Hybrid Traffic Flow Model Research Articles

Research on the application of cellular automata and improved BP neural network in road design of logistics park

With large-scale construction of the Logistics Parks, it has become an urgent problem to quantitatively analyze, evaluate and optimize the logistics park designing, which needs to be solved scientifically. At present, more of the domestic logistics park planning of a part of the qualitative analysis, the lack of quantitative and overall study, resulting in internal structure disjointed. Based on cellular automata theory, this paper presents a hybrid traffic flow model which is more suitable for the traffic characteristics of the logistics park, and analyzes the complexity of the collection and evacuation system in the logistics park, combined with BP neural network and its improved algorithm, the method of road design in Logistics Park is studied and the feasibility and validity of the model and algorithm are verified by an example. The train of thought is expected to provide for the planning and construction of the internal road in the logistics park.

A traffic responsive control framework for signalized junctions based on hybrid traffic flow representation

The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized method, which can simultaneously compute the network decision variables (i.e., the green timings at each junction and the offset of the traffic light plans of the network). Furthermore, the framework is based on a hybrid traffic flow model operating as a prediction model and plant model in the control procedure. The hybrid traffic flow model combines two sub-models: an aggregate model (i.e., the Cell Transmission Model; CTM) and a disaggregate model (i.e., the Cellular Automata model; CA), using a transition cell to connect them. The whole framework is tested on a signalized arterial, performing several analyses to calibrate the MPC strategy and evaluate the traffic control approach using fixed and adaptive control strategies. All analyses are made in terms of total time spent, network total delay, queue lengths and degree of saturation.

A hybrid traffic flow model for traffic management with human-driven and connected vehicles

This paper proposes a hybrid traffic flow model able to support the implementation of traffic management strategies in the presence of human-driven and connected vehicles. The model is based on the combination of two models: an aggregate model (the cell transmission model) and a disaggregate model (the cellular automata model). The model was tested considering three main layouts, namely a ring-shaped arc, a signalised link, and a grid network with four origins and four destinations, and then calibrated on real data. The model was also applied in the presence of connected vehicles. Our results point out the model’s local consistency in terms of wave propagation and its suitability with respect to the benchmark models as well as in the presence of connected vehicles.

Analysis and comparison of traffic flow models: a new hybrid traffic flow model vs benchmark models

BackgroundThis paper compares a hybrid traffic flow model with benchmark macroscopic and microscopic models. The proposed hybrid traffic flow model may be applied considering a mixed traffic flow and is based on the combination of the macroscopic cell transmission model and the microscopic cellular automata.Modelled variablesThe hybrid model is compared against three microscopic models, namely the Krauß model, the intelligent driver model and the cellular automata, and against two macroscopic models, the Cell Transmission Model and the Cell Transmission Model with dispersion, respectively. To this end, three main applications were considered: (i) a link with a signalised junction at the end, (ii) a signalised artery, and (iii) a grid network with signalised junctions.ResultsThe numerical simulations show that the model provides acceptable results. Especially in terms of travel times, it has similar behaviour to the microscopic model. By contrast, it produces lower values of queue propagation than microscopic models (intrinsically dominated by stochastic phenomena), which are closer to the values shown by the enhanced macroscopic cell transmission model and the cell transmission model with dispersion. The validation of the model regards the analysis of the wave propagation at the boundary region.

Evolvement laws and stability analyses of traffic network constituted by changing ramps and main road

Proposing realistic hybrid traffic flow model is a promising and hot topic in the area of fluid mechanics and nonlinear dynamics, since they can take advantages of combining dynamical properties of each individual vehicle and macroscopic characteristics of the global system. In this paper, different from the previous work, we propose a hybrid traffic flow model considering the dynamical competition between ramps and main roads. Afterwards, the dynamical control equations of the proposed system are established. Then, by means of performing finite difference analyses, nonlinear dynamical characteristics and specific properties of the proposed system are investigated. Evolvement laws of characteristic order parameters of the proposed traffic flow system are obtained by analyzing the change of density, velocity and current in various circumstances. Moreover, matrices of partition coefficient are employed into the proposed traffic network composed of a main road and varied ramps. Additionally, linear and nonlinear stability analyses are considered in different phase spaces. Therefore, the robustness of the proposed system is tested by both linear and nonlinear dynamics. Our work will be helpful to understand mesoscopic dynamical behaviors of each individual vehicle and inner interactions between them.

Stability analysis and wave dynamics of an extended hybrid traffic flow model

The stability analysis and wave dynamic properties of an extended hybrid traffic flow model, WZY model, are intensively studied in this paper. The linear stable condition obtained by the linear stability analysis is presented. Besides, by means of analyzing Korteweg–de Vries equation, we present soliton waves in the metastable region. Moreover, the multiscale perturbation technique is applied to derive the traveling wave solution of the model. Furthermore, by means of performing Darboux transformation, the first-order and second-order doubly-periodic solutions and rational solutions are presented. It can be found that analytical solutions match well with numerical simulations.

Hybrid traffic flow model for intelligent vehicles exiting to off-ramp

With the rapid development of vehicular technology, hi-tech manufacturing facilities are equipped in intelligent vehicles to improve road capacity and traffic safety. However, freeway diverge segment has significant influence on current traffic flow, and could affect the heterogeneous traffic flow consisting of manual and intelligent vehicles. The primary objective of this study is to evaluate how intelligent vehicles affect traffic flow at an off-ramp bottleneck.In order to depict the car-following dynamics of manual vehicles, the modified comfortable model, one of the most classic cellular automata models, is employed to distinguish intelligent vehicles. In this paper, intelligent vehicles consist of adaptive cruise control (ACC) vehicles cooperative adaptive cruise control (CACC) vehicles. The ACC and CACC model are proposed by partners for advanced transportation technology (PATH), which are validated by real experimental data. Besides, vehicles equipped with CACC will degrade ACC vehicle if the leading vehicle is driven manually. From the perspective of vehicle's lateral movement, two novel lane-changing models, including the discretionary lane-change (DLC) model and mandatory lane-change (MLC) model, are developed to model the future behaviors of intelligent vehicles. A risk factor λ is introduced into the DLC model to distinguish vehicles from conventional ones. Based on environment perception technology, a five-step MLC decision-making model is designed specifically for intelligent vehicles exiting to off-ramp. It is comprised of environment perception, safe gap computation, measured gap ranking, measured gap classification and lane-changing gap selection. Based on the proposed hybrid traffic flow model, numerical simulations are conducted to study the influences of intelligent vehicles on the traffic flow near an off-ramp. Apart from the market penetration of intelligent vehicles, parameters considered in this paper include the demands of mainlines and off-ramp, range of environment perception, length of lane-changing area, and level of lane-changing risk.Analytical studies and simulation results are as follows. 1) The integration of car-following model and lane-changing model for the off-ramp system enables vehicles to have reasonable dynamic characteristics. 2) The capacity ascends to the peak after an initial decrease as CACC vehicle penetration increases. The maximum capacity obtained in 100% CACC vehicle scenario is improved by over 50%, compared with that in 50% CACC penetration scenario. 3) Enlarging the ranges of environment perception and lane-changing areas, and enhancing the lane-changing risk can significantly dissipate congestion upstream of the off-ramp and improve the efficiency of mainlines. However, they have little influence on traffic flow at off-ramp. 4) The worst performance of the system occurs in the scenario of 50% CACC penetration, where deterioration caused by degraded ACC vehicles suggests that enough patience and public confidence should be paid for the development of intelligent vehicles.

Theoretical analysis of a hybrid traffic model accounting for safe velocity

A hybrid traffic-flow model [Wang–Zhou–Yan (WZY) model] is brought out in this paper. In WZY model, the global equilibrium velocity is replaced by the local equilibrium one, which emphasizes that the modification of vehicle velocity is based on the view of safe-driving rather than the global deployment. In the view of safe-driving, the effect of drivers’ estimation is taken into account. Moreover, the linear stability of the traffic model has been performed. Furthermore, in order to test the robustness of the system, the evolvement of the density wave and the velocity wave of the traffic flow has been numerically calculated.

A hybrid traffic flow model with considering the influence of adaptive cruise control vehicles and on-ramps

Recently, autonomous vehicles and the relevant studies have attracted much attention. Adaptive cruise control (ACC), which is a kind of cruise control system for vehicles, automatically adjusts the vehicle speed to maintain a safe distance from vehicles ahead. Since the vehicle with ACC (called ACC vehicles) is semi-autonomous, the performance of ACC vehicle must be quite different from that of manual vehicle. The characteristics of traffic flow with ACC vehicles should be carefully investigated, especially when the traffic system is a bit complicated, such as on-ramp system. The primary objective of this paper is to propose a traffic flow model to simulate the traffic flow with considering the influence of ACC vehicles and on-ramps. Based on the model proposed by Yuan in 2009 [Yuan Y M 2009 Ph. D. Dissertation (Hefei: University of Science and Technology of China)], a hybrid traffic flow model with considering the influence of ACC vehicles and on-ramps is developed. Considering the differences between ACC and manual vehicles, a car-following sub-model based on constant time headway principle is developed for ACC vehicles, while an MCD cellular automata sub-model is proposed for manual vehicles. Besides, a new parameter, , is introduced to show different psychologies of drivers when changing lane from on-ramp to main road. The lane-changing model for vehicles on-ramp is developed as well. At the end, numerical simulation is demonstrated to study the influence of ACC vehicles on traffic flow at on-ramp, and to reveal the influence of parameters on the proposed hybrid model (i.e., the length of merge area, the desired time headway of ACC vehicle and ) on model performance. The results of this paper are as follows. 1) When the ACC vehicles exist in a traffic system, the performance of traffic flow in a on-ramp area is improved: the influence of merged vehicles on main road is reduced, and the average speed and volume are increased. 2) The increase of ACC vehicles can help to alleviate traffic congestion in both congestion duration and scope aspects. 3) The newly proposed hybrid model is sensitive to the length of merge area lw, the desired time headway of ACC vehicle Hd and lane-changing psychology parameter : the decrease of Hd and the increase of can both improve the average speed and volume of traffic flow. In addition, when the volume of on-ramp is small, the speed and volume of main road can be improved by enlarging lw. When the volume of on-ramp is large, a small lw will be better for traffic flow.

Vehicle density estimation of freeway traffic with unknown boundary demand–supply: an interacting multiple model approach

As distributed parameter systems, dynamics of freeway traffic are dominated by the current traffic parameter and boundary fluxes from upstream/downstream sections or on/off ramps. The difference between traffic demand-supply and boundary fluxes actually reflects the congestion level of freeway travel. This paper investigates simultaneous traffic density and boundary flux estimation with data extracted from on-road detectors. The existing studies for traffic estimation mainly focus on the traffic parameters (density, velocity, etc.) of mainline traffic and ignore flux fluctuations at boundary sections of the freeway. We propose a stochastic hybrid traffic flow model by extending the cell transmission model (CTM) with Markovian multi-mode switching. A novel interacting multiple model (IMM) filtering for simultaneous input and state estimation is developed for discrete-time Markovian switching systems with unknown input. A freeway segment of Interstate 80 East (I-80E) in Berkeley, Northern California, is chosen to investigate the performance of the developed approach. Traffic data is obtained from the Performance Measurement System (PeMS).

A hybrid traffic flow model for real time freeway traffic simulation

Macroscopic traffic flow models play a significant role in the Intelligent Transportation Systems (ITS), especially for the urban traffic control and the dynamic traffic assignment, in which the traffic dynamics usually described by the nonlinear equations are difficult to be solved and limit the practice application. This paper presents a hybrid macroscopic and microscopic (macromicroscopic) traffic model by extending Daganzo’s Cell Transmission Model (CTM) with the real time speed dynamic. A simple supplying and demanding function is defined to represent the traffic propagation between the adjacent cell boundaries, and the car-following model is integrated to specify the dynamics of average speed in each cell. Simulation results with data set collected from a 4-kilometre long urban freeway show the performance of the model compared to the METANET model.

Exact and grid-free solutions to the Lighthill–Whitham–Richards traffic flow model with bounded acceleration for a class of fundamental diagrams

In this article, we propose a new exact and grid-free numerical scheme for computing solutions associated with an hybrid traffic flow model based on the Lighthill–Whitham–Richards (LWR) partial differential equation, for a class of fundamental diagrams. In this hybrid flow model, the vehicles satisfy the LWR equation whenever possible, and have a constant acceleration otherwise. We first propose a mathematical definition of the solution as a minimization problem. We use this formulation to build a grid-free solution method for this model based on the minimization of component function. We then derive these component functions analytically for triangular fundamental diagrams, which are commonly used to model traffic flow. We also show that the proposed computational method can handle fixed or moving bottlenecks. A toolbox implementation of the resulting algorithm is briefly discussed, and posted at https://dl.dropbox.com/u/1318701/Toolbox.zip.

Optimal dynamic pricing strategies for high-occupancy/toll lanes

This paper proposes a self-learning approach to determine optimal pricing strategies for high-occupancy/toll lane operations. The approach learns recursively motorists’ willingness to pay by mining the loop detector data, and then specifies toll rates to maximize the freeway’s throughput while ensuring a superior travel service to the users of the toll lanes. In determination of the tolls, a multi-lane hybrid traffic flow model is used to explicitly consider the impacts of the lane-changing behaviors before the entry points of the toll lanes on throughput and travel time. Simulation experiments are conducted to demonstrate and validate the proposed approach, and provide insights on when to convert high-occupancy lanes to toll lanes.

Mixing Microscopic and Macroscopic Representations of Traffic Flow: Hybrid Model Based on Lighthill–Whitham–Richards Theory

The hybrid traffic flow model, coupling a microscopic (vehicle-based) and a macroscopic (flow-based) representation of traffic flow, may be a useful tool to better understand the relationships between the various types of representation. It can also be a basis for implementing various model extensions, which may be easier with using one type of representation or the other. The hybrid model presented here combines a flow and a vehicular representation of the same model, which is the classical Lighthill–Whitham–Richards model. The use of a simple and unique model makes it possible to focus on the specific problems raised by translating boundary conditions from vehicular to flow formulation and conversely. This translation is made in order to ensure the conservation of flow and proper transmission of information both downstream and upstream and to minimize the perturbations induced by transitions between a continuous and a discrete representation of flow. The resulting model is shown to have good properties, particularly concerning congestion propagation and flow smoothing at the interfaces between the two models.