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      <title>NONPARAMETRIC TRAFFIC FLOW PREDICTION USING KERNEL ESTIMATOR</title>
      <link>https://trid.trb.org/View/481257</link>
      <description><![CDATA[In this paper, a nonparametric short-term traffic flow prediction model based on functional estimation techniques is considered, using the kernal smoother for the autoregression function.  This model is designed for nonlinear statistical prediction.  The application to traffic flow forecasting motivates the analysis, and shows the ability of this model to be turned in different ways for different specific applications.  Performance of the proposed model has been evaluated using measured data for a ZELT test area at Toulouse. Preliminary results indicates a greater predictive accuracy of this model.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481257</guid>
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    <item>
      <title>A BASIC STUDY OF EXPRESSWAY TRAVEL TIME ESTIMATION USING A BOTTLENECK SIMULATION MODEL</title>
      <link>https://trid.trb.org/View/481258</link>
      <description><![CDATA[When providing information for drivers, significant differences have been found between estimated and actual travel times.  It is suggested that this is due to traffic conditions changing when congestion is reached and to the long distances travelled on expressways.  The expressway bottleneck simulation model developed at Ritsumeikan has been modified to simulate long distance travel on motorways.  This was calibrated using data collected from a survey on the Tomei and Meishin Expressway. A procedure for estimating long distance expressway travel time was developed.  One of the prime objectives of the study was to confirm the adaptability and reliability of the method of travel time estimation.  For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481258</guid>
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    <item>
      <title>A CONTINUOUS TIME LINK MODEL FOR DYNAMIC NETWORK LOADING BASED ON TRAVEL TIME FUNCTION</title>
      <link>https://trid.trb.org/View/481259</link>
      <description><![CDATA[Two requirements for a satisfactory dynamic network loading model are identified: a) an allowance for overtaking on a link and b) flow propagation through the network should be consistent with speed.  The FIFO rule and its implications are discussed.  The two requirements identified are investigated and a link model developed which is based on a travel time formulation rather than the commonly adopted exit function formulations.  The model is then applied to small networks to show the ability of the model to explicitly deal with bottlenecks and to represent while-trip re-routing so that it can be used as a tool for the evaluation of control strategies.  For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481259</guid>
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    <item>
      <title>A QUEUEING THEORY APPROACH TO SPEED-FLOW-DENSITY RELATIONSHIPS</title>
      <link>https://trid.trb.org/View/481260</link>
      <description><![CDATA[A model for speed-flow-density relationships of traffic flow is developed that is completely based on queueing theory.  Thus the queueing theory is shown to provide a unified frame both for roads (uninterrupted flow) and intersections (interrupted flow).  The parameters of the model are the jam density, the mean desired speed of the drivers and the coefficient of variation of the time for passing a given piece of roadway at the desired speeds.  The model is discussed and its properties are investigated.  Numerical results obtained from the model are compared with empirical data.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481260</guid>
    </item>
    <item>
      <title>A NEW APPROACH TO PROBLEMS OF TRAFFIC FLOW THEORY</title>
      <link>https://trid.trb.org/View/481261</link>
      <description><![CDATA[The problems of modelling traffic flow when approaching maximum capacity are outlined and a new approach developed by the authors is described.  This method allows for the spontaneous formation of different kinds of localised structures in traffic flow as congestion increases.  A comprehensive macroscopic model of traffic flow based on a 'Navier-Stokes-like' equation is is first considered.  The decisive role of localised perturbation is then described which forms local clusters of vehicles of 3 types, a) a traffic jam, b) a low density traffic downstream which is formed by the jam and c) a transition layer between the low density traffic and the initial traffic flow.  Diagrams of the different states of traffic flow are discussed.  For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481261</guid>
    </item>
    <item>
      <title>FLOW AROUND DISTORTIONS IN A DENSE RECTANGULAR GRID ROAD NETWORK III COUPLING OF CROSS-FLOWS</title>
      <link>https://trid.trb.org/View/481262</link>
      <description><![CDATA[The theory described in parts I and II is generalized so that the cost of travel per unit distance at a point x , y is a linear function of not only the flow in the direction of travel but also of the flow in the cross direction.  If this cost is more sensitive to the flow in the cross direction than in the direction of travel, the traffic assignment problem is non-convex and possibly ill-posed. Otherwise it is (theoretically) possible to describe the flow around various distortions (obstructions or special road segments).  Some specific solutions are obtained in the nearly "singular" case in which the cost of travel is equally sensitive to the flows in the two cross directions.  The flow is still treated as a single commodity flow with travel only in the positive x and y directions.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481262</guid>
    </item>
    <item>
      <title>A TIME-DEPENDENT MULTI-CLASS PATH FLOW ESTIMATOR</title>
      <link>https://trid.trb.org/View/481263</link>
      <description><![CDATA[Path flow information is important to both traffic engineers and transportation planners.  A one-stage, multi-class path flow estimator is presented which allows for trip-makers with different levels of network information.  Link costs are decomposed into two components, a fixed component and a demand-determined, variable component.  Demand is determined by a logit path choice model.  By carrying queues over from one period to the next, the temporary over-loading of the network which characterises peak periods can be allowed for.  Steady state conditions are assumed within each period, so avoiding difficulties with FIFO.  An iterative balancing model fitting algorithm is presented and shown to be convergent. Sensitivity expressions for the primal and dual variables are formulated.  To avoid the need for a prior specification of paths, a column generation scheme is proposed.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481263</guid>
    </item>
    <item>
      <title>A FORMULATION AND SOLUTION ALGORITHM FOR A MULTI-CLASS DYNAMIC TRAFFIC ASSIGNMENT PROBLEM</title>
      <link>https://trid.trb.org/View/481264</link>
      <description><![CDATA[Dynamic traffic assignment (DTA) has been a topic of substantial research during the past decade.  While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution capabilities.  In order to model the impact of Advanced Transportation Management and Information Systems (ATMIS), especially route guidance and other information provision systems, it is necessary to develop a set of multi-class traffic models to acknowledge the fact that there are different classes of users of the transportation system, and that they respond differently to traffic information.  At least, the model should be able to differentiate travelers or vehicles who receive real-time traffic information versus those who don't.  This paper aims to advance the state-of-the-art in DTA modeling.  In this paper, an analytical approach is developed to model multiple classes of users of the transportation system.  It is a step forward of the long-term efforts in analytical DTA modeling, which distinguishes itself from simulation-based DTA models.  Specifically, the users are divided into three classes: (i) fixed route travelers; (ii) stochastic dynamic user-optimal (SDUO); (iii) dynamic user-optimal (DUO).  The property of each class is defined and integrated into one modeling framework through a Variational Inequality (VI) approach. Subsequently, a solution algorithm for the formulation is discussed. This algorithm uses a combination of various solution techniques, such as relaxation, Frank-Wolfe and Method of Successive Averages (MSA).  It is applied to four scenarios to verify the correctiveness of the solutions obtained.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481264</guid>
    </item>
    <item>
      <title>ASYMMETRIC MULTICLASS TRAFFIC ASSIGNMENT: A COHERENT FORMULATION</title>
      <link>https://trid.trb.org/View/481265</link>
      <description><![CDATA[Behavioural and mathematical problems in the current formulation of the asymmetric multiclass traffic assignment model are brought to light.  A new formulation is presented that resolves these difficulties.  The formulation is quantified, and the result is a general class of coherent, multiclass cost functions.  A numerical calibration exercise for a car and truck class model concludes the paper.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481265</guid>
    </item>
    <item>
      <title>BAYESIAN THEORY AND CLUSTER ANALYSIS IN THE IDENTIFICATION OF ROAD ACCIDENT BLACKSPOTS</title>
      <link>https://trid.trb.org/View/481266</link>
      <description><![CDATA[The paper presents a probabilistic model developed for the evaluation of the level of road sections safety.  Cluster analysis was used to determine the sections of a road that should be examined in order to identify blackspots among them.  To process this identification, Bayesian theory has been adopted.  It uses the general information about accident features distribution over all the sections as prior knowledge, and a piece of information about the features distribution specific to a certain section as posterior knowledge.  Each road section is then characterized by a certain weight value derived from the prior and the posterior knowledge.  This weight is then used as a basic value in the identification process, in which the section is or is not classified as a blackspot one.  The model was practically applied to accident data obtained from police reports.  The results of this application are presented in the last part of the paper.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481266</guid>
    </item>
    <item>
      <title>CHOOSING COMPARISON GROUPS FOR ROAD SAFETY COUNTERMEASURE EVALUATIONS</title>
      <link>https://trid.trb.org/View/481267</link>
      <description><![CDATA[A common approach for assessing the effect of a road safety countermeasure on a group of entities is to compare the accident experience on this treated group to the accident experience on a similar group of untreated entities (ie a comparison group).  The principal assumption behind this approach is the similarity between the treated group and the comparison group.  A major shortcoming of this approach is the lack of an objective method for assessing this similarity.  In this paper it is proposed that since the available data for assessing the similarity of two groups of entities is probabilistic in nature, the decision process for selecting a comparison group is fundamentally stochastic.  A stochastic approach for selecting the most appropriate comparison group is developed and its application illustrated with a numerical example.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481267</guid>
    </item>
    <item>
      <title>DEVELOPING A SET OF FUEL CONSUMPTION AND EMISSIONS MODELS FOR USE IN TRAFFIC NETWORK MODELLING</title>
      <link>https://trid.trb.org/View/481268</link>
      <description><![CDATA[This paper introduces the results of a research project on the pollutant emissions and fuel consumption characteristics of mixed traffic streams under different levels of congestion.  The project involved extensive testing of a number of vehicles, both on-road and in the laboratory, to determine their fuel consumption and emissions characteristics under different traffic conditions.  A set of models for different vehicle types were then assembled, based on the hierarchical family of models for fuel consumption presented by Biggs and Akcelik (1986), which was also capable of describing vehicle emission rates.  The model family consists of models at four levels, from an 'instantaneous' model for individual vehicles driven in traffic, through an 'elemental' model suitable for studies of intersection behaviour, a 'link' model suitable for transport network analysis, and a 'journey' model suitable for land use planning applications.  The models for individual vehicle types may be combined to yield models for the performance of a traffic stream. These models may then be incorporated into transport network analysis performance, as tools for use in the prediction of environmental and energy impacts of road transport projects.  One such integration of the models into a super-model (IMPAECT) for environmental impact analysis of transport planning decisions is described.  The focus is on the development and application of the energy and emissions models, which are made up of three sub-models: (1) traffic stream composition sub-models, to determine the emissions or fuel consumption of a traffic stream as an aggregate of the vehicles in that stream, (2) congestion functions, to relate travel conditions (delays, queuing and speed-time trajectories) to traffic flows on particular types of roads, and (3) sub-models of vehicle energy and emissions performance under different traffic conditions.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481268</guid>
    </item>
    <item>
      <title>MULTI SENSOR, MULTIVARIATE, AND MULTI-CLASS INCIDENT DETECTION SYSTEM FOR ARTERIAL STREETS</title>
      <link>https://trid.trb.org/View/481269</link>
      <description><![CDATA[A novel approach to incident detection on arterial streets that utilizes multi-sensor, multi-class, and multivariate classifiers to differentiate between various traffic states is proposed.  The similarities between the Bayes' fusion of multi-sensor allocations and Multiple Attribute Decision Making (MADM) are established.  An array of MADM algorithms is thus made available to the traffic engineer for purposes of fusion of multi-sensor allocations.  One such algorithm is applied to the detection of incidents on arterial streets using detector occupancies and vehicle counts by lane, probe travel times, and probe report numbers as attributes.  The probe data proves valuable in enhancing the performance of detector data based models.  Models based solely on probe data lack in performance, due to excessive overlaps in class distributions.  The possibilities for identifying incidents through their flow imbalance impacts, using multivariate detector classifiers, prove promising.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481269</guid>
    </item>
    <item>
      <title>STATIONARY STATES IN STOCHASTIC PROCESS MODELS OF TRAFFIC ASSIGNMENT: A MARKOV CHAIN MONTE CARLO APPROACH</title>
      <link>https://trid.trb.org/View/481270</link>
      <description><![CDATA[Traditional methods of traffic assignment are now widely perceived to have serious shortcomings, particularly in relation to the modelling requirements arising from increasingly saturated networks, complex traffic control and emerging driver information systems.  This has led to increased interest in more complex assignment models, including approaches incorporating stochastic elements to account for errors in drivers' perceptions and day-to-day variation in behaviour. However, whilst such newer, more complex models, have the scope to provide much greater realism, they are generally mathematically intractable.  Furthermore, empirical investigation of these models by direct simulation tends to be impossible if travellers interact in a contemporaneous fashion.  Nevertheless, simulation of such models is possible using statistical techniques known as Markov Chain Monte Carlo methods.  The objective of this paper is to demonstrate how existing stochastic process models can potentially be generalized to permit more complex and realistic representations of traveller memory and travller interactions, and to show how the equilibria of such models can be computed using Markov Chain Monte Carlo techniques. The properties of different types of stochastic assignment models are investigated both theoretically, and through small and medium scale empirical examples.  Avenues for further research in stochastic modelling of transport systems are discussed.  (A) For the covering abstract see IRRD 886400.]]></description>
      <pubDate>Mon, 24 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/481270</guid>
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