Traffic Flow Behavior Research Articles

Simulation study of traffic circle intersection with traffic lights

Using the Nagel-Schreckenberg model, we investigate the flow characteristics in a traffic circle system, where the entry lanes are controlled by traffic lights operating in a fixed-time ([Formula: see text]. We considered four different strategies to control traffic coming from [Formula: see text] entry lanes. We found that depending on the strategy used, four distinct traffic phases can appear in the circulating lane of the traffic circle, namely free flow, congestion, maximum current, and gridlock. Also, we investigate the origin of the gridlock phase in both cases (i.e. with/without traffic lights). Furthermore, the lengths of queues of stopped vehicles in the entry lanes were studied. We found that the traffic flow behavior on the exit/entry lanes depends strongly on the flow characteristics at the circulating lane as well as traffic lights strategy. To improve the operation of the traffic circle system, we have studied the time delay between the traffic lights to switch where all entry lanes go red, which allowing vehicles to clear the circulating lane.

A macroscopic traffic model based on weather conditions**Project supported by Higher Education Commission, Pakistan/National Center of Big Data and Cloud Computing.

A traffic model based on the road surface conditions during adverse weather is presented. The surface of a road is affected by snow, compacted snow, and ice, which affects the traffic behavior. In this paper, a new macroscopic traffic flow model based on the transition velocity distribution is proposed which characterizes traffic alignment under adverse weather conditions. Two examples are considered to illustrate the effect of the transition velocity behavior on traffic velocity and density. Simulation results are presented which show that this model provides a more accurate characterization of traffic flow behavior than the well known Whitham–Payne model. The proposed model can be used to reduce accidents and improve road safety during adverse weather conditions.

Discretionary lane-changing behavior: empirical validation for one realistic rule-based model

ABSTRACTIn this paper, we discuss the mechanisms for discretionary lane-changing behavior in traffic flow. NGSIM video data are used to check the validity of different lane-changing rules, and 373 lane changes at 4 locations in US-101 highway are analyzed. We find that the classical lane-changing rules of rule-based model cannot explain many cases in the empirical dataset. Therefore, we propose one new decision rule, comparing the position after a time horizon of several seconds without a lane-change. This rule can be described as “to have a further position within 9 seconds”. The tests on NGSIM data show that this rule can explain most (76%) of the lane-changing cases. Besides, some data when lane changes do not occur are also studied. We find that most (81%) of non-lane-changing vehicles do not fulfill the new rule. Thus, it can be considered as one sufficient and necessary condition for discretionary lane-changing.

Integrating ultra‐fast charging stations within the power grids of smart cities: a review

Plug-in electric vehicles (PEVs) have become a key factor driving towards smart cities, which allow for higher energy efficiency and lower environmental impact across urban sectors. Industry vision for future PEV includes the ability to recharge a vehicle at a speed comparable to traditional gas refuelling, i.e. <3 min. per vehicle. Such a technology, referred to as ultra-fast charging (UFC), has drawn much interest from research and industry. However, UFC poses unprecedented challenges to existing electricity supply infrastructure due to its large power density, impulsive, and stochastic load characteristics. Planning the locations and electric capacities of UFC stations is critical to preventing detrimental impacts. In particular, efforts must be made of mitigate grid asset depreciation, grid instabilities, and deteriorated power quality. The authors first review planning methods for conventional charging stations. Next, they discuss outlooks for UFC planning solutions by drawing an analogy with renewable energy (RE) source planning. This analogy is based on the similar power density and stochastic characteristics of RE and UFC. While this study mainly focuses on UFC planning from the power grid perspective, other urban aspects, including traffic flow and end-user behaviour, are examined for feasible UFC integration within smart cities.

An extended car-following model incorporating the effects of lateral gap and gradient

This study proposes a new car-following (CF) model to capture the effects of road geometry characteristics on traffic flow behavior. In particular, an extended CF model is proposed incorporating the effects of both lateral gap and gradient. Stability of the proposed model is analyzed using the perturbation method to obtain the stability condition. Numerical experiments are performed for comparisons among the full velocity difference (FVD) model, two-sided lateral gaps based full velocity difference (TSFVD) model, and the proposed model. Results from numerical experiments demonstrate that, with the increase of the slope, the stability region of the proposed model will be enlarged in uphill scenario, while it will be reduced in downhill scenario, respectively. Also, the proposed model is effective to rapidly dissipate the effect of a perturbation such as a sudden acceleration or deceleration from the lead vehicle. In addition, the CF behavior of traffic flow can be characterized by the proposed model in terms of the space headway profile in uphill and downhill scenarios. That is, with the increase of the slope, the average space headway of the traffic flow will be decreased in uphill scenario, while it will be increased in downhill scenario, respectively. These findings can be generalized to the scenario of traffic system with gradient and lateral gap.

Traffic flow behavior at a single-lane urban roundabout

In this paper, we propose a stochastic cellular automata model to study the traffic behavior at a single-lane roundabout. Vehicles can enter the interior lane or exit from it via [Formula: see text] intersecting lane, the boundary conditions are stochastic. The traffic is controlled by a self-organized scheme. It has turned out that depending on the rules of insertion to the roundabout, five distinct traffic phases can appear, namely, free flow, congestion, maximum current, jammed and gridlock. The transition between the free flow and the gridlock is forbidden. The density profiles are used to study the traffic pattern at the interior lane of the roundabout. In order to quantify the interactions between vehicles in the interior lane of the roundabout, the velocity correlation coefficient (VCC) is also studied. Besides, the spatiotemporal diagrams corresponding to the entry/exit lanes are derived numerically. Furthermore, we have investigated the effect of displaying signal ([Formula: see text], as the [Formula: see text] decreases, the maximum current increases at the expense of the free flow and the jamming phase. Finally, we have investigated the effect of the braking probability [Formula: see text] on the interior lane of the roundabout. We have found that the increase of [Formula: see text] raises the spontaneous jam formation on the ring. Thus, enlarges the maximum current and the jamming phase while the free flow phase decreases.

Bi-directional movement characteristics of Camponotus japonicus ants during nest relocation.

Foraging and nest relocation forming a bi-directional traffic of outbound and inbound individuals in one-lane organization are two main activities in an ant's life. In this paper, we conducted an experiment on nest relocation of loaded and unloaded ants, moving back and forth between the old nest and the new one. In the experiment, we observed both uni- and bi-directional traffic flow. The headway-speed relationships indicate that the ants showed the same sensitivity to the distance headway in the two types of flow. For bi-directional traffic flow, head-on encounters and giving-way behavior between ants moving in opposing directions were a common occurrence. It took one unloaded ant 2.61s to solve a head-on encounter with another unloaded ant. Compared with unloaded ants, loaded ants had a lower moving speed, but were less likely to be impacted by a head-on encounter. In the observation region, both sudden stop and head-on encounters contained two phases: deceleration and acceleration. Our analysis indicates that the relaxation time in the deceleration process is less than that in the acceleration process. The reduction of movement efficiency of encountering two discontinuous ants is larger than that when encountering two successive ants (0.18). This is owing to the absence of head-on encounters with following ants. The bi-directional traffic of ants under experimental conditions investigated in this study may inform future studies of high-efficiency movement in collective behavior and traffic systems.

Comparative Analysis Of K-Means Data Mining and Outlier Detection Approach for Network-Based Intrusion Detection

New kind of intrusions causes deviation in the normal behaviour of traffic flow in computer networks every day. This study focused on enhancing the learning capabilities of IDS to detect the anomalies present in a network traffic flow by comparing the k-means approach of data mining for intrusion detection and the outlier detection approach. The k-means approach uses clustering mechanisms to group the traffic flow data into normal and abnormal clusters. Outlier detection calculates an outlier score (neighbourhood outlier factor NOF) for each flow record, whose value decides whether a traffic flow is normal or abnormal. These two methods were then compared in terms of various performance metrics and the amount of computer resources consumed by them. Overall, k-means was more accurate and precise and has better classification rate than outlier detection in intrusion detection using traffic flows. This will help systems administrators in their choice of IDS.

Traffic flow behavior at un-signalized intersection with crossings pedestrians

Mixed traffic flux composed of crossing pedestrians and vehicles extensively exists in cities. To study the characteristics of the interference traffic flux, we develop a pedestrian-vehicle cellular automata model to present the interaction behaviors on a simple cross road. By realizing the fundamental parameters (i.e. injecting rates α1, α2, the extracting rate β and the pedestrian arrival rate αP), simulations are carried out. The vehicular traffic flux is calculated in terms of rates. The effect of the crosswalk can be regarded as a dynamic impurity. The system phase diagrams in the (α1,αP) plane are built. It is found that the phase diagrams consist essentially of four phases namely Free Flow, Congested, Maximal Current and Gridlock. The value of the Maximal current phase depends on the extracting rate β, while the Gridlock phase is achieved only when the pedestrians generating rate is higher than a critical value. Furthermore, the effect of vehicles changing lane (Pch1,Pch2) and the location of the crosswalk XP on the dynamic characteristics of vehicles flow are investigated. It is found that traffic situation in the system is slightly enhanced if the location of the crosswalks XP is far from the intersection. However, when Pch1, Pch2 increase, the traffic becomes congested and the Gridlock phase enlarges.

Briefing: High-performance computing for city-scale modelling and simulations

Smarter cities and infrastructure are essential if the world is to respond effectively to the critical challenges it faces. As of 2008, and for the first time in human history, more than half of the world's population now live in cities. Yet cities increasingly need to be able to do more with less, to provide for the well-being of their citizens in a truly sustainable way. City-scale simulations are becoming a possibility with advancements in the computing hardware and software technologies. Recent advancements in distributed scaling using Apache Spark is exemplified through a case-study on simulating the traffic flow behaviour of London at per-hour time resolution. The case-study on the response of ground and structures in central Tokyo shows the advancements in multigrid techniques and Finite Element simulations. This paper discusses the advancements and challenges in high-performance computing (hardware, algorithms, software, and visualisation techniques) in achieving the possibility of real-time city-scale simulations.

The investigation of the lateral interaction effect's on traffic flow behavior under open boundaries

In this paper, an open boundaries traffic flow system is studied by taking into account the lateral interaction with spatial defects. For a random defects distribution, if the vehicles velocities are weakly correlated, the traffic phases can be predicted by considering the corresponding inflow and outflow functions. Conversely, if the vehicles velocities are strongly correlated, a phase segregation appears inside the system's bulk which induces the maximum current appearance. Such velocity correlation depends mainly on the defects densities and the probabilities of lateral deceleration. However, for a compact defects distribution, the traffic phases are predictable by using the inflow in the system beginning, the inflow entering the defects zone and the outflow function.

On node models for high-dimensional road networks

Macroscopic traffic models are necessary for simulation and study of traffic’s complex macro-scale dynamics, and are often used by practitioners for road network planning, integrated corridor management, and other applications. These models have two parts: a link model, which describes traffic flow behavior on individual roads, and a node model, which describes behavior at road junctions. As the road networks under study become larger and more complex — nowadays often including arterial networks — the node model becomes more important. Despite their great importance to macroscopic models, however, only recently have node models had similar levels of attention as link models in the literature. This paper focuses on the first order node model and has two main contributions. First, we formalize the multi-commodity flow distribution at a junction as an optimization problem with all the necessary constraints. Most interesting here is the formalization of input flow priorities. Then, we discuss a very common “conservation of turning fractions” or “first-in-first-out” (FIFO) constraint, and how it often produces unrealistic spillback. This spillback occurs when, at a diverge, a queue develops for a movement that only a few lanes service, but FIFO requires that all lanes experience spillback from this queue. As we show, avoiding this unrealistic spillback while retaining FIFO in the node model requires complicated network topologies. Our second contribution is a “partial FIFO” mechanism that avoids this unrealistic spillback, and a (first-order) node model and solution algorithm that incorporates this mechanism. The partial FIFO mechanism is parameterized through intervals that describe how individual movements influence each other, can be intuitively described from physical lane geometry and turning movement rules, and allows tuning to describe a link as having anything between full FIFO and no FIFO. Excepting the FIFO constraint, the present node model also fits within the well-established “general class of first-order node models” for multi-commodity flows. Several illustrative examples are presented.

Network-wide adaptive tolling for connected and automated vehicles

This article proposes Δ-tolling, a simple adaptive pricing scheme which only requires travel time observations and two tuning parameters. These tolls are applied throughout a road network, and can be updated as frequently as travel time observations are made. Notably, Δ-tolling does not require any details of the traffic flow or travel demand models other than travel time observations, rendering it easy to apply in real-time. The flexibility of this tolling scheme is demonstrated in three specific traffic modeling contexts with varying traffic flow and user behavior assumptions: a day-to-day pricing model using static network equilibrium with link delay functions; a within-day adaptive pricing model using the cell transmission model and dynamic routing of vehicles; and a microsimulation of reservation-based intersection control for connected and autonomous vehicles with myopic routing. In all cases, Δ-tolling produces significant benefits over the no-toll case, measured in terms of average travel time and social welfare, while only requiring two parameters to be tuned. Some optimality results are also given for the special case of the static network equilibrium model with BPR-style delay functions.

Traffic flow behavior at a single lane traffic circle

In this paper, we propose a stochastic cellular automata (CA) model to study traffic dynamic at a single-lane traffic circle of [Formula: see text] entry/exit points. The boundaries are controlled by the injecting rates [Formula: see text], [Formula: see text] and the extracting rate [Formula: see text]. Both the cases with and without the splitter islands of width [Formula: see text] are considered. The phase diagrams in the space [Formula: see text] are constructed and the density profiles are also investigated. The variation of the phase diagram with the traffic circle size [Formula: see text], the number of entry point [Formula: see text], and the time needed for drivers to change their exit willingly [Formula: see text] is studied. The results show that the phase diagram in both cases consists essentially of three phases namely free flow, congestion and gridlock. However, the large sized traffic circle shows better performance in the free flow phase, in contrary, the increase of [Formula: see text] enlarges the congestion and the gridlock phases. We have also found that the decrease of [Formula: see text] enhances the traffic flow situation in the traffic circle. Furthermore, as the [Formula: see text] increases, the free flow phase enlarges while the congestion and gridlock ones shrink.

An extended microscopic traffic flow model based on the spring-mass system theory

This study proposes a new microscopic traffic flow model based on the spring-mass system theory. In particular, considering the similarity between the acceleration or deceleration behavior in traffic flow and the scaling properties of a spring, a car-following (CF) model is proposed based on the fundamental physical law of the spring-mass system. Stability of the proposed model is analyzed using the perturbation method to obtain the stability condition. Numerical experiments are performed through simulation. The results demonstrate the proposed model can capture the characteristic of propagation backwards of disturbance in traffic flow. In addition, the findings of this study provide insights in modeling traffic flow from the mechanical system theory perspective.

A model of pedestrian delay at unsignalized intersections in urban networks

Delay is an important performance measure for pedestrian crossings considering their interactions with other road users. This study provides an improved analytical model to mathematically estimate pedestrian delay using renewal theory, which considers driver yielding and vehicle platooning. A generalized model is first provided to accommodate different traffic flow and driver behavior assumptions. Then the proposed model is developed on the basis of a mixture of free traffic and platooned traffic with consideration of driver yielding behaviors to better replicate field conditions in an urban setting. A second application using the HCM 2010 assumptions is also derived to compare it to the HCM 2010 model. Lastly, field data were collected and used for validation from two locations: Gainesville, FL and Washington, D.C. A simulation via MATLAB is performed to evaluate the model results for a variety of cases. The comparisons to the field data as well as the simulation confirm the applicability and accuracy of the proposed model. It is also found that the current HCM 2010 model overestimates the pedestrian delay compared with field data.

Application of AHP-GIS Technology to Assess Congestion Vulnerability, a Case Study of Ranchi City, India

Urban traffic congestion is a multi-dimensional phenomenon and therefore, is sensitive to certain influencing factors behaving in a random manner. Consequently, the possibility of a route characterized by smooth flow of traffic becoming congested cannot be ruled out. The present research investigation attempts to categorize different routes of the study area in terms of their degree of congestion vulnerability. Average Speed (AS), Delay Ratio of Average Speed (DRAS), Stopped Time (ST), Stopped Time Gradient (STG), and Absolute Deviation in Congestion Index Value (ADCIV) were identified as the potential influencing factors. The AHP was employed to rank the importance of the aforementioned influencing factors in triggering congestion that can sometimes lead to traffic deadlock. On the other hand, the GIS Weighted Sum Overlay technique was employed to determine the integrated impact of the influencing factors on the behavior of traffic flow. The results showed close agreement with the real scenario of the traffic congestion observed in the field.

The structure of user equilibria: Dynamic coevolutionary simulations vs. cyclically expanded networks

Abstract: A variety of approaches exist that model traffic time-dependently. While all approaches have their advantages and disadvantages but have to find a balance between modeling traffic as realistic as possible and being still manageable in combinational terms. While transport simulations are efficient in evaluating user equilibria in large scale scenarios, their potential to be used for optimization is limited. On the other hand, analytical formulations like models based on cyclically time-expanded networks can be used to optimize traffic flow, but are not suitable for large scale scenarios. By optimizing the network structure in a mathematical model and evaluating its effect in a more realistic transport simulation, two models can benefit from each other. Detailed knowledge about model properties and differences in traffic flow behavior help to understand results and potential difficulties of such a model combination. In this paper, properties of two such models are compared regarding traffic flow modeling. It is shown that the set of user equilibria in both models and, therefore, the resulting route distributions can be structurally different.

Stochastic modelling for traffic flow: a review

The stochastic process and estimation from the review paper for the breakdown flow contains two random flow breakdowns variables. Breakdown flow happens when the two random variables, breakdown speed and breakdown duration, occurs at the homogeneous level. The model follows microscopic model which are homogeneous and continues in a heterogeneous level for a macroscopic model. The models are based from the vehicle changes at different levels of their speed. The mathematical process used in order to obtain the random variables are Weibull probability distribution for the breakdown speed and also the probability density function for the breakdown duration as an estimation also known as the hazard function. Simulation using Monte Carlo method will compute the random sampling from the breakdown variables and breakdown duration into a macroscopic model. The results will compare the actual data collected from Caltrans in 2007 and the mathematical model and simulation will be the same traffic flow behaviour and characteristics.

Stochastic modelling for traffic flow: a review

The stochastic process and estimation from the review paper for the breakdown flow contains two random flow breakdowns variables. Breakdown flow happens when the two random variables, breakdown speed and breakdown duration, occurs at the homogeneous level. The model follows microscopic model which are homogeneous and continues in a heterogeneous level for a macroscopic model. The models are based from the vehicle changes at different levels of their speed. The mathematical process used in order to obtain the random variables are Weibull probability distribution for the breakdown speed and also the probability density function for the breakdown duration as an estimation also known as the hazard function. Simulation using Monte Carlo method will compute the random sampling from the breakdown variables and breakdown duration into a macroscopic model. The results will compare the actual data collected from Caltrans in 2007 and the mathematical model and simulation will be the same traffic flow behaviour and characteristics.