Numerical simulation of a continuum model for bi-directional pedestrian flow

An algorithm for an extended reactive dynamic user equilibrium model of pedestrian counterflow as a continuum is developed. It is based on a cell-centered high-resolution finite volume scheme with a fast sweeping method for an Eikonal-type equation on an orthogonal grid. A high-order total variation diminishing Runge-Kutta method is adopted for the time integration of semi-discrete equations. The numerical results demonstrate the rationality of the model and efficiency of the algorithm. Some crowd pedestrian flow phenomena, such as dynamic lane formation in bi-directional flow, are observed which are helpful for a global comprehension of pedestrian dynamics. Also, the model can be utilized with different potential applications.     

An anisotropic continuum model for traffic assignment in mixed transportation networks

This work deals with a two-dimensional continuum model for the problem of congested traffic assignment in an urban transportation system consisting of a set of freeways superimposed over a dense street network. The formulation leads to a system of non-linear differential equations whose unknowns are given by the travel times from arbitrary points of the network to the corresponding destinations. The governing equations are appropriately solved by means of the Finite Element Method. Then, traffic flow on every link of the network can be obtained. Numerical examples are given in order to demonstrate the efficiency of the developed model.     

A personalized kinetic model of traffic flow

A kinetic model of traffic flow on roads is developed which takes into account not only the multilane structure of the road, but also the multifaced aspect of traffic in which different kinds of vehicles and of drivers interact together. Differentiation among the various types of individuals is accomplished by introducing, in the traffic simulation, a modeling methodology proper of sociobiological population dynamics. In particular, the evolution is described by a generalized Boltzmann model for several population density functions. On the other hand, the intrinsic character of the individual driver-vehicle, that is free to autonomously decide about his future, justifies the introduction of an independent linear stochastic term in the evolution equation, in addition tto the quadratic interaction one, that is uncommon in these models.     

Hybrid evolutionary algorithms in a SVR traffic flow forecasting model

Accurate urban traffic flow forecasting is critical to intelligent transportation system developments and implementations, thus, it has been one of the most important issues in the research on road traffic congestion. Due to complex nonlinear data pattern of the urban traffic flow, there are many kinds of traffic flow forecasting techniques in literature, thus, it is difficult to make a general conclusion which forecasting technique is superior to others. Recently, the support vector regression model (SVR) has been widely used to solve nonlinear regression and time series problems. This investigation presents a SVR traffic flow forecasting model which employs the hybrid genetic algorithm-simulated annealing algorithm (GA-SA) to determine its suitable parameter combination. Additionally, a numerical example of traffic flow data from northern Taiwan is used to elucidate the forecasting performance of the proposed SVRGA-SA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal autoregressive integrated moving average (SARIMA), back-propagation neural network (BPNN), Holt-Winters (HW) and seasonal Holt-Winters (SHW) models. Therefore, the SVRGA-SA model is a promising alternative for forecasting traffic flow.     

A novel car-following inertia gray model and its application in forecasting short-term traffic flow

Real-time and accurate short-term traffic flow prediction results can provide real-time and effective information for traffic information systems. Based on classic car-following models, this paper establishes differential equations according to the traffic state and proposes a car-following inertial gray model based on the information difference of the differential and gray system, in combination with the mechanical characteristics of traffic flow data and the characteristics of an inertial model. Furthermore, analytical methods are used to study the parameter estimation and model solution of the new model, and the important properties, such as the original data, inertia coefficient and simulation accuracy, are studied. The effectiveness of the model is verified in two cases. The performance of the model is better than that of six other prediction models, and the structural design of the new model is more reasonable than that of the existing gray models. Moreover, the new model is applied to short-term traffic flow prediction for three urban roads. The results show that the simulation and prediction effects of the model are better than those of other gray models. In terms of the traffic flow state, an optimal match between short-term traffic flow prediction and the new model is achieved.     

An extended multi-anticipative delay model of traffic flow

An extended multi-anticipative delay model is proposed by introducing multiple velocity differences and incorporating the reaction-time delay of drivers. The stability condition of the new model is obtained by applying the linear stability theory, and the modified Korteweg–de Vries (mKdV) equation is derived by the use of the nonlinear analysis method. The analytical and numerical results show that both the reaction-time delay of drivers and the information of multiple velocity differences have an important influence on the stability of the model, and that the stabilization of traffic flow is enhanced by appending the velocity difference information of multiple vehicles ahead or by decreasing the delay time.     

The Aw-Rascle traffic model with locally constrained flow

We consider solutions of the Aw-Rascle model for traffic flow fulfilling a constraint on the flux at x=0. Two different kinds of solutions are proposed: at x=0 the first one conserves both the number of vehicles and the generalized momentum, while the second one conserves only the number of cars. We study the invariant domains for these solutions and we compare the two Riemann solvers in terms of total variation of relevant quantities. Finally we construct ad hoc finite volume numerical schemes to compute these solutions.     

A new cellular automaton model for traffic flow

Establishment of effective traffic models to reveal fundamental traffic characteristics is an essential requirement in the design, planning and operation of transportation systems. In 1992 Nagel and Schreckenberg presented a cellular automaton model describing traffic flow of N cars on a single lane and applied it in the famous project TRANSIMS on transportation simulation. In this paper, the author proposes a new model for the same problem and gives a comparison of simulation results with the former ones. The comparison shows that the new model works better under the condition of high traffic density.     

A microcrack-based continuum damage model with application towards refractories

The present work discusses numerical results of damage evolution due to thermoshock processes at refractory ceramics. Damage patterns have been generated using a two-scale approach for brittle materials, implemented into a finite element framework. For this purpose, a cell model has been employed, incorporating cracks on a microscopic level. The impact of these discontinuities on macroscopic material properties and damage evolution is determined with the help of analytical homogenization techniques. Finally, the potential of the numerical tool is demonstrated by means of refractory bricks, being imposed by thermomechanical loading. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Non-linear analysis of a traffic flow

A nonlinear mathematical model, which takes into account the dissipative mechanism, is used to describe the signal transmission in a traffic flow. It is shown that dissipative mechanisms, under certain conditions, may produce attenuation effects against the typical nonlinear steepening of waves. An asymptotic analysis is carried out to discuss wave features when the governing hyperbolic system of equations is objective to different kinds of approximations.     

Simulation of turbulent dispersion using a simple random model of the flow field

A method is devised to simulate the movement and spreading of a patch of contaminant in two-dimensional turbulent flow. The turbulent motion is exponentially divided into components of differing wave number, adjacent components being made to have correlation times differing by a factor of two. The turbulent motion is then reconstructed by replacing each component with a sinusoidal advection field having a randomly directed wave number. Contaminant particles are advected by each of the reconstructed components, the smallest scale components being applied first. A computer simulation was performed, using a Kolmogorov k^{-$\text{5}\text{3}$} turbulent energy spectrum. Batchelor's σ ∝ t^{$\text{3}\text{2}$} law for the spreading of a contaminant patch was reproduced, approximately, as was Richardson's non-Gaussian asymptotic form of the distance-neighbour function.     

A simple model for fluid accumulation and flow in a porous medium

A porous media model is derived describing the accumulation and flow of fluid within a domain. The model consists of a differential expression determining the saturated fluid subdomain and a relation describing the pressure distribution within that domain. The wellposedness and numerical solution of a simplified problem is presented and a validation using field rainfall outflow data collected from a highway roadbed is discussed.     

The mathematical solution of a cellular automaton model which simulates traffic flow with a slow-to-start effect

In this paper we investigate a cellular automaton model associated with traffic flow and of which the mathematical solution is unknown before. We classify all kinds of stationary states and show that every state finally evolves to a stationary state. The obtained flow-density relation shows multiple branches corresponding to the stationary states in congested phases, which are essentially due to the slow-to-start effect introduced into this model. The stability of these states is formulated by a series of lemmas, and an algorithm is given to calculate the stationary state that the current state finally evolves to. This algorithm has a computational requirement in proportion to the number of cars.     

A network traffic flow model for motorway and urban highways

The research reported in this paper develops a network-level traffic flow model (NTFM) that is applicable for both motorways and urban roads. It forecasts the traffic flow rates, queue propagation at the junctions and travel delays through the network. NTFM uses sub-models associated with all road and junction types that comprise the highway. The flow at any one part of the network is obviously very dependent on the flows at all other parts of the network. To predict the two-way traffic flow in NTFM, an iterative simulation method is executed to generate the evolution of dependent traffic flows and queues. To demonstrate the capability of the model, it is applied to a small case study network and a local Loughborough–Nottingham highway network. The results indicate that NTFM is capable of identifying the relationship between traffic flows and capturing traffic phenomena such as queue dynamics. By introducing a reduced flow rate on links of the network, the effects of strategies used to carry out roadworks can be mimicked.     

A hybrid macroscopic-based model for traffic flow in road networks

Recently, the unquestionable growth of interest to increase the operational efficiency and capability of transportation systems led to the development of a large number of traffic modeling theories. One of the major operational issues when developing a transportation system management model lies in the selection of the appropriate methodological approach with respect to several decisions, such as the selection of the type of input and output data as well as the qualitative representation and the computational power of the model. Despite the considerable effort in the area, there is still not an approach which per se models effectively the various dynamically evolving features of traffic in road networks. The present paper addresses this issue by introducing a new hybrid approach which combines the complementary features and capabilities of both continuum mathematical models e.g. 1, 6, 23 and 26 and knowledge-based models e.g. 7, 22 and 28 in order to describe effectively traffic flow in road networks.     

An aggregate stochastic programming model for air traffic flow management

In this paper, we present an aggregate mathematical model for air traffic flow management (ATFM), a problem of great concern both in Europe and in the United States. The model extends previous approaches by simultaneously taking into account three important issues: (i) the model explicitly incorporates uncertainty in the airport capacities; (ii) it also considers the trade-off between airport arrivals and departures, which is a crucial issue in any hub airport; and (iii) it takes into account the interactions between different hubs.The level of aggregation proposed for the mathematical model allows us to solve realistic size instances with a commercial solver on a PC. Moreover it allows us to compute solutions which are perfectly consistent with the Collaborative Decision-Making (CDM) procedure in ATFM, widely adopted in the USA and which is currently receiving a lot of attention in Europe. In fact, the proposed model suggests the number of flights that should be delayed, a decision that belongs to the ATFM Authority, rather than assigning delays to individual aircraft.     

A two-regime traffic flow model and the consistency of its parameters

An attempt is made to demonstrate the traffic behaviour and phenomena under normal morning peak period conditions, and to examine the suitability of a two-regime traffic flow model for these conditions. This paper has three main parts. First, the consistency of flow and concentration patterns of a 9-mile freeway section is examined and provides a basis for distinguishing between the free-flow and the congested-flow regimes. This distinction clearly indicates the data points obtained from traffic flow situations, which, in time-sequence, approach maximum flow conditions, congested conditions, and through a recovery process backwards to free-flow conditions.

In the second part, a car-following model for the two-regime approach is introduced. By using the analysis of driver performance as a sensitivity measurement, model parameters are defined and evaluated. An overall comparison between the proposed and known generalized car-following models emphasizes the advantages of the proposed model, particularly its simplicity and clarity at both the micro- and macroscopic levels, for the two-regime phenomenon.

In the third part, the steady-state formulation, derived from the proposed car-following model, is evaluated by using the time-sequence data points. The consistency of the two-regime model parameters is apparently well preserved regarding data sets of 3-year period (1972–1975) with respect to three independent variables: years, workdays and locations.     

Stabilization of traffic flow in optimal velocity model via delayed-feedback control

Traffic jams may occur due to various reasons, such as traffic accidents, lane reductions and on-ramps. In order to suppress the traffic congestion in an optimal velocity traffic model without any driver’s delay taken into account, a delayed-feedback control of both displacement and velocity differences is proposed in this study. By using the delay-independent stability criteria and the H_∞-norm, the delayed-feedback control can be determined to stabilize the unstable traffic flow and suppress the traffic jam. The numerical case studies are given to demonstrate and verify the new control method. Furthermore, a comparison is made between the new control method and the method proposed by Konishi et al. [K. Konishi, M. Hirai, H. Kokame, Decentralized delayed-feedback control of an optimal velocity traffic model, Eur. Phys. J. B 15 (2000) 715–722]. The results show that the new control method makes the traffic flow more stable and improves the control performance.