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Traffic simulations are valuable tools for urban mobility planning and operation, particularly in large cities. Simulation-based microscopic models have enabled traffic engineers to understand local transit and transport behaviors more deeply and manage urban mobility. However, for the simulations to be effective, the transport network and user behavior parameters must be calibrated to mirror real scenarios. In general, calibration is performed manually by traffic engineers who use their knowledge and experience to adjust the parameters of the simulator. Unfortunately, there is still no systematic and automatic process for calibrating traffic simulation networks, although some methods have been proposed in the literature. This study proposes a methodology that facilitates the calibration process, where an artificial neural network (ANN) is trained to learn the behavior of the transport network of interest. The ANN used is the Multi-Layer Perceptron (MLP), trained with back-propagation methods. Based on this learning procedure, the neural network can select the optimized values of the simulation parameters that best mimic the traffic conditions of interest. Experiments considered two microscopic models of traffic and two psychophysical models (Wiedemann 74 and Wiedemann 99). The microscopic traffic models are located in the metropolitan region of São Paulo, Brazil. Moreover, we tested the different configurations of the MLP (layers and numbers of neurons) as well as several variations of the backpropagation training method: Stochastic Gradient Descent (SGD), Adam, Adagrad, Adadelta, Adamax, and Nadam. The results of the experiments show that the proposed methodology is accurate and efficient, leading to calibration with a correlation coefficient greater than 0.8, when the calibrated parameters generate more visible effects on the road network, such as travel times, vehicle counts, and average speeds. For the psychophysical parameters, in the most simplified model (W74), the correlation coefficient was greater than 0.7. The advantage of using ANN for the automatic calibration of simulation parameters is that it allows traffic engineers to carry out comprehensive studies on a large number of future scenarios, such as at different times of the day, as well as on different days of the week and months of the year. [ABSTRACT FROM AUTHOR]

We study a 1D scalar conservation law whose non-local flux has a single spatial discontinuity. This model is intended to describe traffic flow on a road with rough conditions. We approximate the problem through an upwind-type numerical scheme and provide compactness estimates for the sequence of approximate solutions. Then, we prove the existence and the uniqueness of entropy weak solutions. Numerical simulations corroborate the theoretical results and the limit model as the kernel support tends to zero is numerically investigated. [ABSTRACT FROM AUTHOR]

A system to obtain vehicular energy‐use and emissions in transient traffic is proposed. It operates at a microscopic 1‐s time scale, capturing critical stop‐and‐go dynamics in a controlled and repeatable computational environment. This allowed the definition of a sensitivity function linking energy‐use to traffic flow, providing an additional comparison parameter. To obtain the dynamics data, crucial for transient traffic modeling implementation and validation, a video‐tracking technique is used to overcome velocimeter and GPS data shortcomings. This approach allowed to observe and reproduce a traffic scene and agreed with a M/D/n queuing traffic model. Once the system contains precise dynamics, it can be implemented for traffic scenarios such as intersections, school areas, or future road projects. Any simulated vehicular technology can be incorporated into the analysis. A case study was implemented using 1000 electric (EV) and combustion engine vehicles (CV) interacting with trucks, buses, and motorcycles, while monitoring individual vehicular systems. These included the powertrain and regenerative braking to obtain energy‐use and emissions. EVs proved to be not only more efficient, but less sensitive to traffic buildup than CVs. The techniques presented here, lend themselves to technological design and evaluation and allows testing real‐life vehicular systems for sustainable traffic and energy planning. [ABSTRACT FROM AUTHOR]

We focus on entropy admissible solutions of scalar conservation laws in one space dimension and establish new regularity results with respect to time. First, we assume that the flux function f is strictly convex and show that, for every x ∈ ℝ, the total variation of the composite function f ο u(∙, x) is controlled by the total variation of the initial datum. Next, we assume that f is monotone and, under no convexity assumption, we show that, for every x, the total variation of the left and the right trace u(∙,x±) is controlled by the total variation of the initial datum. We also exhibit a counterexample showing that in the first result the total variation bound does not extend to the function u, or equivalently that in the second result we cannot drop the monotonicity assumption. We then discuss applications to a source-destination model for traffic flows on road networks. We introduce a new approach, based on the analysis of transport equations with irregular coefficients, and, under the assumption that the network only contains so-called T-junctions, we establish existence and uniqueness results for merely bounded data in the class of solutions where the traffic is not congested. Our assumptions on the network and the traffic congestion are basically necessary to obtain well-posedness in view of a counterexample due to Bressan and Yu. We also establish stability and propagation of BV regularity, and this is again interesting in view of recent counterexamples. [ABSTRACT FROM AUTHOR]

In this paper, we derive second order hydrodynamic traffic models from kinetic-controlled equations for driver-assist vehicles. At the vehicle level we take into account two main control strategies synthesising the action of adaptive cruise controls and cooperative adaptive cruise controls. The resulting macroscopic dynamics fulfil the anisotropy condition introduced in the celebrated Aw–Rascle–Zhang model. Unlike other models based on heuristic arguments, our approach unveils the main physical aspects behind frequently used hydrodynamic traffic models and justifies the structure of the resulting macroscopic equations incorporating driver-assist vehicles. Numerical insights show that the presence of driver-assist vehicles produces an aggregate homogenisation of the mean flow speed, which may also be steered towards a suitable desired speed in such a way that optimal flows and traffic stabilisation are reached. [ABSTRACT FROM AUTHOR]

A signalized intersection regulated by pre-timed control in an urban traffic network is considered. A method for computing the mean delay of vehicles based on the theory of queues with server vacations is adapted from the existing literature and an algorithm for numerical implementation is proposed. Arrivals are assumed to occur according to a batch Markovian arrival process (BMAP). The proposed algorithm is an alternative to the previous methods that includes a numerical improvement in the computation of the queue invariant probabilities. In the case of isolated intersections we compare the new algorithm with other traffic models, including simulation model, Webster model and the Highway Capacity Manual model. The mean delay of vehicles given by the new algorithm is a short distance away from the mean delay obtained in the simulations. The approximation for large flows given by the proposed algorithm is as good as the Highway Capacity Manual model and with no need to tune unknown parameters. Our results are of interest for traffic engineers, since other approaches have been subject to criticism when flows near capacity are involved. [ABSTRACT FROM AUTHOR]

A dynamical system is studied. This system belongs to the class of contour networks introduced by A.P. Buslaev. The system is a version of the system called an open chain of contours. Continuous and discrete versions of the system were considered earlier. The system contains N contours. There is one adjacent contour for the utmost left and the utmost right contour, and there are two adjacent contours for any other contour. There is a common point of any two adjacent contours. This point is called a node. There is a cluster in each contour. For the continuous version, the cluster is a segment, moving with constant velocity if there is no delay. For the discrete version, the cluster is a group of adjacent particles. Delays are due to that two clusters may not move through the same node simultaneously. The main system characteristic, studied earlier, is the average velocity of clusters. In this paper, the continious and discrete version of the open chain of contours are considered. The following version of the system is also considered. Each cluster is a segment, and the cluster is shifted onto the distance α at any discrete moment if no delay occurs. We have obtained the limit distribution of the system states. We have also obtained the limit state distribution (invariant measure) for the open chain of contours with continuous state space and continuos time and for the open chain of contours with discrete state space and discrete time. [ABSTRACT FROM AUTHOR]

This paper develops Lárraga and Alvarez-Icaza (LAI) cellular automata model which is based on safe human reaction. Vehicles are moving at two single-lane streets with periodic boundary condition and pass from intersection point via yielding mechanism avoiding collision. The model characteristics and fundamental diagrams have been obtained by Monte Carlo simulations. Our results suggest that LAI model with yielding mechanism is able to reproduce the realistic acceleration and deceleration capabilities, which are desired parameters. Moreover, the plateau region in total current illustrates the hardness of the yielding mechanism and limited speed strategy, which is applied near the intersection point. [ABSTRACT FROM AUTHOR]

We consider a one-dimensional traffic model with a slow-to-start rule. The initial position of the cars in R is a Poisson process of parameter λ . Cars have speed 0 or 1 and travel in the same direction. At time zero the speed of all cars is 0; each car waits a mean-one exponential time to switch speed from 0 to 1 and stops when it collides with a stopped car. When the car is no longer blocked, it waits a new exponential time to assume speed one, and so on. We study the saturated regime λ > 1 and the critical regime λ = 1 , showing that in both regimes all cars collide infinitely often and each car has asymptotic mean velocity 1 / λ . In the saturated regime the moving cars form a point process whose intensity tends to 1. The remaining cars condensate in a set of points whose intensity tends to zero as 1 / t . We study the scaling limit of the traffic jam evolution in terms of a collection of coalescing Brownian motions. [ABSTRACT FROM AUTHOR]

Non-commercial Land Ports of Entry (LPOEs) are unique transportation facilities controlling the ingress and egress of passenger vehicles from Mexico to the United States and vice versa. The calibration of microscopic traffic simulation models of non-commercial LPOEs requires a deep understanding of operational processes and driving behavior at these facilities. This paper provides a methodology to guide modelers in calibrating microscopic traffic simulation models of non-commercial LPOEs. The methodology establishes a common framework for modeling operational processes and traffic operations. Moreover, the methodology includes the value of four state variables that characterizes operations of passenger vehicles at non-commercial LPOEs. These variables are speed, acceleration, deceleration, and headway. The authors evaluated this methodology using the Otay Mesa non-commercial LPOE as a case study. Results showed that this methodology could be potentially used to model non-commercial LPOEs along the US–Mexico border and other border regions worldwide. [ABSTRACT FROM AUTHOR]

We study the derivation of second order macroscopic traffic models from kinetic descriptions. In particular, we recover the celebrated Aw–Rascle model as the hydrodynamic limit of an Enskog-type kinetic equation out of a precise characterisation of the microscopic binary interactions among the vehicles. Unlike other derivations available in the literature, our approach unveils the multiscale physics behind the Aw–Rascle model. This further allows us to generalise it to a new class of second order macroscopic models complying with the Aw–Rascle consistency condition, namely the fact that no wave should travel faster than the mean traffic flow. [ABSTRACT FROM AUTHOR]

Traffic management on highways may be upgraded on the basis of new equipment and more powerful information technologies, such as cloud resources and storage. However, deficiencies are evident in mathematical models of traffic behavior with stochastic speed and lane changes on multilane highways. The proposed model of traffic takes account of several types of vehicles, differing in speed and size. The model parameters may be adjusted on the basis of measurements of the traffic flow from highway-based sensors. [ABSTRACT FROM AUTHOR]

The paper proposes a general framework to analyze control problems for conservation law models on a network. Namely, we consider a general class of junction distribution controls and inflow controls and we establish the compactness in L¹ of a class of flux-traces of solutions. We then derive the existence of solutions for two optimization problems: (I) the maximization of an integral functional depending on the flux-traces of solutions evaluated at points of the incoming and outgoing edges; (II) the minimization of the total variation of the optimal solutions of problem (I). Finally we provide an equivalent variational formulation of the min-max problem (II) and we discuss some numerical simulations for a junction with two incoming and two outgoing edges. [ABSTRACT FROM AUTHOR]

Simulation is one of the most powerful tools we have for evaluating the performance of opportunistic networks (OppNets). In this paper, we focus on available tools and models, compare their performance and precision and experimentally show the scalability of different simulators. We also perform a gap analysis of state-of-the-art OppNet simulations and sketch out possible further development and lines of research. This paper is targeted at students starting work and research in this area while also serving as a valuable source of information for experienced researchers. [ABSTRACT FROM AUTHOR]

In this study, we propose a novel method for a travel path inference problem from sparse GPS trajectory data. This problem involves localization of GPS samples on a road network and reconstruction of the path that a driver might have been following from a low rate of sampled GPS observations. Particularly, we model travel path inference as an optimization problem in both the spatial and temporal domains and propose a novel hybrid hidden Markov model (HMM) that uses a uniform cost search (UCS)-like novel combinational algorithm. We provide the following improvements over the previous studies that use HMM-based methods: (1) for travel path inference between matched GPS positions, the proposed hybrid HMM algorithm evaluates all candidate paths to find the most likely path for both the temporal and spatial domains. In contrast, previous studies either create interpolated trajectories or connect matched GPS positions using the shortest path assumption, which might not be true, especially in urban road networks (Goh et al. 2012; Lou et al. 2009). (2) The proposed algorithm uses legal speed limits for the evaluation of discrepancy in the temporal domain as in Goh et al. (2012), and Lou et al. (2009) only if there is not sufficient historical average speed data; otherwise, we use historical average speed computed from data. Our experiments with real datasets show that our algorithm performs better than the state of the art VTrack algorithm (Thiagarajan et al. 2009), especially for cases where GPS data is sampled infrequently. [ABSTRACT FROM AUTHOR]

A queuing system resulting from a signalized intersection regulated by pretimed control in a network of urban traffic is considered. Modeling the queue length and the delay of vehicles is crucial to evaluate the performance of intersections equipped with traffic signals. Air quality and rational use of energy also depend on an efficient management of the intersections. These traffic systems have the specificity that the server (green signal) is deactivated (red signal) during a fixed period of time. In the present work, an M/ D/1 queue with a server that occasionally takes vacations is analyzed. The mean delays of vehicles and the mean queue length are computed and compared with those obtained by using a detailed simulation model in a case study. We find that, in general, the mean delays of vehicles given by the proposed queuing model provide a good approximation, but the model can provide slightly smaller values than those obtained in the simulation model for large traffic flows. This result is of interest for traffic engineers, as the approaches one can find in the literature for large signalized urban traffic flows are subject to criticism. [ABSTRACT FROM AUTHOR]

We couple, at a fixed interface, the microscopic Follow the Leader model and the macroscopic Lighthill–Whitham–Richards model, both used for describing vehicular traffic. The coupling is obtained by suitable boundary conditions. We prove existence of solutions for the corresponding Cauchy problem, by using the wave-front tracking method and classical results on ordinary differential equations. [ABSTRACT FROM AUTHOR]

Called to seek fresh thinking in mobility management, European cities present strong interest in parking management. In contrast with traditional approaches where parking problem was treated as a problem of inadequate supply whose solution lies on abundant, free and on a first-come basis parking provision, the rational of parking management is conscripted so as to combat traffic and environmental problems. At the new parking approach, parking policy should respect particular needs of each area and should apply in a flexible way so as to serve an integrated development plan. At this framework, the current paper examines Thessaloniki's case, Greece, that presents severe traffic problems. The paper tries to evaluate the impacts on traffic and environmental indicators of the implementation of a controlled parking system. The results verify that when a parking system becomes controlled and a strong enforcement mechanism applies, the modal split changes in favor of public transport. [ABSTRACT FROM AUTHOR]

The era of autonomous vehicles infer new challenges in several fields. When autonomous vehicles take over the road in a large volume, consumer preferences around car-ownership will transform, traffic modeling and control will need correction, and moreover hackers will appear. These are just a few impacts which are expectable in the near future. Accordingly, the paper's aim is to enlighten trends and upcoming challenges of driverless vehicles and automated transportation system from a transportation engineering perspective. [ABSTRACT FROM AUTHOR]

Calibration and validation of traffic models is a necessary step to better fit model output to real-world conditions. Presently, there has been little research in this particular area of evacuation modeling because of a lack of observed traffic data from evacuation events. This paper provides a general framework for the calibration and validation of regional-scale evacuation models. The authors then present a case study in which calibration and validation is carried out for an evacuation model using observed evacuation data. The case study presents a traffic simulation model that was developed to analyze traffic conditions associated with a regional-level mass emergency evacuation for southeastern Louisiana, including New Orleans and Baton Rouge. The case study focuses on two important aspects of the model: traffic assignment calibration and network flow validation. The calibration procedure attempted to determine parameter values that would result in the most realistic traffic assignment by comparing assignment results with real-world traffic flows. The validation procedure revealed the importance of including background traffic in the simulation model. [ABSTRACT FROM AUTHOR]

Because of the need of introducing ecologically clean transport technologies, activities bound up with using electric propulsion in motor vehicles operating in public transport are undertaken. Technical and operational possibilities of introducing electric-powered buses to the communal public transport are shown in the article. The operation of that kind of fleet requires appropriate technical infrastructure involving charging electric-powered urban transport. Simultaneously, former experiences show strong mutual connection between technical sphere and organizational system of communal public transport in agglomerations. Hence, essential significance among other things is given to the layout of the functioning bus lines network and the organisation of bus operations on the lines (timetable). The models of the technical, organizational, economical and ecological links enabling optimal choice of type of bus propulsion were worked out, with the aim of solving this problem rationally. [ABSTRACT FROM AUTHOR]

In this article, a new approach concerning two stages of the creaming phenomena in emulsions, not distinguished in the literature, is presented. The continuity theory and the equation of motion taken from the traffic engineering were used to describe the changes in the medium that is discontinuous at microscopic level. In the modeling work, the experimental data obtained by the nephelometric measurements were used. It gave a real insight into the actual processes taking place during the phenomena of creaming in comparison to the classical methods. [ABSTRACT FROM PUBLISHER]

Statistical mechanics points out as fluctuations have a relevant role for systems near critical points. We study the effect of traffic fluctuations and the transition to congested states for a stochastic dynamical model of traffic on a road network. The model simulates a finite population that moves from one road to another according to random transition probabilities. In such a way, we mimic the traffic fluctuations due to the granular feature of traffic and the dynamics at the crossing points. Then the amplitude of traffic flow fluctuations is proportional to the average flow as suggested by empirical observations. Assuming a parabolic shaped flow-density relation, there exists an unstable critical point for the road dynamics and the system can perform a phase transition to a congested state, where some roads reach their maximal capacity. We apply a statistical physics approach to study the onset congestion and we characterize analytically the relation between the fluctuations amplitude and the appearance of congested nodes. We verify the results by means of numerical simulations on a Manhattan-like road network. Moreover we point out the existence of oscillating regimes, where traffic oscillations back propagate on the road network, whose onset depend sensitively from the traffic fluctuations and that have a strong influence on the hysteresis cycles of the systems when the traffic load is modulated. The comparison between the numerical simulations and the empirical traffic data recorded by an inductive-loop traffic detector system (MTS system) on the county roads of the Emilia Romagna region in Italy is shortly discussed. [ABSTRACT FROM AUTHOR]

We review numerical and analytical results that have been obtained for a general model of intersecting flows of two types of particles propagating towards east (ε) and north (N) on a bidimensional M x M square lattice. The behaviour of this model can also be reproduced by a system of mean field equations. The low density behaviour of both models is studied, with a focus on pattern formation. Using periodic boundary conditions, particles self-organize into a pattern of alternating diagonal stripes, which corresponds to an instability in the mean-field equations. With open boundary conditions, translational symmetry is broken. One then observes an asymmetry between the organization of the two types of particles, leading to tilted diagonals whose angle of inclination differs from 45 °, both for the particle system and the equations. The angle of inclination of the stripes is measured using two different numerical methods. Finally, simplified theoretical arguments based on a particular mode of propagation give a quantitative estimate for the angle of the stripes. A complementary understanding of the phenomenon in terms of effective interactions between particles is presented. [ABSTRACT FROM AUTHOR]

We present two frameworks for the description of traffic, both consisting in the coupling of systems of different types. First, we consider the Free-Congested model [7, 11], where a scalar conservation law is coupled with a 2 x 2 system. Then, we present the coupling of a micro- and a macroscopic models, the former consisting in a system of ordinary differential equations and the latter in the usual LWR conservation law, see [10]. A comparison between the two different frameworks is also provided. [ABSTRACT FROM AUTHOR]

Copyright of Obras y Proyectos is the property of Universidad Catolica de la Santisima Concepcion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently traffic management is becoming more important to achieve the goal of sustainable transport, and a good traffic model can describe the traffic behavior efficiently. The traffic models can be classified based on level of details as submicroscopic-, microscopic-, mesoscopic-, and macroscopic-level models. In this paper, we provide a review of the four types of models (submicro, micro, meso, and macro) and then propose a multilevel model of traffic, which combines submicroscopic, microscopic, and macroscopic levels of traffic model. In this work, we do not consider the mesoscopic-level model. At the submicroscopic level, we develop a bond graph model of a four-wheeled vehicle considering the longitudinal, lateral, yaw, and actuator dynamics. At the microscopic level, we develop a car-following model based on virtual interconnections between the submicroscopic bond graph models of vehicles. Then, at the macroscopic level, we deduce macroscopic variables (average speed, density, and flow) from the submicroscopic and microscopic models. Having a multilevel model of traffic allows combining two properties of modeling simulation, one in real-time mode at microscopic and submicroscopic levels and the other at offline mode at macroscopic level. Thus, the whole supervision of the road traffic can be performed. Finally, the multilevel model of traffic is validated on a real-time simulator of vehicle dynamics, based on experimental measurements acquired from intelligent autonomous vehicles (IAVs). In addition, real experiments on IAVs are performed to validate the model. [ABSTRACT FROM PUBLISHER]

This paper presents a new model for VoIP workload generation. The novelty of our proposal consists in modeling the sessions by characterizing both the user behavior (session level) and the packet generation for an active call (intra-session level) with easily measured parameters and low computational complexity. This approach also facilitates systematic study of changes in user behavior and voice codec. The session level was modeled by analysis of call-holding time and time interval between successive calls. The model for call-holding time, characterizing the individual user behavior, uses the Pareto type 2 probability distribution. The time interval between calls is obtained from aggregate traffic and can be modeled by exponential probability distribution. Aggregate traffic is obtained by superposition of simultaneous sessions. The data used to characterize the session level were collected at the backbone of two Brazilian telecommunication carriers. The model for intra-session level comprises the characterization of the packet size and the packet inter-arrival time. The intra-session model was based on data generated in a laboratory environment, in order to properly characterize the codec influence on packet generation and to avoid the effects of delay, jitter and loss commonly present in an operational network. Models for constant bit rate and variable bit rate codecs were considered. A simulator was implemented and the results indicate that our model properly mimics the characteristics observed in real traffic and can be used for VoIP modeling and workload generation. Additionally, an application to automate the performance analysis was developed. [ABSTRACT FROM AUTHOR]

In this paper, a computer system named Advanced Emulator (AE), which is developed for simulation of traffic models, is presented. Unlike traditional transportation programs such as PARAMICS and VISSIM, AE has no built-in concrete traffic models. Instead, AE implements a specialized scripting language, the AE language, through which researchers write scripts defining logic of concrete traffic models to be simulated by themselves, and a runtime virtual machine, the AE virtual machine, which interpret and execute scripts written in the AE language to fulfill simulation. Thus, AE provides researchers a platform on which they can build customized simulation packages for various traffic models from the ground up. Using AE, researchers can virtually simulate any traffic model from car following and lane changing to ramp metering. Therefore, AE could be a useful tool in research fields of traffic model comparison, prototyping, and validation. [ABSTRACT FROM AUTHOR]

This paper points out questionable derivations for the formulated solution in the algebraic approach for the optimal length of local bus route of a traffic model for bus service zones. It also provides revisions for the algebraic approach to prove the existence and uniqueness for the formulated optimal solution. An iterative method was then applied to obtain an alternative sequence that converges to the optimal solution. The same numerical examples in the literature are examined to support the findings. [ABSTRACT FROM AUTHOR]

The past 20 years have seen significant improvements in the way regional mass evacuations are carried out in the United States. Today's use of phased evacuation orders, contraflow, and citizen-assisted transit evacuations have come about as lessons learned from previous evacuations and have led to improvements in later ones. This paper summarizes a study to examine what may be a future step in this improvement process: the concept of flexible evacuation responses to major catastrophic hazards. Within this idea, evacuation plans would be developed in which the timing, direction of movement, and regional traffic-management plans would be changed based on the characteristics (e.g., strength, speed, movement, etc.) of a particular threat. This study was carried out using an integrated model that combines a calibrated evacuation demand model with a calibrated microscopic simulation model to evaluate a set of flexible evacuation plans for four theoretical hurricane conditions. The experimental results showed that even simple alterations to a single, static, one-size-fits-all-scenarios plan had significant benefits to the movement of traffic. In addition, such improvements could provide over $400,000 in fuel savings over the existing static plan. Whereas this research was based on evacuation from a hurricane, it is expected that similar results could be attained for evacuations from other threats. [ABSTRACT FROM AUTHOR]

Copyright of Tecnura is the property of Tecnura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In computer networks, network traffic measurement is the process of measuring the amount and type of traffic on a particular network. This is especially important with regard to effective bandwidth management. Hence more sophisticated network traffic monitoring and analysis tools are in need in order to maintain the network system stability and to fix network problems on time or to avoid network failure. Considering this need we propose Field programmable gate array (FPGA) architecture for network flow analysis. A decision tree algorithm is also proposed for flow classification. The designed architecture is tested against various real time traffic models created using probability distribution technique. The performance evaluation of this architecture proves that it support the network traffic stream at multi giga bit rate which is better than most of the existing software techniques. [ABSTRACT FROM AUTHOR]

This paper establishes a mathematical model that can represent the conflicting effects of two pedestrian streams that have an oblique intersecting angle in a large crowd. In a previous paper, a controlled experiment in which two streams of pedestrians were asked to walk in designated directions was used to model the bidirectional pedestrian stream of certain intersecting angles. In this paper, the writers revisit that problem and apply the Bayesian inference method to calibrate an improved model with the controlled experiment data. Pedestrian movement data are also collected from a busy crosswalk by using a video observation approach. The two sets of data are used separately to calibrate the proposed model. With the calibrated model, the relationship between speed, density, and flow is studied in both the reference and conflicting streams, and a prediction is made regarding how these factors affected the interactions of moving pedestrian streams. It is found that the speed of one stream not only decreases with its total density, but also decreases with the ratio of its flow relative to the total flow, i.e., the speed of the pedestrians decreases if their stream changes from the major to minor stream. It is also observed that the maximum disruption that was induced by pedestrian flow from an intersecting angle occurs when the angle is approximately 135°. [ABSTRACT FROM AUTHOR]

Application of microscopic traffic simulation beyond the corridor level analysis is not widely seen in literature. This is partly because of the fact that a simulation model cannot capture behavior responses such as peak spreading. This study develops a framework that integrates agent-based travel behavior models with large-scale traffic simulation to capture the regional impacts of new development. The proposed model is then applied to the I-270/I-495/I-95 corridor in the north Washington, DC metropolitan area in a case study. Findings from this study reveal the potential of the proposed model to capture network dynamics and behavioral reactions. This framework also provides a valuable tool for the evaluation of new transportation infrastructure, such as the intercounty connector (ICC) corridor currently under construction, and its operation strategies. [ABSTRACT FROM AUTHOR]

Urban traffic systems that possess system states that are distributed, parallel, deterministic, stochastic, discrete, and continuous are well suited for a Petri net (PN) approach. The literature survey conducted in this paper shows the vast applications of PNs in modeling and simulation, analyzing and evaluating performances, intelligent control and optimization, and congestion management in urban traffic systems. This paper outlines the related works conducted using PNs and discusses its viability, such as its contributions and limitations. Extendibility and future research potential to further the successful applications of PNs in traffic systems are discussed and proposed in this paper. [ABSTRACT FROM PUBLISHER]

A toll-lane selection process at a toll plaza can be looked at as an outcome of the choice processes of individual drivers. In this paper, an attempt is made to develop a random utility-based discrete multinomial choice model for the behavior of automobile drivers while selecting toll lanes at a toll plaza. Specifically, a multinomial logit model is developed and calibrated using disaggregate level choice data from three toll plazas with different geometry and rates of arrival of vehicles. The calibrated logit models from the different sites when statistically compared show that a generic model, applicable to all the sites, is possible. Such a generic model is also developed. The use of the proposed model can improve the analysis of traffic flow at toll plazas and ultimately lead to more effective designs of these facilities. [ABSTRACT FROM AUTHOR]

Traffic flow forecasting, especially the short-term case, is an important topic in intelligent transportation systems (ITS). This paper researches network-scale modeling and forecasting of short-term traffic flows. First, the concepts of single-link and multilink models of traffic flow forecasting are proposed. Secondly, four prediction models are constructed by combining the two models with single-task learning (STL) and multitask learning (MTL). The combination of the multilink model and multitask learning not only improves the experimental efficiency but also improves the prediction accuracy. Moreover, a new multilink, single-task approach that combines graphical lasso (GL) with neural network (NN) is proposed. GL provides a general methodology for solving problems involving lots of variables. Using L1 regularization, GL builds a sparse graphical model, making use of the sparse inverse covariance matrix. Gaussian process regression (GPR) is a classic regression algorithm in Bayesian machine learning. Although there is wide research on GPR, there are few applications of GPR in traffic flow forecasting. In this paper, GPR is applied to traffic flow forecasting, and its potential is shown. Through sufficient experiments, all of the proposed approaches are compared, and an overall assessment is made. [ABSTRACT FROM AUTHOR]

Until recently, the Poisson process has been used to model internet and road traffic queues. It has been established that internet traffic exhibits self-similarity, which is very different from the Poisson process. Motivated by this, efforts have been made to examine whether road traffic is also self-similar. Earlier efforts in this direction indicate that road traffic is indeed self-similar. To substantiate this, this paper examines, by various methods, whether real time traffic on a busy national highway in India is self-similar. The results from this examination prove that the traffic observed on the highway is self-similar. This paper also presents a novel method based on percentiles for computing the Hurst parameter, which is an indicator for the intensity of self-similarity. The paper also validates the percentile method with two other existing methods. Additionally, the traffic at a toll plaza on the highway has been modelled as queueing system, and performance measures have also been computed, namely, mean queue length and busy period distribution. The numerical results clearly demonstrate that the analysis presented in this paper can be useful for improved designs of toll plazas. [ABSTRACT FROM AUTHOR]

Although auxiliary through lanes (ATLs) are often used to increase the capacity at signalized intersections, their utilization by motorists tends to be significantly lower than continuous through lanes (CTLs). This study was designed to (1) determine whether recently proposed models for predicting lane-drop utilization are applicable to Buffalo, New York; (2) develop new models for predicting ATL utilization and for predicting drivers' merge behavior at ATLs; and (3) assess the ability of microscopic traffic simulation models to reproduce observed merging behavior. To achieve this, geometric, traffic count, and merge data were collected from select sites in Buffalo. The study shows that lane utilization in Buffalo is a function of total through-traffic volume, right-turning volume, and upstream and downstream land-use types. The average merge distance, in contrast, tends to be a function of the ATL total length, the first lane-drop warning sign, the speed limit, and the total through-traffic volume. The study also identified the challenges of calibrating merge behavior in microscopic traffic simulation models against field observations. [ABSTRACT FROM AUTHOR]

Traffic flows around roundabouts have been found to be dependent on origin-destination flows, but the true nature of this relationship is not properly understood. Present analyses are based on either gap acceptance models or empirical models. These models do not properly account for the impact of origin-destination flows on roundabout operations. This has limited the possibility to develop strategies that improve roundabout operations by controlling inflows. This research proposes a theory to analyze roundabout traffic flows and a strategy to determine inflows into a roundabout that would maximize the outflow from the roundabout. This strategy could be implemented through use of signals to meter vehicles at the entry. To achieve this, a theoretical framework is proposed based on the macroscopic fundamental diagram for urban networks. The theory and strategy is then tested using microscopic simulation. It was found that the outflow from a roundabout is dependent on the average flow and the average trip length around the roundabout. The average trip length is a function of the origin-destination flows. [ABSTRACT FROM AUTHOR]

Although the phenomenon of induced traffic has been theorized for more than 60 years and is now widely accepted among transport researchers, the traffic-generating effects of road capacity expansion are still often neglected in transport modelling. Such omission can lead to serious bias in the assessments of environmental impacts as well as the economic viability of proposed road projects, especially in situations where there is a latent demand for more road capacity. This has been illustrated in the present paper by an assessment of travel time savings, environmental impacts and the economic performance of a proposed road project in Copenhagen with and without short-term induced traffic included in the transport model. The available transport model was not able to include long-term induced traffic resulting from changes in land use and in the level of service of public transport. Even though the model calculations included only a part of the induced traffic, the difference in cost-benefit results compared to the model excluding all induced traffic was substantial. The results show lower travel time savings, more adverse environmental impacts and a considerably lower benefit-cost ratio when induced traffic is partly accounted for than when it is ignored. By exaggerating the economic benefits of road capacity increase and underestimating its negative effects, omission of induced traffic can result in over-allocation of public money on road construction and correspondingly less focus on other ways of dealing with congestion and environmental problems in urban areas. [ABSTRACT FROM AUTHOR]

We study reconfigurations of wavelength-routed Wavelength Division Multiplexing (WDM) networks in response to lightpath demand changes, with the objective of servicing more lightpath demands without additional network resources from a long-term network operation point of view. For the reconfiguration problem under study, we assume WDM network operators are provided with lightpath demands in batches. With limited network resources, our problem has two unique challenges: balancing network resource allocations between current and future lightpath demands, and modeling future lightpath demands. The first challenge implies making tradeoffs between accepting as many current immediate lightpath demands as possible and reserving a certain amount of network resources for near future predicted lightpath demands. The second challenge implies modeling future predicted lightpath demands, which are not exactly known or certain as the current lightpath demands. Our proposed model allows a natural separation between the operation of the optical layer and the user traffic layer (predominantly the IP-layer), while supporting their interactions, for which we propose a new formulation for per-link congestion control, associated with a mathematical solution procedure. Our simulation results reveal that by properly controlling resource allocations in the current session using our proposed mechanism, rejections in future sessions are greatly reduced. [ABSTRACT FROM AUTHOR]

RNA polymerases transcribe the genetic information from DNA to RNA. They move along the DNA by stochastic single-nucleotide steps that are interrupted by pauses. Here we use a variant of driven lattice gas models or exclusion processes to study the effects of these pauses under conditions, where many RNA polymerases transcribe the same gene. We consider elemental pauses, where RNA polymerases are inactive and immobile, and backtracking pauses, during which RNA polymerases translocate backwards in a diffusive fashion. Under single-molecule conditions, backtracking can lead to complex dynamics due to a power-law distribution of the pause durations. Under conditions of dense RNA polymerase traffic, as in the highly transcribed genes coding for ribosomal RNA and transfer RNA, backtracking pauses are strongly suppressed because the trailing active RNA polymerase restricts the space available for backward translocation and ratchets the leading backtracked RNA polymerase forward. We characterize this effect quantitatively using extensive computer simulations. Furthermore, we show that such suppression of pauses may have a regulatory role and lead to highly cooperative control functions when coupled to transcription termination. [ABSTRACT FROM AUTHOR]