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The article discusses the major differences in articles which investigated the application of wavelet networks in traffic volume forecasting. First is the focus of research on the use of wavelet networks for the prediction of short-term traffic flow data. Second, the wavelet networks are different. Third, the performance of wavelet networks is compared with the performance of popular neural network models.

The article presents views and insights of the author regarding the mathematical analysis on the flow of traffic through a toll plaza. Significantly, one of the problems posed in the examination of traffic flow has been the poor management and design of the roadway and the toll collection system. Furthermore, the nature of a toll plaza is that multiple lanes expand into even more lanes into which people can change if they feel it is disadvantageous. The author provided an overview of the kinds of solutions that were submitted as well as the highlights of the judging process itself and the challenges that the particular problem represented to the judges. Finally, some tips and advisories were provided in reaction to some to various issues.

This paper attempts to apply both global and local sensitivity analyses (SA) to fully test the integrated activity-based model (ABM) within several experiments based on a Chinese medium-sized city, Baoding. MATSim (Multi-agent Transport Simulation) that is a typical integrated ABM is used as an example for the SA. The global SA, which is based on the elementary effect method, is firstly applied to identify the influential parameters. Then the once-at-a-time (OAT)-based Local SA is employed to further reveal the relationship between the influential parameters and the outputs of interest, such as traffic flow. The SA results show the extent to which and how three influential MATSim parameters (population scaling factor, the number of iterations and time step size) influence the outputs of interest. In addition, the SA results of MATSim suggest that the parameters of time mutation rate and performing utility can heavily influence the outputs of interest and properly setting them can optimize the daily plans of agents. Finally, this paper concludes with suggestions on how to wisely use the SA findings for both MATSim and other ABM users. [ABSTRACT FROM AUTHOR]

One of the main characteristics of a Vehicular Ad-hoc Networks (VANET) is high mobility. Therefore, the high overhead and end-to-end delay are natural results. The prediction of future movements for vehicles provides traffic observations to improve and enhance the network performance and to serve the VANET applications. The clustering approach is a popular technique used in most studies to deal with the network's dynamic topology. In most studies, the clustering algorithms are tested and evaluated according to the cluster head (CH) selection approach. Selecting a suitable CH will lead to the prolonging of the cluster lifetime. A long life time represents an indication for cluster stability, also known as cluster maintenance. Cluster maintenance has got less consideration by the previous VANET studies. The stability prediction represents a challenging task in the clustering approach. This paper highlights the stability prediction in the VANET's Highway scenario. It proposes a new approach to evaluate the vehicle's cluster stability prediction by utilizing the stochastic process. The modeling of joining and leaving takes place using the birth-death process as a stochastic process for evaluating the stability of the clustering algorithm. The main advantage of this approach is to predict and evaluate the vehicle cluster stability with time, using a new mathematical model. [ABSTRACT FROM AUTHOR]

This paper is devoted to the mathematical modeling of traffic flow in a large automobile network. A statistical model of traffic flow proposed by the authors and designed for full-scale modeling of the operation of large-scale transport systems on long time intervals is used. A model has been constructed for one of the sides of the Moscow Ring Road and experiments have been carried out for two ways of jamming on the highway. The functionality of the naive entry control model has been tested in both types of the experiments. It has been shown that even the simplest method of limiting the incoming flow is efficient in terms of highway travel time losses. [ABSTRACT FROM AUTHOR]

In industrial applications, many systems present serious productivity problems due to limited resources. Generally, the dynamics of resource allocation are inherently discrete-event driven, such as the buffer allocation in production line systems. In this paper, we develop a discrete-event mathematical model for resource allocation optimization. In this work, we consider two crucial optimization objectives, e.g., deadlock-free and efficiency, that originate from the customer's actual requirements. The main aim is to develop a resource allocation scheme for fulfilling the production process (without deadlock) while ensuring that the cost of the process is minimized. As a case study, we consider the vehicle scheduling problem in a signal-free intersection. The intersection is divided into several disjoint spatial traffic resources, and vehicles need to occupy different traffic resources for passing through the intersection. Thus, the traffic control problem at the signal-free intersection is transformed into a scheduling problem with limited resource constraints. An online control approach is developed to schedule vehicles to go through the intersection safely and efficiently by optimizing the resource allocation order. Simulation results demonstrate the efficiency and robustness of the proposed model and optimization approach. [ABSTRACT FROM AUTHOR]

This paper examines the problem of determining the relation of variables and deterministic parameters of the optimum solution space for bus service zones within an urban transit model, due to the ever-evolving need for an efficient and effective transit system in modern society. A positive solution for the length of a local bus service zone was proposed and proven. Moreover, the Newton method was applied to derive a convergent sequence faster than the alternate sequence proposed in a previous paper. This analytic model will help transportation operators determine the optimum dimensions of bus service zones with great accuracy and will influence other tasks such as budget allocation. [ABSTRACT FROM AUTHOR]

In this paper, we propose enhanced fundamental diagrams based on different water film depths by considering the effects of hydroplaning using a physical method. Various factors are calculated to describe the total safe distance headway of main vehicle components. These factors include the driver reaction times, reaction distances, vehicle braking times, and vehicle braking distances corresponding to different water film depths. An excellent match is found between the computed braking distance, the braking time calculated using the proposed numerical model, and the results published in other papers. These calculations are performed to estimate the distance headway and quantitatively analyse the relationships between the speed, density, and water film depth. By using three road-specific parameters estimated by our proposed model, namely, the free-flow speed, jam density, and capacity flow, a link transmission model is developed to analyse the dynamic impact of the water film depth. [ABSTRACT FROM AUTHOR]

There are differences between the requirements for traffic network for traffic demand in daily and emergency situations. In order to evaluate how the network designed for daily needs can meet the surging demand for emergency evacuation, the concept of emergency reliability and corresponding evaluation method is proposed. This paper constructs a bilevel programming model to describe the proposed problem. The upper level problem takes the maximum reserve capacity multiplier as the optimization objective and considers the influence of reversible lane measures taken under emergency conditions. The lower level model adopts the combined traffic distribution/assignment model with capacity limits, to describe evacuees' path and shelter choice behavior under emergency conditions and take into account the traits of crowded traffic. An iterative optimization method is proposed to solve the upper level model, and the lower level model is transformed into a UE assignment problem with capacity limits over a network of multiple origins and single destination, by adding a dummy node and several dummy links in the network. Then a dynamic penalty function algorithm is used to solve the problem. In the end, numerical studies and results are provided to demonstrate the rationality of the proposed model and feasibility of the proposed solution algorithms. [ABSTRACT FROM AUTHOR]

Aiming at two-lane road, this paper establishes three models to analyze the opposite-overtaking rules of emergency vehicle based on cellular automaton (CCA) model. Based on the simulation of mixed traffic flow for multi-density conditions, the density-speed diagrams have been obtained consequently. According to the analysis, when the traffic density of the opposite lane is low, the opposite driving behavior of emergency vehicle can improve the average speed effectively. At the same time, if the cocurrent lane is in high-density traffic, the traffic in the opposite lane will be disturbed, but the vehicles in the cocurrent lane will not be affected. The paper has further discussed the influence of different emergency vehicle driving behaviors on traffic. The results reveal that as the traffic of the opposite lane is in a low-density range, if emergency vehicle operates overtaking behavior precisely, the greater the density of the cocurrent lane is, the more obviously the speed improve. Meanwhile large random fluctuation of overtaking times will occur. While the risky lane change behavior displays different traffic characteristics, that is when the same direction lane is in high density, the speed increases slightly and the lane change number is changed regularly. [ABSTRACT FROM AUTHOR]

This paper presents the formulation of a new optimization problem designated as the express minibus problem, which intends to form small groups of clients with compatible boarding/exiting points in time and space for a new type of urban mobility service. This new transport option, as a competitive alternative to the private car, aims to provide almost direct services between dispersed demand poles in places where high-capacity and efficient public transport options are scarce, thus combining the major strengths of both public transport and private vehicles. Conventional public transport systems can present efficient space and energy consumption, whereas private vehicles have high levels of flexibility, are fast, and are always available. The proposed algorithm aims at assessing the potential demand of this new service by developing a clustering algorithm in which the groups of clients formed for each minibus route should present the following characteristics: there is a small number of boarding and exiting points, where in each point there is only boarding or alighting; boarding points should be close to each other, as well as the exiting points; there must be a reasonable distance between the last boarding point and the first exiting point; the average load factor must be high; and for all clients the overall detour time relative to the direct service should be small. This paper presents the rationale and structure of the clustering algorithm, followed by an application for the Lisbon metropolitan area during the morning peak, which could be adapted to the afternoon peak with some slight modifications. [ABSTRACT FROM AUTHOR]

Urban traffic congestion is a common problem that affects many cities around the world. In this paper, an actual urban traffic simulation model (AUTM) for traffic congestion predicting and avoiding is proposed, which includes three key components: the map and transfer (MT) conversion method, the optimized spatial evolution rules, and a congestion-avoidance routing algorithm. Three key techniques are combined in our proposed model: (1) The MT conversion method is proposed to get actual urban cellular spaces, which apply the optimized spatial evolution rules to simulate the vehicular dynamics better. (2) AUTM is proposed for simulating traffic congestion and predicting the effect of adding overpasses and roadblocks. (3) The congestion-avoidance routing algorithm is proposed for vehicles to dynamically update their routes toward their destinations, which can achieve traffic optimization in urban simulations. This paper presents the results of applying this novel model to a large-scale real-world case in different urban traffic congestion situations. Extensive experimental simulations in various actual cities have been carried out. Our results in the extreme case are encouraging: The prediction accuracy of traffic congestions is almost 89%, and the variance of prediction road density is less than 0.15. [ABSTRACT FROM AUTHOR]

Abstract: Taking account of the effect of the driver's memory, an extended car‐following model is proposed in this paper. A control signal including the velocity contrast of considered car and the following car is taken into account in this extended model. Numerical simulations are implemented to prove that the application of the model can suppress the traffic congestion successfully. [ABSTRACT FROM AUTHOR]

Train dwell time estimation is a critical issue in both scheduling and rescheduling phases. In a previous paper, the authors proposed a novel dwell time estimation model at short stops which did not require the passenger data. This model shows promising results when applied to Dutch railway stations. This paper focuses on testing and improving the generality of the model by two steps: first, the model is tested by applying more independent datasets from another city and comparing the estimation accuracy with the previous Dutch case; second, the model’s generality is tested by a theoretical approach through the analysis of individual model parameters, variables, model scenarios, and model structure as well as work conditions. The validation results during peak hours show that the MAPE of the model is 11.4%, which is slightly better than the results for the Dutch railway stations. A more generalized predictor called “dwell time at the associated station” is used to replace the square root term in the original model. The improved model can estimate train dwell time in all the investigated stations during both peak and off-peak periods. We conclude that the proposed train dwell time estimation model is generic in the given condition. [ABSTRACT FROM AUTHOR]

Entry capacity loss at multilane roundabouts caused by rainfall was investigated. Traffic and rainfall data were collected continuously for eight weeks at selected sites in South Africa and Malaysia. Three classes of rainfall (light, moderate, and heavy) were used. Both linear and exponential techniques were used to model the relationship between entry and circulating traffic flows. Correction factor for entry angle and radius was introduced in the linear model equations to allow for variations in geometric data. Correction factor is not required for the exponential model technique. Notwithstanding, both techniques predicted that entry capacity loss would result from rainfalls irrespective of their intensity. Results show that light rainfall may cause about 5% entry and circulating capacity loss, moderate rainfall may cause about 12% capacity loss, and heavy rainfall may cause about 17% capacity loss. This paper proposed further studies into the effect of two circulating lanes rather than one on entry capacity at roundabouts. [ABSTRACT FROM AUTHOR]

In smart parking environments, how to choose suitable parking facilities with various attributes to satisfy certain criteria is an important decision issue. Based on the multiple attributes decision making (MADM) theory, this study proposed a smart parking guidance algorithm by considering three representative decision factors (i.e., walk duration, parking fee, and the number of vacant parking spaces) and various preferences of drivers. In this paper, the expected number of vacant parking spaces is regarded as an important attribute to reflect the difficulty degree of finding available parking spaces, and a queueing theory-based theoretical method was proposed to estimate this expected number for candidate parking facilities with different capacities, arrival rates, and service rates. The effectiveness of the MADM-based parking guidance algorithm was investigated and compared with a blind search-based approach in comprehensive scenarios with various distributions of parking facilities, traffic intensities, and user preferences. Experimental results show that the proposed MADM-based algorithm is effective to choose suitable parking resources to satisfy users’ preferences. Furthermore, it has also been observed that this newly proposed Markov Chain-based availability attribute is more effective to represent the availability of parking spaces than the arrival rate-based availability attribute proposed in existing research. [ABSTRACT FROM AUTHOR]

In order to gain an overall view on all relevant connections of the elements in a public transportation system, a systematic approach is advisable to follow, which applies well-proven methodology. In case a structure contains both hierarchical and non-hierarchical connections, the formerly recommended methodologies are: ISM-AHP, ISM-ANP, ANP. This paper however proposes a different approach: AHP-ISM, which aims to keep the AHP hierarchy, but simul- taneously to amend that with the non-hierarchical types of linkages within the structure. By that, those connections that were verified in the AHP procedure can be considered dominant, but also weaker linkages might provide impor- tant additional information about the whole structure. The additional ISM procedure is suitable for two purposes: the most influential elements of the AHP structure can be selected, moreover also direct and indirect impacts of element improvement might be followed in the structure by considering both types of connections within the system, using the directed graph of ISM. The introduced AHP-ISM model is applicable for analyzing public transportation systems – as shown in the paper – but also generally applicable for any AHP applications, which are not strictly but dominantly hierarchically structured. [ABSTRACT FROM AUTHOR]

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models. [ABSTRACT FROM AUTHOR]

Accurate estimates of characteristic traffic load effects are essential in order to optimise bridge safety assessment. Permit trucks dominate the extreme upper tail of the truck loading distribution and as a result need careful examination. This paper proposes rules for filtering these trucks from weigh-in-motion data for both the USA and Europe. The importance of these trucks in critical bridge loading events is then examined for both regions. A Monte Carlo traffic simulation model is developed, which focuses on the accurate simulation of permit trucks. [ABSTRACT FROM AUTHOR]

This paper presents a review and critical analysis of the mathematical literature concerning the modeling of vehicular traffic and crowd phenomena. The survey of models deals with the representation scales and the mathematical frameworks that are used for the modeling approach. The paper also considers the challenging objective of modeling complex systems consisting of large systems of individuals interacting in a nonlinear manner, where one of the modeling difficulties is the fact that these systems are difficult to model at a global level when based only on the description of the dynamics of individual elements. The review is concluded with a critical analysis focused on research perspectives that consider the development of a unified modeling strategy. [ABSTRACT FROM AUTHOR]

This paper deals with linear parameter varying (LPV) modeling and identification of a generic, second-order freeway traffic flow model. A non-conventional technique is proposed to transform the nonlinear freeway traffic flow model into a parameter-dependent form. The resulting exact LPV model is equivalent to the original nonlinear dynamics. Simplification of the nonlinear model gives rise to the introduction of an approximate LPV description. The application of parameter varying identification approaches are made possible by the transformation. Closed-loop predictor-based subspace identification for LPV systems (PBSID LPV) is applied to estimate the affine parameter matrices of the LPV freeway models developed. If the model structure of the original plant is assumed to be known, this paper shows a solution how to estimate LPV model parameters based on the identified model. Parameter-dependent models are identified and validated using real detector measurement data in order to emphasize the applicability of the kernel PBSID LPV methodology. Comparison with traditional nonlinear parametric identification, generally used in traffic identification, is also provided. [ABSTRACT FROM AUTHOR]

Most transport models for short-term strategic planning are required to be calibrated with current planning parameters and updated traffic data. There are basically two steps involved in transport model calibration, namely, trip matrix updating and network calibration. These two steps are carried out iteratively in the conventional approach and may not achieve a stable solution. This paper proposes a bilevel programming model that integrates the two steps of trip matrix updating and network calibration into one stage. A solution algorithm is developed on the basis of genetic algorithms. Numerical examples are presented to illustrate the performance of the proposed model and solution algorithm under various conditions where different source data are available. [ABSTRACT FROM AUTHOR]

Traffic flow simulation is recently being applied to types of studies which require at the same time a large study area and models deeper than macroscopic assignments. Examples are investigations of the effects dynamic route guidance over large networks and the coupling with environmental models on large domains. The computational complexity can be reduced first by moving from microscopic to mesoscopic traffic flow models of the Payne-Cremer type. Where still more computing power is needed, parallelisation of the model may offer a solution. This paper describes a particular mesoscopic traffic flow model and its parallelisation undertaken in the ESPRIT project SIMTRAP. A new two step decomposition strategy is detailed along with its implementation using the message passing model PVM. The resulting speed-up is reported, drawing on both theoretical considerations and on measurements taken in the SIMTRAP demonstrator applications. The paper concludes with lessons learned from the experiments and directions for future work. [ABSTRACT FROM AUTHOR]

A simple yet efficient traffic flow model, in particular one that describes vehicle longitudinal operational control and further characterizes a traffic flow fundamental diagram, is always desirable. Though many models have been proposed in the past with each having its own merits, research in this area is far from conclusive. This paper contributes a new model, i.e., the longitudinal control model, to the arsenal with a unique set of properties. The model is suited for a variety of transportation applications, among which a concrete example is provided in this paper. [ABSTRACT FROM AUTHOR]

This paper is concerned with the modeling of the Dynamic Traffic Assignment Problem (DTAP) for predicting the flows of urban transportation networks, mainly at peak periods. During the past 40 years, most of the research has been for the Static Traffic Assignment Problem (STAP) where it is assumed that demand is constant over time. This assumption is realistic for the analysis of intercity freight transportation networks over long periods of time, but it does not hold in an urban area, for simulating the flow variations during short periods (peak hours). Hence, during the past 20 years, the interest to the DTAP has been increasing. The seventies have been a transition period between heuristic models (where the demand is assigned to instantaneous minimum cost paths), and optimization models that take into account the demand over the whole study horizon of time, but all of them incorporate important limitations (only one destination; unrealistic conditions on the cost functions so that the flow "reaches" the destination; possible violation of the link capacities; etc.). In this paper, we propose a Dynamic Traffic Assignment Model which is mainly based on the following assumption: the time spent by a vehicle on a link may be decomposed into a fixed travel time plus a waiting time. The fixed travel time corresponds to the free or uncongested travel time over the link. Then the vehicle is put in an exit queue (which resides on the same link) until it becomes possible to enter a forward link; this decision is based on the link costs and their capacities. We show that this model leads to a network structure (a temporal expansion of the base network, including the queues) and therefore the DTAP may be viewed as a "simple" STAP over the expanded network. Hence, all the theories... [ABSTRACT FROM AUTHOR]

In this paper, we deal with the analysis of the solutions of traffic flow models at multiple scales in both cases of a single road and road networks. We are especially interested in measuring the distance between traffic states (as they result from the mathematical modeling) and investigating whether these distances are somehow preserved passing from the microscopic to the macroscopic scale. By means of both theoretical and numerical investigations, we show that, on a single road, the notion of Wasserstein distance fully catches the human perception of distance independently of the scale, while in the case of networks it partially loses its nice properties. [ABSTRACT FROM AUTHOR]

In this paper, we use car-following model to explore each commuter's trip cost and the system's total trip cost in the commuter's system allowing late arrival. The numerical results show that each commuter's trip cost and the system's total trip cost are related to each commuter's time headway at the origin and the proportion of the commuters' late arrival, but the system's total trip cost has the minimum value that is irrelevant to the proportion of the commuters' late arrival. [ABSTRACT FROM AUTHOR]

The online routing game model can be used to measure and prove the benefits of online real time data in road traffic navigation systems. A few properties of the routing strategies are already proved. In this paper we point out that there are some paradoxes like phenomena behind these proofs, similarly as in the Braess network. [ABSTRACT FROM AUTHOR]

This paper investigates the cell-transmission model (CTM)-based single destination system optimum dynamic traffic assignment (SO-DTA) problem, focusing attention on a case where the cell properties are time-invariant. We show the backward propagation of congestion in CTM does not affect the optimal arrival flow pattern of SO-DTA, if the fundamental diagram is of triangular/trapezoidal shape as in the CTM. We mathematically prove that the set of earliest arrival flows (EAFs) not constrained by the traffic wave propagation equations obtained on the node-arc network without cell division is a subset of the SO-DTA. This finding leads to a new approach to the SO-DTA that solves the EAF. Such an EAF can be obtained by merely applying static flow techniques and turning the static flows into dynamic flows over time. Therefore, SO-DTA can theoretically be solved with a run time at the link level depending polynomially on log T . We use numerical examples to verify the results and report the computational benefits of the proposed method by solving SO-DTA on a real-world network. [ABSTRACT FROM AUTHOR]

Traffic flow modeling is one of the fundamental keys to solving a traffic engineering problem. Among many parameters, time headway is frequently used to model traffic flow characteristics. A statistical analysis of time headways is immensely important to both theoretical traffic modeling and simulation-based traffic modeling. Basically, it allows researchers to describe an inherently random pattern of traffic flows. Past studies have mainly focused on the time headways of vehicles on highways, freeways, and arterials. However, studies of time headways on urban expressways are rather limited and still need further investigation. In this paper, the author investigates and characterizes the time-headway distributions of vehicles traveling on an urban expressway in Bangkok, Thailand. Particularly, the exponential distribution, the lognormal distribution, and the generalized extreme value (GEV) distribution are used to model the time headways. It is found that the GEV distribution is most effective in modeling time headways. In fact, the GEV distribution can describe more than 90% of the empirical distributions on most lanes and sections of the expressway. On the other hand, the exponential distribution is the least effective distribution. It can only describe the empirical distributions during the periods when the traffic is extremely light. [ABSTRACT FROM AUTHOR]

In this paper, we explore each vehicle's exhaust emissions under the full velocity difference (FVD) model and the car-following model with consideration of the traffic interruption probability during three typical traffic situations. Numerical results show that the vehicle's exhaust emissions of the second model are less than those of the first model under the three typical traffic situations, which shows that the second model can reduce each vehicle's exhaust emissions. [ABSTRACT FROM AUTHOR]

The evaluation of railway line capacity is an important problem, which effects majority of problems in rail transportation planning. The railway capacity is dependent on infrastructure, traffic, and operating parameters. A key factor affecting railway line capacity is the impact of different train types. As the combination of different train types increases, more interference is generated. In this paper, for evaluation of train type interactions on railway line capacity, an integer-programming model for both line and line section is presented. The problem is formulated as a multicommodity network design model on a space-discrete time network. The railway capacity is calculated using data typically available to planners. The inputs of the model are the characteristic of each train type and railway line attributes. The model determines railway capacity based on train type mixes. In addition, this model considers impact of train types on capacity and waiting time. In order to show the features of the model, a case study is implemented in Iran Railways. The capacity tends to increase non-linearly with small incremental changes in parameters. The mixture of train types reduces the railway line capacity. The proposed model can help railway managers for long-term planning. [ABSTRACT FROM PUBLISHER]

The paper presents a model for freeway traffic performance evaluation and control in a First-Order Hybrid Petri Net (FOHPN) framework. Such a hybrid Petri net formalism includes continuous places holding fluid, discrete places containing a non-negative integer number of tokens and transitions, which are either discrete or continuous. In order to suitably describe the dynamics of the freeway traffic flow, we allow updating the transition firing speed as a function of the markings modeling the freeway traffic, as described by the stationary flow-density relationship. Moreover, we propose an online optimal control coordination of speed limits with the objective of maximizing the flow density. The use of FOHPNs offers several significant advantages with respect to the model existing in the related literature: the graphical feature enables an easy modular modeling approach and the mathematical aspects efficiently allow simulating and optimizing the system. The effectiveness of the FOHPN formalism is shown by applying the proposed modeling and control technique to a stretch of a freeway in the North-East of Italy, where a solution of an accident situation is considered. [ABSTRACT FROM PUBLISHER]

This paper considers the technological development of an additional network for Vilnius City public transport. Several types of scenarios for the development of Vilnius City tram line were analysed. This paper describes the situation pertaining to Vilnius City transport system as well as the traffic parameters, which are used for a multiple attribute ranking of a tram line development in Vilnius City. The multiple attribute criteria methods have been chosen to perform the ranking of three development scenarios and to estimate the best alternative based on the traffic conditions of Vilnius City. The experts of different decision-making groups have performed the importance analysis of traffic parameters, which were chosen for the assessment of alternative scenarios for the tram line development. The transport system experts were used to determine the relative weights of indicators. Two methods – TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and SAW (Simple Additive Weighting)–were used and compared to determine the best transport development alternative based on traffic parameters. Two multi-criteria methods were applied in this research to perform the ranking of more accurate alternatives and to make the comparison of calculation results. [ABSTRACT FROM AUTHOR]

An effective calibration method of the cellular automaton based traffic microsimulation model is proposed in this paper. It is shown that by utilizing a genetic algorithm it is possible to calibrate different parameters of the model much better than a traffic expert. Moreover, using this process it is also possible to find several model parameters that arc extremely difficult to calibrate as relevant data can not be measured using standard monitoring technologies or complete data sets arc often not available. The quality of the new calibrated models is discussed in the task of vehicle travel time estimation. The precision of simulations is increased over three times compared to a manually tuned model. The average error rate is 10.75 % in comparison with several field travel time data. [ABSTRACT FROM AUTHOR]

This paper proposes a simulation-based optimization (SO) method that enables the efficient use of complex stochastic urban traffic simulators to address various transportation problems. It presents a metamodel that integrates information from a simulator with an analytical queueing network model. The proposed metamodel combines a general-purpose component (a quadratic polynomial), which provides a detailed local approximation, with a physical component (the analytical queueing network model), which provides tractable analytical and global information. This combination leads to an SO framework that is computationally efficient and suitable for complex problems with very tight computational budgets. We integrate this metamodel within a derivative-free trust region algorithm. We evaluate the performance of this method considering a traffic signal control problem for the Swiss city of Lausanne, different demand scenarios, and tight computational budgets. The method leads to well-performing signal plans. It leads to reduced, as well as more reliable, average travel times. [ABSTRACT FROM AUTHOR]

Pedestrian simulation plays an important role in the fields of transport station management, building evacuation and safety management of large public events. Among the continuous pedestrian flow models, the social force model is one of the most widespread and supports all of the above use cases. Since its initial proposal by Helbing and Molnar [(1995). Social force model for pedestrian dynamics. Physical Review E, 51, 4282], many improvements of the social force model have been put forward for solving various, but mostly specific, problems. However, an up-to-date and essentially comprehensive review bringing all the model variants into a common context is missing. In this paper, we propose such a framework in terms of assessment criteria for pedestrian models considering pedestrian attributes, motion base cases, self-organisation phenomena and some special cases. Starting with the initial version of Helbing and Molnar [(1995). Social force model for pedestrian dynamics. Physical Review E, 51, 4282] and the escape panic version of Helbing, Farkas, and Vicsek [(2000a). Simulating dynamical features of escape panic. Nature, 407, 487-490], we classify the improvements and assess their degree of the improvements. Further discussion is presented from the perspectives of description ability, parameter calibration and flexible application in a complex environment. [ABSTRACT FROM AUTHOR]

Road crashes are mainly caused by three concurrent factors: infrastructure, vehicles, and human factors. The interaction between infrastructure and human factors leads to the concept of geometric design consistency, which can be defined as how drivers’ expectations and road behavior fit. This paper presents a new global consistency model based on the difference between the inertial operating speed profile (Vi) and the operating speed profile (V85). The first is calculated as the weighted average speed of the previous road section and represents drivers’ expectations, whereas the second represents road behavior. A set of 71 homogeneous two-lane rural road segments located in Italy were used in the calibration of the model. As a result, a safety performance function based on this new consistency model was proposed to estimate the number of crashes on an entire road segment. Finally, the new model was compared with previous global consistency models, concluding that the new consistency parameter better explains the phenomenon than the previous ones. Therefore, the new consistency model is a useful tool for engineers that allows estimation of the number of crashes and incorporates road safety into the geometric design of both new two-lane rural roads and improvements to existing highways. [ABSTRACT FROM AUTHOR]

This paper deals with accuracy and long-term stability of bridge weigh-in-motion (B-WIM) systems. Research focused on four improvements, developed within two research projects financed by the European Commission. These improvements have increased accuracy of the results for four classes according to the European WIM specifications. The novel axle detection method recommends alternative locations to acquire strain responses under the moving vehicles, which provide reliable axle information without the need to install axle detectors in the carriageway. The new algorithm for calculating experimental influence lines combines the individual influence lines, generated from the responses of vehicles from the traffic flow, to obtain a robust solution that does not depend on the type of the vehicle. The third development adjusts the sensor factors to account for measurement errors on concrete structures, especially those resulted from hidden cracks. Finally, the effects of varying temperature and vehicle velocities on the WIM results were studied and their influences mitigated, to increase long-term stability of B-WIM results. All improvements were validated using long-term B-WIM measurements collected on four different bridges. [ABSTRACT FROM AUTHOR]

The car-following model is an important micro-traffic model for simulating car-following behaviour in traffic engineering and research studies. Conventional car-following models are always presented using mathematical equations reflecting ideal traffic conditions. In the big data era, data-driven models become a popular trend. In this study, a data-driven car-following model based on the rough set theory is proposed to consider information hidden in a field data set. On the basis of field data obtained from measurement devices such as the next generation simulation (NGSIM) trajectory data set, and using the methods of the rough set theory, an optimal decision rule set is established. Redundant attributes and redundant attribute values are removed for simplifying the car-following behaviour decision problem. Attribute significance and weights are computed for selecting matching rules. A car-following behaviour decision algorithm is designed to choose appropriate rules to determine the follower's velocity according to current observations. Simulations illustrate that the proposed data-driven car-following model can simulate the micro-traffic behaviour of followers well. [ABSTRACT FROM AUTHOR]

Road traffic simulation is a useful tool for studying road traffic and evaluating solutions to traffic problems. Large-scale agent-based road traffic simulation is computationally intensive, which triggers the need for conducting parallel simulation. This paper deals with the synchronization problem in parallel agent-based road traffic simulation to reduce the overall simulation execution time. We aim to reduce synchronization operations by introducing some redundant computation to the simulation. There is a trade-off between the benefit of reduced synchronization operations and the overhead of redundant computation. The challenge is to minimize the total overhead of redundant computation and synchronization. First, to determine the amount of redundant computation, we proposed a way to define extended layers of partitions in the road network. The sizes of extended layers are determined by the behavior of agents and the topology of road networks. Second, due to the dynamic nature of road traffic, a heuristic was proposed to adjust the amount of redundant computation according to traffic conditions during simulation run-time to minimize the overall simulation execution time. The efficiency of the proposed method was investigated in a parallel agent-based road traffic simulator using real-world network and trip data. Results have shown that the method can reduce synchronization overhead and improve the overall performance of the parallel simulation significantly. [ABSTRACT FROM PUBLISHER]

Severe weather conditions and inherent uncertainties in various components of railway traffic systems can lead to equipment breakdown and reduced capacity on tracks and stations. This paper formulates a two-stage fuzzy optimization model to obtain a robust rescheduling plan under irregular traffic conditions, and a scenario-based representation is adapted to characterize fuzzy recovery time durations on a double-track railway line. The model aims to minimize the expected total delay time in the rescheduled train schedule with respect to the original timetable. Two decomposed sub-models are further developed corresponding to the trains in different directions, and then GAMS optimization software is used to obtain the robust rescheduling plan. The numerical experiments demonstrate the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

SUMMARY This paper proposes a stepwise genetic fuzzy logic controller (SGFLC) by considering traffic flows and queue lengths of cars and motorcycles as state variables and extension of green time as control variable, towards the minimization of total vehicle delays. For the learning efficiency of SGFLC and the capability in capturing traffic behaviors of Asian urban streets, where mixed traffic of cars and motorcycles are prevailing, the mixed traffic cell transmission model (MCTM) is introduced to replicate traffic behaviors. To investigate the control performance of the proposed SGFLC model, comparisons with two pre-timed timing plans and three adaptive signal timing models are conducted at an isolated intersection. Results show our proposed SGFLC model performs best. Moreover, as traffic flows vary more noticeably, the SGFLC model performs even better. In the experimental and field cases of three-intersection arterial under four coordinated signal systems, namely simultaneous, progressive, alternate and independent, both cases consistently show that the proposed SGFLC model perform best, suggesting that the proposed SGFLC signal control model is efficient and robust. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Left-turn gap acceptance at an unsignalized intersection is dependent on many factors. The Highway Capacity Manual (HCM) uses a single value of critical gap for all types of intersections; however, this may be oversimplistic and lead to inaccurate estimates of left-turn delay and capacity. Most existing studies also do not differentiate between gap and lag when evaluating gap acceptance. In this paper, binary logit models were developed to estimate the probability of accepting or rejecting a given gap or lag for a left-turning vehicle from a major road at an unsignalized intersection considering a number of potential influencing factors. Gap acceptance behavior was found to be influenced by the type of gap presented to the driver (gap or lag). Gap duration, total wait time, time to turn, distance to next signal downstream, and median type were found to be significant factors in predicting the probability of accepting or rejecting a gap. In the model for lag acceptance lag duration, time to turn, crossing width, speed limit, and distance to next signal downstream were found to be significant. Equations for estimating the critical gap and lag were developed. Critical gap and lag were found to be varying over a wide range of values depending on the type of intersection. The range was smaller for critical gaps than lags. The findings from this study can improve operational analysis of left turns at unsignalized intersections by using different critical gaps for different traffic and geometric conditions. [ABSTRACT FROM AUTHOR]

This paper presents a lane-level positioning method by trajectory reckoning without Global Positioning System (GPS) equipment in the environment of Cooperative Vehicle-Infrastructure System (CVIS). Firstly, the accuracy requirements of vehicle position in CVIS applications and the applicability of GPS positioning methods were analyzed. Then, a trajectory reckoning method based on speed and steering data from vehicle's Control Area Network (CAN) and roadside calibration facilities was proposed, which consists of three critical models, including real-time estimation of steering angle and vehicle direction, vehicle movement reckoning, and wireless calibration. Finally, the proposed method was validated through simulation and field tests under a variety of traffic conditions. Results show that the accuracy of the reckoned vehicle position can reach the lane level and match the requirements of common CVIS applications. [ABSTRACT FROM AUTHOR]

The development of control systems to handle the congestion at intersection in urban traffic is a critical research issue. Petri Nets and Fuzzy Logic have played vital role in the development of such systems. Petri nets, a mathematical modeling tool, makes graphical modeling, simulation and real time control modeling, more functional. Fuzzy logic deals with uncertainties in the environment to make the systems more realistic. In this paper, a real time traffic control model has proposed and implemented in MATLAB. Several results have been discussed and found satisfactory. [ABSTRACT FROM AUTHOR]

Multiagent-based simulation (MABS) is a very active interdisciplinary area bridging multiagent research and social science. The key technology to conduct truly useful MABS is agent modeling for reproducing realistic behaviors. In order to make agent models realistic, it seems natural to learn from human behavior in the real world. The challenge presented in this paper is to obtain an individual behavior model by using participatory modeling in the traffic domain. We show a methodology that can elicit prior knowledge for explaining human driving behavior in specific environments, and then construct a driving behavior model based on the set of prior knowledge. In the real world, human drivers often perform unintentional actions, and occasionally, they have no logical reason for their actions. In these cases, we cannot rely on prior knowledge to explain them. We are forced to construct a behavior model with an insufficient amount of knowledge to reproduce the driving behavior. To construct such individual driving behavior model, we take the approach of using knowledge from others to complement the lack of knowledge from the target. To clarify that the behavior model including prior knowledge from others offers individuality in driving behavior, we experimentally confirm that the driving behaviors reproduced by the hybrid model correlate reasonably well with human behavior. [ABSTRACT FROM PUBLISHER]

Based on the effects that signal light has on car-following behavior, this paper developed a new signal light model. Numerical tests show that our model can reproduce the cluster, the dissipation and the propagation of the stopping waves and starting waves resulted by signal light. Finally, linear stability analysis and simulation show that our model is always stable. [ABSTRACT FROM AUTHOR]

Traffic systems are often highly populated discrete event systems that exhibit several modes of behavior such as free flow traffic, traffic jams, stop-and-go waves, etc. An appropriate closed loop control of the congested system is crucial in order to avoid undesirable behavior. This paper proposes a macroscopic model based on continuous Petri nets as a tool for designing control laws that improve the behavior of traffic systems. The main reason to use a continuous model is to avoid the state explosion problem inherent to large discrete event systems. The obtained model captures the different operation modes of a traffic system and is highly compositional. In order to handle the variability of the traffic conditions, a model predictive control strategy is proposed and validated. [ABSTRACT FROM AUTHOR]