Synchronized flow in oversaturated city traffic

Kerner, Boris S.; Klenov, Sergey L.; Hermanns, Gerhard; Hemmerle, Peter; Rehborn, Hubert; Schreckenberg, Michael

doi:10.1103/physreve.88.054801

Cited by 31 publications

(18 citation statements)

References 14 publications

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“…To guarantee this, simulations were used that are based on a stochastic Kerner-Klenov model [47][48][49][50][51] which is in the framework of three-phase traffic theory. In accordance with the empirical observations of oversaturated city traffic, this model can reproduce both SPs and MQs [32].…”

Section: Cumulated Acceleration and Energy Efficiency Of Vehiclessupporting

confidence: 50%

“…However, synchronised flow also occurs in city traffic: As has recently been found in the three-phase theory of city traffic [27][28][29][30][31], the transition from under-to oversaturated traffic at a traffic signal is associated with the emergence of a synchronised flow pattern in an initially free flow. Furthermore, synchronised flow patterns (SPs) have been predicted to exist in oversaturated city traffic at traffic signals as well [32].…”

Section: Wide Moving Jamsmentioning

confidence: 99%

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Impact of Synchronised Flow in Oversaturated City Traffic on Energy Efficiency of Conventional and Electrical Vehicles

Hemmerle¹,

Koller²,

Hermanns³

et al. 2016

Coll Dyn

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In this study of city traffic, we show that empirical synchronised flow patterns, which have been revealed recently in oversaturated traffic, exhibit considerable impact on the energy efficiency of vehicles. In particular, we have found out that energy consumption in oversaturated city traffic can decrease considerably when the oversaturated city traffic consists of synchronised flow patterns rather than consisting of moving queues of the classical traffic flow theory at traffic signals. Using empirical GNSS data measured by navigation devices on two different road sections in Düsseldorf, Germany, we show that synchronised flow patterns and moving queues differ in their cumulated vehicle acceleration (a sum of positive speed differences along a vehicle trajectory) despite similar mean speeds. Energy efficiency in return is dependent on the cumulated vehicle acceleration. We consider both the fuel consumption of conventional vehicles with combustion engines and the energy balance of electrical vehicles.

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Section: Cumulated Acceleration and Energy Efficiency Of Vehiclessupporting

confidence: 50%

Section: Wide Moving Jamsmentioning

confidence: 99%

Impact of Synchronised Flow in Oversaturated City Traffic on Energy Efficiency of Conventional and Electrical Vehicles

Hemmerle¹,

Koller²,

Hermanns³

et al. 2016

Coll Dyn

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“…It should be noted that a consideration of features of synchronized flow resulting from the breakdown both in highway traffic [32,33] and in oversaturated city traffic [44,45] is also out of scope of this review. This is because this review is solely devoted to a brief consideration of the set of fundamental empirical features of traffic breakdown occurring in free flow at highway bottlenecks as well as to the impact of these empirical features of the breakdown on theoretical fundamentals for reliable control and optimization of vehicular traffic and transportation networks.…”

Section: Basic Theoretical Fundament For the Development Of Reliable mentioning

confidence: 99%

Failure of classical traffic flow theories: a critical review

Kerner

2015

Elektrotech. Inftech.

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We explain that the fundamental empirical basis for automatic driving, reliable control and optimization of traffic and transportation networks is the set of empirical features of traffic breakdown at a road bottleneck. We show why generally accepted traffic and transportation theories and models are not consistent with this empirical fundament of traffic science. In particular, these classical traffic theories are as follows: (i) the Lighthill-Whitham-Richards (LWR) theory and traffic flow models in the framework of the LWR theory (for example, Daganzo's cell transmission model) that explain traffic breakdown through a fundamental diagram of traffic flow, (ii) General Motors (GM) class of traffic-flow models that explain traffic breakdown through traffic flow instability due to a driver reaction time (for example, the following well-known models belong to the GM model class: Gipps's model, Payne's model, Newell's optimal velocity (OV) model, Wiedemann's model (VISSIM traffic simulation tool), Bando et al. OV model, Treiber's Intelligent Driver Model, Krauß model (SUMO tool), the Aw-Rascle model), (iii) the classical understanding of stochastic highway capacity, and (iv) Wardrop's principles for dynamic control, assignment, and optimization of traffic and transportation networks.In turn, this can explain why dynamics network optimization and control approaches based on these classical traffic flow theories failed by their applications in the real world. We discuss why rather that the assumption about the existence of stochastic highway capacity, at any time instant there should be the infinite number of highway capacities within a range of the flow rate between a minimum capacity and a maximum capacity as assumed in three-phase theory introduced by the author. Because the assumption about the infinite number of highway capacities is consistent with the set of the fundamental empirical features of traffic breakdown at highway bottlenecks, this can be considered a theoretical fundament for the development of reliable automatic driving, control and optimization of vehicular traffic and transportation networks. We discuss briefly some features of the three-phase theory explaining the empirical fundament of transportation science.

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“…With the aim to model the driving behaviors induced by the traffic signal, this research work adopts a one-dimensional lattice to construct a single lane road segment and all vehicles are assumed to move from the left to the right, as shown in Figure 1. The previous studies [21,22] have proved that it is sufficient to consider traffic breakdown at a single signalized intersection in order to reveal features of traffic breakdown at the signal. Therefore, a traffic light which operates in a fixed cycle manner is amounted on the single lane road segment.…”

Section: The Signalized Traffic Scenariomentioning

confidence: 99%

Modelling Signal Controlled Traffic Based on Driving Behaviors

Yang

Chen

2015

Discrete Dynamics in Nature and Society

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In urban traffic, of particular interest the traffic breakdown which is primarily resulted from the driving behaviors is emerged to respond to the traffic signal. To investigate the influences of driving behaviors on the traffic breakdown, a cellular automaton model has been developed by incorporating a number of driving behaviors typically manifesting during the different stages when the vehicle approaching a traffic light. Numerical simulations have been performed based on a road segment consisting of three sections and each section is associated with a set of rules. The numerical simulations have demonstrated that the proposed model is capable of producing the time-delayed traffic breakdown and the dissolution of the oversaturated traffic. Furthermore, it has been evidenced that the probability of the traffic breakdown can be increased by involving the slow-to-start behavior. However, the activation of the anticipatory behavior can effectively impede the transition from undersaturated to oversaturated traffic. Finally, the contributions of the driving behaviors on the traffic breakdown have been quantitatively examined.

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Synchronized flow in oversaturated city traffic

Cited by 31 publications

References 14 publications

Impact of Synchronised Flow in Oversaturated City Traffic on Energy Efficiency of Conventional and Electrical Vehicles

Impact of Synchronised Flow in Oversaturated City Traffic on Energy Efficiency of Conventional and Electrical Vehicles

Failure of classical traffic flow theories: a critical review

Modelling Signal Controlled Traffic Based on Driving Behaviors

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