Automatic Tracing and Forecasting of Moving Traffic Jams Using Predictable Features of Congested Traffic Flow

The disturbance factors in the traffic flow may lead to traffic congestion. The agglomeration characteristics shown in traffic jams are similar to the biological swarm characteristics. In this paper, acceleration-spacing model is established based on the potential field method and the Lagrange method. The vehicle in front is viewed as the main force source. Then the data of the traffic congestion caused by the temporary parking in front of the school are used to calibrate the parameters of the model. It can be verified that the model is effective.

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Data-Driven Methods for Detecting Traffic Jams in Vehicular Traffic Systems

Volume 7B: Dynamics, Vibration, and Control ◽

10.1115/imece2020-23691 ◽

2020 ◽

Author(s):

Amin Ghadami ◽

Charles R. Doering ◽

Bogdan I. Epureanu

Keyword(s):

Dynamical Systems ◽

Complex Systems ◽

Critical Point ◽

Traffic Flow ◽

Traffic Dynamics ◽

Traffic Jams ◽

Forecasting Methods ◽

Traffic Flow Management ◽

Traffic Systems ◽

Emergent Behaviors

Abstract Ground vehicle traffic jams are a serious issue in today’s society. Despite advances in traffic flow management in recent years, predicting traffic jams is still a challenge. Recently, novel techniques have been developed in complex systems theory to enable forecasting emergent behaviors in dynamical systems. Forecasting methods have been developed based on exploiting the phenomenon of critical slowing down, which occurs in dynamical systems near certain types of bifurcations and phase transitions. Herein, we explore recently developed tools of tipping point forecasting in complex systems, namely early warning indicators and bifurcation forecasting methods, and investigate their application to predict traffic jams on roads. The measurements required for forecasting are recorded dynamical features of the system such as headways between cars in traffic or density of cars on road. Forecasting approaches are applied to simulated and experimental traffic flow conditions. Results show that one can successfully predict proximity to the critical point of congestion as well as traffic dynamics after this critical point using the proposed approaches. The methodologies presented can be used to analyze stability of traffic models and address challenges related to the complexity of traffic dynamics.

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Performance Evaluation of Magnetic Wireless Sensor Networks Algorithm for Traffic Flow Monitoring in Chaotic Cities

Modelling and Simulation in Engineering ◽

10.1155/2018/2591304 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Haji Said Fimbombaya ◽

Nerey H. Mvungi ◽

Ndyetabura Y. Hamisi ◽

Hashimu U. Iddi

Keyword(s):

Magnetic Field ◽

Wireless Sensor Networks ◽

Sensor Networks ◽

Traffic Flow ◽

Wireless Sensor ◽

Success Rates ◽

Earth’S Magnetic Field ◽

Congested Traffic ◽

Flow Monitoring ◽

Flow Information

Traffic flow monitoring involves the capturing and dissemination of real-time traffic flow information for a road network. When a vehicle, a ferromagnetic object, travels along a road, it disturbs the ambient Earth’s magnetic field, causing its distortion. The resulting distortion carries vehicle signature containing traffic flow related information such as speed, count, direction, and classification. To extract such information in chaotic cities, a novel algorithm based on the resulting magnetic field distortion was developed using nonintrusive sensor localization. The algorithm extracts traffic flow information from resulting magnetic field distortions sensed by magnetic wireless sensor nodes located on the sides of the road. The model magnetic wireless sensor networks algorithm for local Earth’s magnetic field performance was evaluated through simulation using Dar es Salaam City traffic flow conditions. Simulation results for vehicular detection and count showed 93% and 87% success rates during normal and congested traffic states, respectively. Travel Time Index (TTI) was used as a congestion indicator, where different levels of congestion were evaluated depending on the traffic state with a performance of 87% and 88% success rates during normal and congested traffic flow, respectively.

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An Extended Car-Following Model in a Multi-Interaction Driving System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.178-181.2717 ◽

2012 ◽

Vol 178-181 ◽

pp. 2717-2720

Author(s):

Man Xian Tuo

Keyword(s):

Numerical Simulation ◽

Traffic Flow ◽

Flow Model ◽

Extended Model ◽

Traffic Flow Model ◽

Driving System ◽

Car Following ◽

Traffic Jams ◽

Car Following Model ◽

The Stability

An extended traffic flow model is proposed by introducing the multiple information of preceding cars. The linear stability condition of the extended model is obtained, which shows that the stability of traffic flow is improved by considering the interaction of preceding cars to the following car. Numerical simulation shows that the traffic jams are suppressed efficiently by taking into account the multiple information of the preceding cars.

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A NEW CELLULAR AUTOMATON MODEL FOR TRAFFIC FLOW WITH DIFFERENT PROBABILITY FOR DRIVERS

International Journal of Modern Physics C ◽

10.1142/s0129183107010541 ◽

2007 ◽

Vol 18 (05) ◽

pp. 773-782 ◽

Cited By ~ 6

Author(s):

H. B. ZHU ◽

H. X. GE ◽

S. Q. DAI

Keyword(s):

Cellular Automaton ◽

Traffic Flow ◽

Metastable State ◽

Maximum Flow ◽

Traffic Model ◽

Fundamental Diagram ◽

Density Dependent ◽

Spontaneous Formation ◽

Traffic Jams ◽

Ca Model

Based on the Nagel–Schreckenberg (NaSch) model of traffic flow, a new cellular automaton (CA) traffic model is proposed to simulate microscopic traffic flow. The probability p is a variable which contains a randomly selected term for each individual driver and a density-dependent term which is the same for all drivers. When the rational probability p is obtained, the larger value of maximum flow which is close to the observed data can be reached compared with that obtained from the NaSch model. The fundamental diagram obtained by simulation shows the ability of this modified CA model to capture the essential features of traffic flow, e.g., the spontaneous formation of traffic jams and appearance of the metastable state. These indicate that the presented model is more reasonable and realistic.

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MODIFIED COMFORTABLE DRIVING MODEL FOR CONGESTED TRAFFIC FLOW

International Journal of Modern Physics B ◽

10.1142/s021797920402518x ◽

2004 ◽

Vol 18 (14) ◽

pp. 1991-2001 ◽

Cited By ~ 13

Author(s):

RUI JIANG ◽

QING-SONG WU

Keyword(s):

Time Series ◽

Computer Simulation ◽

Traffic Flow ◽

Red Light ◽

Flow Density ◽

Traffic Patterns ◽

Fundamental Diagram ◽

Average Data ◽

Congested Traffic ◽

Driving Model

In this paper, the concepts of "jammed status" and "jam headway" [X. B. Li, R. Jiang and Q. S. Wu, Phys. Rev.E68, 016117 (2003)] are introduced into the Modified Comfortable Driving (MCD) model [R. Jiang and Q. S. Wu, J. Phys.A36, 381 (2003)] to simulate the congested traffic flow including synchronized flow and wide moving jams. Using computer simulation, the fundamental diagram, the space–time plots, the time series of the density in the jams, the 1-min average data in the flow-density plane, the traffic patterns induced by red light are investigated. It is shown that the new model can describe both the synchronized flow and the sparse wide jams quite well.

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SELF-ORGANIZED CRITICALITY IN 1D TRAFFIC FLOW

Fractals ◽

10.1142/s0218348x96000388 ◽

1996 ◽

Vol 04 (03) ◽

pp. 279-283 ◽

Cited By ~ 5

Author(s):

TAKASHI NAGATANI

Keyword(s):

Traffic Flow ◽

Transition Probability ◽

Annihilation Process ◽

One Dimensional ◽

Traffic Jams ◽

Self Organized ◽

Stochastic Transition ◽

Self Organized Criticality ◽

The One ◽

Empty Wave

Annihilation process of traffic jams is investigated in a one-dimensional traffic flow on a highway. The one-dimensional fully asymmetric exclusion model with open boundaries for parallel update is extended to take into account stochastic transition of cars, where a car moves ahead with transition probability pt. Near pt=1, the system is driven asymptotically into a steady state exhibiting a self-organized criticality. Traffic jams with various lifetimes (or sizes) appear and disappear by colliding with an empty wave. The typical lifetime <m> of traffic jams scales as [Formula: see text], where ∆pt=1−pt. It is shown that the cumulative lifetime distribution Nm(∆pt) satisfies the scaling form [Formula: see text].

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KdV–Berger solution and local cluster effect of two-sided lateral gap continuum traffic flow model

International Journal of Modern Physics B ◽

10.1142/s0217979219501534 ◽

2019 ◽

Vol 33 (15) ◽

pp. 1950153 ◽

Cited By ~ 2

Author(s):

Hari Krishna Gaddam ◽

Asha Kumari Meena ◽

K. Ramachandra Rao

Keyword(s):

Traffic Flow ◽

Density Wave ◽

Traveling Wave Solutions ◽

Neutral Stability ◽

Local Cluster ◽

Traffic Jams ◽

Proposed Model ◽

The Stability ◽

Lateral Gaps ◽

Stability Line

This study proposes a new nonlane-based continuum model derived from a two-sided lateral gap-following theory using the relation between microscopic and macroscopic variables. The model considers the effect of lateral gaps of the leading vehicles available on both sides of the following vehicle in multilane scenario. Linear stability analysis is performed to establish the neutral stability condition for the stable traffic flow. Nonlinear analysis is carried out at neutral stability line to derive the KdV–Berger equation, which describes density wave propagation. For that, one of the traveling wave solutions is also obtained. Numerical simulation results show that the two-sided lateral gap in the model improves the stability of the traffic flow by suppressing the traffic jams even at high-density conditions. The results implies that the proposed model is successful in replicating the properties of actual traffic jams in nonlane-based traffic environment.

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USING VARIABLE SPEED LIMITS TO ELIMINATE WIDE MOVING JAMS: A STUDY BASED ON THREE-PHASE TRAFFIC THEORY

International Journal of Modern Physics C ◽

10.1142/s012918311250060x ◽

2012 ◽

Vol 23 (09) ◽

pp. 1250060 ◽

Cited By ~ 17

Author(s):

YIZHI WANG ◽

YI ZHANG ◽

JIANMING HU ◽

LI LI

Keyword(s):

Traffic Flow ◽

Control Strategies ◽

Vehicle Speed ◽

Variable Speed ◽

Speed Limits ◽

Congested Traffic ◽

Three Phase ◽

Variable Speed Limits ◽

Ca Model ◽

Traffic Theory

One frequently observed congested traffic flow pattern is wide moving jam (WMJ), in which the average vehicle speed is very low and the density is very high. In some recent studies, variable speed limits (VSL) were proposed as effective measures to eliminate or abate the influence of jam waves. However, in most of these studies, the stochastic features of driving behaviors and the resulting uncertainty of traffic flow dynamics were not fully considered. In this paper, we use cellular automaton (CA) model-based simulations to test the performances of different VSL control strategies and apply the three-phase traffic theory to further analyze the obtained results. Based on the simulation results, we got two novel findings. Firstly, we observed seven, instead of the previously assumed six, states of traffic flow in the evolution process of WMJ, when VSL were applied. Secondly and more importantly, we found that inappropriate speed limit may induce new WMJ and exaggerate congestions in two ways: one way corresponds to an F → J transition and the other corresponds to an F → S → J transition. Based on these findings, the appropriate lower bound of VSL was finally discussed in this paper.

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