arXiv subjects

Boris S. Kerner

Publications and source records attributed to Boris S. Kerner.

At least 19 recordsLinked to original sources

arXiv2026

Vehicle Overacceleration -- A Fundamental Microscopic Mechanism for Traffic Breakdown Control Using Automated Vehicles and AI

This review article addresses a fundamental controversial question in traffic theory: Is the nucleation character of traffic breakdown at a bottleneck governed by vehicle overdeceleration (overbraking) or by discontinuous vehicle acceleration, referred to as vehicle overacceleration. This question is of particular importance in the context of automated vehicles and AI, whose individual dynamic behavior can enable reliable strategies for traffic breakdown control in the future. We show that, in both human-driven and automated traffic flow, traffic breakdown is governed by vehicle overacceleration rather than vehicle overdeceleration. With this objective, in microscopic modeling we separate traffic breakdown caused by overacceleration from traffic instabilities caused by overdeceleration due to braking behavior, while following recent papers [Phys. Rev. E 108, 014302 (2023); 108, 064305 (2023); 112, 034309 (2025)].

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arXiv2025

Microscopic features of the effect of vehicle overacceleration on traffic flow

Through the development of a microscopic deterministic model in the framework of three-phase traffic theory, microscopic features of vehicle overacceleration, which determines the occurrence of the metastability of free traffic flow at a bottleneck, have been revealed: (i) The greater the impact of vehicle overacceleration on free traffic flow at a bottleneck, the higher the maximum flow rate at which free flow can persist at the bottleneck, i.e., the better traffic breakdown can be avoided. (ii) There can be at least two mechanisms of overacceleration in road lane caused by safety acceleration at the bottleneck. (iii) Through a microscopic analysis of spatiotemporal competition between speed adaptation and vehicle acceleration behaviors, traffic conditions have been found at which safety acceleration in road lane or/and vehicle acceleration due to lane-changing on multi-lane road become overacceleration. (iv) There is spatiotemporal cooperation of different overacceleration mechanisms. (v) The stronger the overacceleration cooperation, the stronger the maintenance of free flow at the bottleneck due to overacceleration. (vi) On two-lane road, both speed adaptation and overacceleration in road lane can effect qualitatively on the overacceleration mechanism caused by lane-changing. These microscopic features of the effect of vehicle overacceleration on traffic flow are related to traffic flow consisting of human-driving or/and automated-driving vehicles.

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arXiv2024

A Methodology of Cooperative Driving based on Microscopic Traffic Prediction

We present a methodology of cooperative driving in vehicular traffic, in which for short-time traffic prediction rather than one of the statistical approaches of artificial intelligence (AI), we follow a qualitative different microscopic traffic prediction approach developed recently [Phys. Rev. E 106 (2022) 044307]. In the microscopic traffic prediction approach used for the planning of the subject vehicle trajectory, no learning algorithms of AI are applied; instead, microscopic traffic modeling based on the physics of vehicle motion is used. The presented methodology of cooperative driving is devoted to application cases in which microscopic traffic prediction without cooperative driving cannot lead to a successful vehicle control and trajectory planning. For the understanding of the physical features of the methodology of cooperative driving, a traffic city scenario has been numerically studied, in which a subject vehicle, which requires cooperative driving, is an automated vehicle. Based on microscopic traffic prediction, in the methodology first a cooperating vehicle(s) is found; then, motion requirements for the cooperating vehicle(s) and characteristics of automated vehicle control are predicted and used for vehicle motion; to update predicted characteristics of vehicle motion, calculations of the predictions of motion requirements for the cooperating vehicle and automated vehicle control are repeated for each next time instant at which new measured data for current microscopic traffic situation are available. With the use of microscopic traffic simulations, the evaluation of the applicability of this methodology is illustrated for a simple case of unsignalized city intersection, when the automated vehicle wants to turn right from a secondary road onto the priority road.

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arXiv2023

Breakdown in vehicular traffic: driver over-acceleration, not over-reaction

Contrary to a wide-accepted assumption about the decisive role of driver over-reaction for breakdown in vehicular traffic, we have shown that the cause of the breakdown is driver over-acceleration, not driver over-reaction. To reach this goal, we have introduced a mathematical approach for the description of driver over-acceleration in a microscopic traffic flow model. The model, in which no driver over-reaction occurs, explains all observed empirical nucleation features of traffic breakdown.

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arXiv2023

Physics of Automated-Driving Vehicular Traffic

We have found that a variety of phase transitions occurring between three traffic phases (free flow (F), synchronized flow (S), and wide moving jam (J)) determine the spatiotemporal dynamics of traffic consisting of 100% automated-driving vehicles moving on a two-lane road with an on-ramp bottleneck. This means that three-phase traffic theory is a common framework for the description of traffic states independent of whether human-driving or automated-driving vehicles move in vehicular traffic. To prove this, we have studied automated-driving vehicular traffic with the use of classical Helly's model (1959) widely applied for automated vehicle motion. Although dynamic rules of the motion of automated-driving vehicles in a road lane are qualitatively different from those of human-driving vehicles, we have revealed that a free-flow-to-synchronized-flow transition (F$\rightarrow$S transition) exhibits the nucleation nature, which was observed in empirical field data measured in traffic consisting of 100% human-driving vehicles. The physics of the nucleation nature of the F$\rightarrow$S transition in automated-driving traffic is associated with a discontinuity in the rate of lane-changing that causes the discontinuity in the rate of over-acceleration. This discontinuous character of over-acceleration leads to both the existence and self-maintaining of synchronized flow at the bottleneck in automated-driving vehicular traffic as well as to the existence at any time instant of a range of highway capacities between some minimum and maximum capacities. Within the capacity range, an F$\rightarrow$S transition can be induced; however, when the maximum capacity is exceeded, then after some time-delay a spontaneous F$\rightarrow$S transition occurs at the bottleneck. The phases F, S, and J can coexist each other in space and time.

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arXiv2020

Effect of Autonomous Driving on Traffic Breakdown in Mixed Traffic Flow: A Critical Mini-Review

A critical analysis of the effect of autonomous driving vehicles on traffic breakdown in mixed traffic flow is made. Classical adaptive cruise control (ACC) and ACC based on three-phase traffic theory (TPACC) are considered. We show that within a wide range of dynamic parameters of classical ACC, the ACC-vehicles can initiate traffic breakdown and reduce highway capacity. Contrarily, in the same range of parameters of TPACC, the TPACC-vehicles do not initiate traffic breakdown. To understand physical reasons for the effect of classical ACC- and TPACC-vehicles on traffic breakdown, we introduce a model of ACC that can be considered a combination of dynamic features of classical ACC and TPACC. With the use of this model, we find how the amplitude of a local speed disturbance caused by the ACC in a vicinity of a bottleneck and the probability of traffic breakdown depend on the dynamic parameters of the ACC.

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arXiv2019

Statistical Physics of Synchronized Traffic Flow: Spatiotemporal Competition between S$\to$F and S$\to$J Instabilities

We have revealed statistical physics of synchronized traffic flow that is governed by a spatiotemporal competition between S$\rightarrow$F and S$\rightarrow$J instabilities (where F, S, and J denote, respectively, the free flow, synchronized flow, and wide moving jam traffic phases). A probabilistic analysis of synchronized flow based on simulations of a cellular automaton model in the framework of three-phase traffic theory is made. This probabilistic analysis shows that there is a finite range of the initial space-gap between vehicles in synchronized flow within which during a chosen time for traffic observation either synchronized flow persists with probability $P_{\rm S}$, or an S$\rightarrow$F transition occurs with probability $P_{\rm SF}$, or else an S$\rightarrow$J transition occurs with probability $P_{\rm SJ}$. Space-gap dependencies of the probabilities $P_{\rm S}$, $P_{\rm SF}$, and $P_{\rm SJ}$ have been found. The statistical features of synchronized flow found for a homogeneous road remain qualitatively for a road with a bottleneck. However, rather than nuclei for S$\rightarrow$F and S$\rightarrow$J instabilities occur at random road locations of the homogeneous road, due to a permanent non-homogeneity introduced by the bottleneck, nuclei for initial S$\rightarrow$F and S$\rightarrow$J instabilities appear mostly at the bottleneck.

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arXiv2017

Physics of Autonomous Driving based on Three-Phase Traffic Theory

We have revealed physical features of autonomous driving in the framework of the three-phase traffic theory for which there is no fixed time headway to the preceding vehicle. A comparison with the classical model approach to autonomous driving for which an autonomous driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that autonomous driving in the framework of the three-phase traffic theory exhibits the following advantages in comparison with the classical model of autonomous driving: (i) The absence of string instability. (ii) Considerably smaller speed disturbances at road bottlenecks. (iii) Autonomous driving vehicles based on the three-phase theory decrease the probability of traffic breakdown at the bottleneck in mixed traffic flow consisting of human driving and autonomous driving vehicles; on the contrary, even a single autonomous driving vehicle based on the classical approach can provoke traffic breakdown at the bottleneck in mixed traffic flow.

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arXiv2016

Failure of classical traffic and transportation theory: The maximization of the network throughput maintaining free flow conditions in network

We have revealed general physical conditions for the {\it maximization} of the network throughput at which free flow conditions are ensured, i.e., traffic breakdown cannot occur in the whole traffic or transportation network. A physical measure of the network -- {\it network capacity} is introduced that characterizes general features of the network with respect to the maximization of the network throughput. The network capacity allows us also to make a general proof of the deterioration of traffic system occurring when dynamic traffic assignment is performed in a network based on the classical Wardrop' user equilibrium (UE) and system optimum (SO) equilibrium.

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arXiv2016

Failure of classical traffic flow theories: Stochastic highway capacity and automatic driving

In a mini-review [Physica A {\bf 392} (2013) 5261--5282] it has been shown that classical traffic flow theories and models failed to explain empirical traffic breakdown -- a phase transition from metastable free flow to synchronized flow at highway bottlenecks. The main objective of this mini-review is to study the consequence of this failure of classical traffic-flow theories for an analysis of empirical stochastic highway capacity as well as for the effect of automatic driving vehicles and cooperative driving on traffic flow. To reach this goal, we show a deep connection between the understanding of empirical stochastic highway capacity and a reliable analysis of automatic driving vehicles in traffic flow. With the use of simulations in the framework of three-phase traffic theory, a probabilistic analysis of the effect of automatic driving vehicles on a mixture traffic flow consisting of a random distribution of automatic driving and manual driving vehicles has been made. We have found that the parameters of automatic driving vehicles can either decrease or increase the probability of traffic breakdown. The increase in the probability of traffic breakdown, i.e., the deterioration of the performance of the traffic system can occur already at a small percentage (about 5$\%$) of automatic driving vehicles. The increase in the probability of traffic breakdown through automatic driving vehicles can be realized, even if any platoon of automatic driving vehicles satisfies condition for string stability.

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arXiv2015

Microscopic Theory of Traffic Flow Instability Governing Traffic Breakdown at Highway Bottlenecks: Growing Wave of Increase in Speed in Synchronized Flow

We have revealed a growing local speed wave of increase in speed that can randomly occur in synchronized flow (S) at a highway bottleneck. The development of such a traffic flow instability leads to free flow (F) at the bottleneck; therefore, we call this instability as an S$\rightarrow$F instability. Whereas the S$\rightarrow$F instability leads to a local {\it increase in speed} (growing acceleration wave), in contrast, the classical traffic flow instability introduced in 50s--60s and incorporated later in a huge number of traffic flow models leads to a growing wave of a local {\it decrease in speed} (growing deceleration wave). We have found that the S$\rightarrow$F instability can occur only, if there is a finite time delay in driver over-acceleration. The initial speed disturbance of increase in speed (called "speed peak") that initiates the S$\rightarrow$F instability occurs usually at the downstream front of synchronized flow at the bottleneck. There can be many speed peaks with random amplitudes that occur randomly over time. It has been found that the S$\rightarrow$F instability exhibits the nucleation nature: Only when a speed peak amplitude is large enough, the S$\rightarrow$F instability occurs; in contrast, speed peaks of smaller amplitudes cause dissolving speed waves of a local increase in speed(dissolving acceleration waves) in synchronized flow. We have found that the S$\rightarrow$F instability governs traffic breakdown -- a phase transition from free flow to synchronized flow (F$\rightarrow$S transition) at the bottleneck: The nucleation nature of the S$\rightarrow$F instability explains the metastability of free flow with respect to an F$\rightarrow$S Transition at the bottleneck.

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arXiv2015

Empirical Features of Spontaneous and Induced Traffic Breakdowns in Free Flow at Highway Bottlenecks

Based on an empirical study of real field traffic data measured in 1996--2014 through road detectors installed on German freeways, we reveal physical features of empirical nuclei for spontaneous traffic breakdown in free flow at highway bottlenecks. It is shown that the source of a nucleus for traffic breakdown is the solely difference between empirical spontaneous and induced traffic breakdowns at a highway bottleneck. Microscopic traffic simulations with a stochastic traffic flow model in the framework of three-phase theory explain the empirical findings. It turns out that in the most cases, a nucleus for empirical spontaneous traffic breakdown occurs through an interaction of one of waves in free flow with an empirical permanent speed disturbance localized at a highway bottleneck. The wave is a localized structure in free flow, in which the total flow rate is larger and the speed averaged across the highway is smaller than outside the wave. The waves in free flow appear due to oscilations in the percentage of slow vehicles; these waves propagate with the average speed of slow vehicles in free flow (about 85--88 km/h for German highways). Any of the waves exhibits a two-dimensional asymmetric spatiotemporal structure: Wave's characteristics are different in different highway lanes.

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arXiv2014

"Cumulated Vehicle Acceleration": An Attribute of GPS Probe Vehicle Traces for On-Line Assessment of Vehicle Fuel Consumption in Traffic and Transportation Networks

To perform a reliable on-line assessment of fuel consumption in vehicles, we introduce "cumulated vehicle acceleration" as an attribute of GPS probe vehicle traces. The objective of the calculation of the attribute "cumulated vehicle acceleration" in the GPS probe vehicle data is to perform a reliable on-line dynamic traffic assignment for the reduction of vehicle consumption in traffic and transportation networks.

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arXiv2012

Theory of self-organized traffic at light signal

Based on numerical simulations of a three-phase traffic flow model, a probabilistic theory of traffic at the light signal is developed. We have found that very complex spatiotemporal self-organized phenomena determine features of city traffic. We have revealed that the breakdown of {\it green wave} in a city is initiated by the emergence of a moving synchronized flow pattern (MSP) within the green wave. It turns out that a sequence of F$\rightarrow$S$\rightarrow$J transitions (F -- free flow, S -- synchronized flow, J -- moving queue) lead to traffic breakdown at the light signal. Both spontaneous and induced breakdowns of the green wave have been found. From a study of a variety of scenarios for arrival traffic, we have found that there are the infinite number of capacities of traffic at the light signal, which are in a capacity range between a minimum capacity and maximum capacity; each of the capacities gives a flow rate at which under-saturated traffic is in a metastable state with respect to the transition to over-saturated traffic. The maximum capacity depends crucially on a time-dependence of the flow rate: The larger the number of vehicles that arrive the light signal during the green phase, the larger the maximum capacity.

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arXiv2011

Physics of traffic gridlock in a city

Based of simulations of a stochastic three-phase traffic flow model, we reveal that at a signalized city intersection under small link inflow rates at which a vehicle queue developed during the red phase of light signal dissolves fully during the green phase, i.e., no traffic gridlock should be expected, nevertheless, traffic breakdown with the subsequent city gridlock occurs with some probability after a random time delay. This traffic breakdown is initiated by a first-order phase transition from free flow to synchronized flow occurring upstream of the vehicle queue at light signal. The probability of traffic breakdown at light signal is an increasing function of the link inflow rate and duration of the red phase of light signal.

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arXiv2010

Effect of Driver Behavior on Spatiotemporal Congested Traffic Patterns at Highway Bottlenecks in the Framework of Three-Phase Traffic Theory

We present results of numerical simulations of the effect of driver behavior on spatiotemporal congested traffic patterns that result from traffic breakdown at an on-ramp bottleneck. The simulations are made with the Kerner-Klenov stochastic traffic flow model in the framework of three-phase traffic theory. Different diagrams of congested patterns at the bottleneck associated with different driver behavioral characteristics are found and compared each other. An adaptive cruise control (ACC) in the framework of three-phase traffic theory introduced by the author (called a "driver alike ACC" (DA-ACC)) is discussed. The effect of DA-ACC-vehicles on traffic flow, in which without the DA-ACC-vehicles traffic congestion occurs at the bottleneck, is numerically studied. We show that DA-ACC-vehicles improve traffic flow considerably without any reduction in driving comfort. It is found that there is a critical percentage of DA-ACC-vehicles in traffic flow: If the percentage of the DA-ACC-vehicle exceeds the critical one no traffic breakdown occurs at the bottleneck. A criticism of a recent "criticism of three-phase traffic theory" is presented

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arXiv2010

Traffic Network Optimum Principle - Minimum Probability of Congestion Occurrence

We introduce an optimum principle for a vehicular traffic network with road bottlenecks. This network breakdown minimization (BM) principle states that the network optimum is reached, when link flow rates are assigned in the network in such a way that the probability for spontaneous occurrence of traffic breakdown at one of the network bottlenecks during a given observation time reaches the minimum possible value. Based on numerical simulations with a stochastic three-phase traffic flow model, we show that in comparison to the well-known Wardrop's principles the application of the BM principle permits considerably greater network inflow rates at which no traffic breakdown occurs and, therefore, free flow remains in the whole network.

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arXiv2007

Features of Traffic Congestion caused by bad Weather Conditions or Accident

Spatiotemporal features and physics of vehicular traffic congestion occurring due to heavy freeway bottlenecks caused by bad weather conditions or accidents are found based on simulations in the framework of three-phase traffic theory. A model of a heavy bottleneck is presented. Under a continuous non-limited increase in bottleneck strength, i.e., when the average flow rate within a congested pattern allowed by the heavy bottleneck decreases continuously up to zero, the evolution of the traffic phases in congested traffic, synchronized flow and wide moving jams, is studied.

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