Jam Emergence Research Articles

The Onset of a Blocking Event as a “Traffic Jam”: Characterization with Ensemble Sensitivity Analysis

Abstract Recently, Nakamura and Huang proposed a theory of blocking onset based on the budget of finite-amplitude local wave activity on the midlatitude waveguide. Blocks form in their idealized model due to a mechanism that also describes the emergence of traffic jams in traffic theory. The current work investigates the development of a winter European block in terms of finite-amplitude local wave activity to evaluate the possible relevance of the “traffic jam” mechanism for the flow transition. Two hundred members of a medium-range ensemble forecast of the blocking onset period are analyzed with correlation- and cluster-based sensitivity techniques. Diagnostic evidence points to a traffic jam onset on 17 December 2016. Block development is sensitive to upstream Rossby wave activity up to 1.5 days prior to its initiation and consistent with expectations from the idealized theory. Eastward transport of finite-amplitude local wave activity in the southern part of the block is suppressed by nonlinear flux modification from the large-amplitude blocking pattern, consistent with the expected obstruction in the traffic jam model. The relationship of finite-amplitude local wave activity and its zonal flux as mapped by the ensemble exhibits established characteristics of a traffic jam. This study suggests that the traffic jam mechanism may play an important role in some cases of blocking onset and more generally that applying finite-amplitude local wave activity diagnostics to ensemble data is a promising approach for the further examination of individual onset events in light of the Nakamura and Huang theory. Significance Statement Blocking is an occasional phenomenon in the mid- and high-latitude atmosphere characterized by the stalling of weather systems. Episodes of blocking are linked to extreme weather but their occurrence is not completely understood. A recent theory suggests that blocks may form in the jet stream like traffic jams on a highway. The onset mechanism contained in the theory could explain why forecasts of blocking are sometimes poor. In this work, we investigate the formation of a 2016 European winter block in the context of the traffic jam theory. Though questions remain regarding the implications for forecast uncertainty, our findings strongly support the notion of a traffic jam onset.

Understanding sudden traffic jams: From emergence to impact

Road traffic jams are a major problem in most cities of the world, resulting in massive delays, increased fuel wastage, and monetary and productivity losses. Unlike conventional computer networks, which experience congestion due to excessive traffic, road transportation networks can experience traffic jams over prolonged periods due to traffic bursts over short time scales that push the traffic density beyond a threshold jam density. We observe that the emergence of such jams can happen over a very short duration, hence we term them as sudden traffic jams. We provide a formalism for understanding the phenomena of sudden traffic jams and show evidence of its existence using loop detector data from New York City. Further, we show the signature of sudden jams when observed at hourly resolution. We also provide a method to compute the traffic curve in a situation where we do not have access to fine-grained flow and density information. With this method, using only hourly speed data from Uber, we compute traffic curves for the road segments in Nairobi, São Paulo, and New York City, which is, by our knowledge, the first attempt to do so for signalized road networks. Running our analysis on the Uber movement speed data for the three cities, we show numerous instances of jams that last several hours, and sometimes as long as 2–3 days. Empirically, we find that Nairobi experiences 3x the mean jam time per road segment as compared to São Paulo and New York City. Based on key development metrics, we find that the ratio of traffic load per road segment for São Paulo, New York City, and Nairobi is approximately 1:2:3. We propose that chaotic driving patterns and traffic mismanagement in the developing world cities lead to tighter traffic curves, more intense jams and overall lower road capacity utilization, which explains the observed data. We posit that the problem of traffic congestion in developing countries cannot be solved entirely by building new infrastructure, but also requires smart management of existing road infrastructure.

On the emergence of traffic jams in a stochastic traffic flow driven by additive and multiplicative white Gaussian noise processes

Understanding the influence of random phenomena on the emergence of jams in vehicular traffic flows is a fundamental question in the study of traffic flow dynamics. Motivated by the fact that additive and multiplicative white Gaussian noise processes represent fundamentally distinct sources of randomness that can engender qualitatively different patterns in the dynamics of traffic flow, here we compare and contrast the influences of those two distinct stochastic processes on the formation of traffic jams. Analyzing the macroscopic dynamics of spatially homogeneous single-lane traffic flow using a car distribution function that evolves according to a Fokker–Planck type equation, we first obtain the equilibrium distribution function in closed form for traffic flow driven by additive as well as multiplicative white Gaussian noise. We then derive the mean first passage time (MFPT) for both cases and also present results that elucidate the influence of varying noise strength on both the equilibrium distribution function and the MFPT. Additionally, we obtain fundamental diagrams corresponding to speed versus flux of vehicle flow for both cases that further highlight the distinct effects of the two types of noise. In summary, the results underscore the contrasting influences of additive and multiplicative noise processes on the emergence of traffic jams and thereby contribute to advancing our understanding of this aspect of stochastic traffic flow. The findings could also help improve our understanding of how randomness affects traffic flows that are a combination of human and self-driven vehicles.

Statistical physics of the development of Kerner's synchronized-to-free-flow instability at a moving bottleneck in vehicular traffic.

With the use of simulations of a stochastic microscopic traffic model in the framework of the three-phase traffic theory, we have revealed the statistical physics of a traffic flow instability with respect to a transition from synchronized flow (S) to free flow (F) (Kerner's S→F instability) at a moving bottleneck (MB) occurring through a slow-moving vehicle in vehicular traffic. We have found that the S→F instability can occur at the MB more frequently than at an on-ramp bottleneck. From a comparison of the occurrence of the S→F instability at the MB and on-ramp bottleneck at the same probability of traffic breakdown and the same flow rate it has been found that, whereas the frequency of the S→F instability at the on-ramp bottleneck barely changes, the larger the velocity of the MB, the more frequently the S→F instability occurs at the MB. Contrarily, when the MB velocity decreases considerably, then rather than the S→F instability, in synchronized flow at the MB the classical traffic flow instability leading to the emergence of wide-moving jams (S→J instability) occurs. It has been found that the physics of the intensification of the S→F instability at the MB with the increase in the MB velocity is associated with the increase in the mean space gap (mean time headway) between vehicles in synchronized flow. For this reason, when the MB velocity increases, there is an MB velocity at which the S→F instability dominates the S→J instability: The MB velocity influences considerably on the competition between the S→F and classical traffic flow instabilities in synchronized flow.

Infrastruktur Jalan Sebagai Lahan Parkir Semarang Bridge Fountain Sungai Banjir Kanal Barat (BKB)

New tourism in Semarang City raises a problem, traffic congestion. New tourism provided in Semarang City by utilizing the existing potensial is Semarang Bridge Fountain. Semarang Bridge Fountain is a dancing fountain located in Semarang City, which inaugurated end of 2018. Located on the West Canal Flood River and becomes new icon in Semarang City. The existence of Semarang Bridge Fountain affects the surrounding road infrastructure. Namely the emergence of traffic jams when the fountain attraction takes place caused by many vehicles parked on Jenderal Sudirman street. The purpose of this research to analyze road infrastructure can be used as parking lots. The method used in this research is descriptive qualitative to explain state of West Canal Flood River. The results of this research shows that parking area became one of problems that arise during event. Many people don’t know location of official parking area provided by City Government. Congestion arises because the community gathers at one point during the event and also does not know the official parking location. From the results of analysis can be concluded need for delivery of official parking location information for community, need for firmness of official parties related arrangement of parking, also the addition of facilities so that activities aren’t concentrated at one point.

Empirical evidence for a jamming transition in urban traffic

Understanding the mechanisms leading to the formation and the propagation of traffic jams in large cities is of crucial importance for urban planning and traffic management. Many studies have already considered the emergence of traffic jams from the point of view of phase transitions, but mostly in simple geometries such as highways for example or in the framework of percolation where an external parameter is driving the transition. More generally, empirical evidence and characterization for a congestion transition in complex road networks are scarce, and here, we use traffic measures for Paris (France) during the period 2014-2018 for testing the existence of a jamming transition at the urban level. In particular, we show that the correlation function of delays due to congestion is a power law (with exponent η ≈ 0.4) combined with an exponential cut-off ξ. This correlation length is shown to diverge during rush hours, pointing to a jamming transition in urban traffic. We also discuss the spatial structure of congestion and identify a core of congested links that participate in most traffic jams and whose structure is specific during rush hours. Finally, we show that the spatial structure of congestion is consistent with a reaction-diffusion picture proposed previously.

A novel lattice hydrodynamic model considering the optimal estimation of flux difference effect on two-lane highway

The optimal estimation of flux difference effect is introduced to construct a new lattice hydrodynamic model for two-lane highway. Through linear stability analysis, it is found that the new consideration plays an important influence upon the stability of two-lane traffic flow. Moreover, the mKdV equation near the critical point is derived from nonlinear analysis, which describes the propagation behavior of traffic jam in two-lane traffic system. Simulation results show that the stability of two-lane traffic system can be increased and the emergence of traffic jams are effectively relieved by the optimal estimation of flux difference effect, which is in good agreement with theoretical analysis.

Effect of optimal estimation of flux difference information on the lattice traffic flow model

Abstract In this paper, a new lattice model is proposed by considering the optimal estimation of flux difference information. The effect of this new consideration upon the stability of traffic flow is examined through linear stability analysis. Furthermore, a modified Korteweg–de Vries (mKdV) equation near the critical point is constructed and solved by means of nonlinear analysis method, and thus the propagation behavior of traffic jam can be described by the kink–antikink soliton solution of the mKdV equation. Numerical simulation is carried out under periodical condition with results in good agreement with theoretical analysis, therefore, it is verified that the new consideration can enhance the stability of traffic systems and suppress the emergence of traffic jams effectively.

CAR FOLLOWING TECHNIQUES: THE ROLE OF THE HUMAN FACTOR RECONSIDERED

Engineering and psychophysiological car following models emerge in the late 1950s (Saifuzzaman & Zheng, 2014). Such models differ in their ground concepts and explanatory mechanisms, but both assume a fundamental tenet: following each other, drivers invariably attempt to couple, keeping safety distance. More recent models focus on the spontaneous emergence of traffic jams that results from the properties of a system of interacting vehicles (i.e., without bottlenecks). In an experimental setting Sugiyama et al., (2008) have successfully recreated the conditions that allow the observation of the typical soliton wave going backwards through several car clusters. When certain speed, density and inter-vehicular distance join, so do traffic jams. Some of us have built upon these and other factors (e.g., wave movement in nature) exploring the mathematical properties of a system with three incognita that also needs three variables to be solved (Melchor & Sanchez, 2014). Two canonical car-following techniques emerge as a consequence: Driving to keep safety Distance (DD) vs Inertia (DI). Also a basic question: can drivers actually understand and follow either way, or do they stick to a basic normative driving behavior? This paper summarizes the results after three experimental studies done with a driving simulator. Several performance measures from individual drivers (accelerations, decelerations, average speed, distance to leader, and so on) were taken. As an overall indicator, results consistently announce in the three studies that DI trips consume less fuel (about 20%) than DD ones. DOI: http://dx.doi.org/10.4995/CIT2016.2016.3406

Emergence of jams in the generalized totally asymmetric simple exclusion process.

The generalized totally asymmetric exclusion process (TASEP) [J. Stat. Mech. (2012) P05014] is an integrable generalization of the TASEP equipped with an interaction, which enhances the clustering of particles. The process interpolates between two extremal cases: the TASEP with parallel update and the process with all particles irreversibly merging into a single cluster moving as an isolated particle. We are interested in the large time behavior of this process on a ring in the whole range of the parameter λ controlling the interaction. We study the stationary state correlations, the cluster size distribution, and the large-time fluctuations of integrated particle current. When λ is finite, we find the usual TASEP-like behavior: The correlation length is finite; there are only clusters of finite size in the stationary state and current fluctuations belong to the Kardar-Parisi-Zhang universality class. When λ grows with the system size, so does the correlation length. We find a nontrivial transition regime with clusters of all sizes on the lattice. We identify a crossover parameter and derive the large deviation function for particle current, which interpolates between the case considered by Derrida-Lebowitz and a single-particle diffusion.

Multiple optimal current difference effect in the lattice traffic flow model

Kerner and Konhäuser study moving jam dynamics first discovered in 1993 in Ref. 1. In light of their previous work, a new lattice hydrodynamic model is presented with consideration of the effect of multiple optimal current difference. To investigate the influences of new consideration on traffic jams, the linear stability analysis of the new model is conducted by employing the linear stability theory. Theoretical analysis result shows that the new consideration can stabilize traffic flow. By means of nonlinear analysis method, a modified Korteweg–deVries (mKdV) equation near the critical point is constructed and solved. The propagation behavior of traffic jam can thus be described by the kink–antikink soliton solution for the mKdV equation. Numerical simulation result shows that the effect of the multiple optimal current differences can suppress the emergence of traffic jams and the result is in good agreement with the analytical results.

Phase transition in traffic jam experiment on a circuit

The emergence of a traffic jam is considered to be a dynamical phase transition in a physics point of view; traffic flow becomes unstable and changes phase into a traffic jam when the car density exceeds a critical value. In order to verify this view, we have been performing a series of circuit experiments. In our previous work (2008 New J. Phys. 10 033001), we demonstrated that a traffic jam emerges even in the absence of bottlenecks at a certain high density. In this study, we performed a larger indoor circuit experiment in the Nagoya Dome in which the positions of cars were observed using a high-resolution laser scanner. Over a series of sessions at various values of density, we found that jammed flow occurred at high densities, whereas free flow was conserved at low densities. We also found indications of metastability at an intermediate density. The critical density is estimated by analyzing the fluctuations in speed and the density–flow relation. The value of this critical density is consistent with that observed on real expressways. This experiment provides strong support for physical interpretations of the emergence of traffic jams as a dynamical phase transition.

Simulating synchronized traffic flow and wide moving jam based on the brake light rule

A new cellular automaton (CA) model based on brake light rules is proposed, which considers the influence of deterministic deceleration on randomization probability and deceleration extent. To describe the synchronized flow phase of Kerner’s three-phase theory in accordance with empirical data, we have changed some rules of vehicle motion with the aim to improve speed and acceleration vehicle behavior in synchronized flow simulated with earlier cellular automaton models with brake lights. The fundamental diagrams and spatial–temporal diagrams are analyzed, as well as the complexity of the traffic evolution, the emergence process of wide moving jam. Simulation results show that our new model can reproduce the three traffic phases: free flow, synchronized flow and wide moving jam. In addition, our new model can well describe the complexity of traffic evolution: (1) with initial homogeneous distribution and large densities, the traffic will evolve into multiple steady states, in which the numbers of wide moving jams are not invariable. (2) With initial homogeneous distribution and the middle range of density, the wide moving jam will emerge stochastically. (3) With initial mega-jam distribution and the density close to a point with the low value, the initial mega-jam will disappear stochastically. (4) For the cases with multiple wide moving jams, the process is analyzed involving the generation of narrow moving jam due to “pinch effect”, which leads to wide moving jam emergence.

Criticality in Dynamic Arrest: Correspondence between Glasses and Traffic

Dynamic arrest is a general phenomenon across a wide range of dynamic systems including glasses, traffic flow, and dynamics in cells, but the universality of dynamic arrest phenomena remains unclear. We connect the emergence of traffic jams in a simple traffic flow model directly to the dynamic slowing down in kinetically constrained models for glasses. In kinetically constrained models, the formation of glass becomes a true (singular) phase transition in the limit T→0. Similarly, using the Nagel-Schreckenberg model to simulate traffic flow, we show that the emergence of jammed traffic acquires the signature of a sharp transition in the deterministic limit p→1, corresponding to overcautious driving. We identify a true dynamic critical point marking the onset of coexistence between free flowing and jammed traffic, and demonstrate its analogy to the kinetically constrained glass models. We find diverging correlations analogous to those at a critical point of thermodynamic phase transitions.

Transition mode of long distance water delivery project before freezing in winter

In order to automatically and safely control long distance water delivery projects in winter, there is a need for a reasonable and feasible transition mode to avoid the emergence of ice jam. Based on open canal hydraulics, a mathematical model of canal system operated by constant downstream depth method is developed. The principle of combining feed-forward control of discharges with feedback control of water level is adopted for operation of check gates and a simulation model of multiple serial canal sections is established. Also, reasonable parameters of proportional-integral (PI) controller and logical dead band are obtained by trial and optimizing. The model is applied to simulate the operation process of the canal sections part of the main canal of the middle route of the South-to-North Water Transfer Project in China. Flow velocities are reduced to less than 0.4 m/s by decreasing discharges of canal pools and turnouts in terms of 3 days' cold current forecast in advance. As a result, discharge in canal was reduced from 70% designed capacity to less than 30%, which is a big challenge for the controller. This paper tests the suggested transition mode from open-channel water transfer state to a low flow ice-forming state at the MATLAB platform, and the results show that this model can achieve the expected goals.

Jam emergence on a circular track in a car-following model

A discrete car-following model (a linear version of the Optimal Velocity Model) is evaluated for vehicles moving on a circular track. The model imposes physical limits on acceleration and deceleration. Braking is treated using a version of Gipps’ safety condition and incorporates the reaction time of drivers. Simulations with two versions of the model, one with a unique velocity–headway relationship and another with a non-unique relationship, show spontaneous emergence of a jam in agreement with the experiment of Sugiyama et al. [Y. Sugiyama, M. Fukui, M. Kikuchi, K. Hasebe, A. Nakayama, K. Nishinari, S. Tadaki, S. Yukawa, New J. Phys. 10 (2008) 033001].

A Study of Phase Transitions on Multilane Roads in the Framework of Three-Phase Traffic Theory

A numerical study of phase transitions in traffic flow on multilane roads in the framework of three-phase traffic theory is presented. It was found that when vehicle merging became easier at a bottleneck, wide moving jams emerged more frequently in synchronized flow upstream of the bottleneck. Depending on the traffic phase and lane-changing probability, lane changing was responsible for qualitatively opposite effects, such as congested traffic dissolution or, in contrast, the emergence of nuclei for traffic breakdown and moving jam emergence. It was found that at a sequence of closely located adjacent bottlenecks, phase transitions between different road lanes resulted in nonregular spatiotemporal traffic dynamics.

Traffic jams without bottlenecks—experimental evidence for the physical mechanism of the formation of a jam

A traffic jam on a highway is a very familiar phenomenon. From the physical viewpoint, the system of vehicular flow is a non-equilibrium system of interacting particles (vehicles). The collective effect of the many-particle system induces the instability of a free flow state caused by the enhancement of fluctuations, and the transition to a jamming state occurs spontaneously if the average vehicle density exceeds a certain critical value. Thus, a bottleneck is only a trigger and not the essential origin of a traffic jam. In this paper, we present the first experimental evidence that the emergence of a traffic jam is a collective phenomenon like ‘dynamical’ phase transitions and pattern formation in a non-equilibrium system. We have performed an experiment on a circuit to show the emergence of a jam with no bottleneck. In the initial condition, all the vehicles are moving, homogeneously distributed on the circular road, with the same velocity. The average density of the vehicles is prepared for the onset of the instability. Even a tiny fluctuation grows larger and then the homogeneous movement cannot be maintained. Finally, a jam cluster appears and propagates backward like a solitary wave with the same speed as that of a jam cluster on a highway.

Study of Freeway Speed Limit Control Based on Three-Phase Traffic Theory

Speed limit control at freeway bottlenecks is numerically studied on the basis of the Kerner-Klenov microscopic stochastic traffic flow model in the context of Kerner's three-phase traffic theory. It turns out that in some cases speed limit control, rather than preventing traffic breakdown, leads to induced congested pattern emergence at the bottleneck, whereas there is free flow at the bottleneck without speed limitation. In other cases, speed limit control can suppress moving jam emergence, which occurs without speed limitation. It is found that these effects are associated with the probabilistic character of traffic breakdown at a bottleneck as well as with complex spatiotemporal congested pattern features.

Empirical test of a microscopic three-phase traffic theory

A review of dynamic nonlinear features of spatiotemporal congested patterns in freeway traffic is presented. The basis of the review is a comparison of theoretical features of the congested patterns that are shown by a microscopic traffic flow model in the context of the Kerner's three-phase traffic theory and empirical microscopic and macroscopic pattern characteristics measured on different freeways over various days and years. In this test of the microscopic three-phase traffic flow theory, a model of an "open" road is applied: Empirical time-dependence of traffic demand and drivers' destinations are used at the upstream model boundaries. At downstream model boundary conditions for vehicle freely leaving a modeling freeway section(s) are given. Spatiotemporal congested patterns emerge, develop, and dissolve in this open freeway model with the same types of bottlenecks as those in empirical observations. It is found that microscopic three-phase traffic models can explain all known macroscopic and microscopic empirical congested pattern features (e.g., probabilistic breakdown phenomenon as a first-order phase transition from free flow to synchronized flow, moving jam emergence in synchronized flow rather than in free flow, spatiotemporal features of synchronized flow and general congested patterns at freeway bottlenecks, intensification of downstream congestion due to upstream congestion at adjacent bottlenecks). It turns out that microscopic optimal velocity (OV) functions and time headway distributions are not necessarily qualitatively different, even if local congested traffic behavior is qualitatively different. Model performance with respect to spatiotemporal pattern emergence and evolution cannot be tested using these traffic characteristics. The reason for this is that important spatiotemporal features of congested traffic patterns are lost in these and many other macroscopic and microscopic traffic characteristics, which are widely used as the empirical basis for a test of traffic flow models.