Framework Of Three-phase Traffic Theory Research Articles

Simulation Study of Rear-End Crash Evaluation considering Driver Experience Heterogeneity in the Framework of Three-Phase Traffic Theory

Driving safety is considered to have a strong relationship with traffic flow characteristics. However, very few studies have addressed the safety impacts in the three-phase traffic theory that has been demonstrated to be an advancement in explaining the empirical features of traffic flow. Another important issue affecting safety is driver experience heterogeneity, especially in developing countries experiencing a dramatic growth in the number of novice drivers. Thus, the primary objective of the current study is to develop a microsimulation environment for evaluating safety performance considering the presence of novice drivers in the framework of three-phase theory. First, a car-following model is developed by incorporating human physiological factors into the classical Intelligent Driver Model (IDM). Moreover, a surrogate safety measure based on the integration concept is modified to evaluate rear-end crashes in terms of probability and severity simultaneously. Based on a vehicle-mounted experiment, the field data of car-following behavior are collected by dividing the subjects into a novice group and an experienced group. These data are used to calibrate the proposed car-following model to explain driver experience heterogeneity. The results indicate that our simulation environment is capable of reproducing the three-phase theory, and the changes in the modified surrogate safety measure are highly correlated with traffic phases. We also discover that the presence of novice drivers leads to different safety performance outcomes across various traffic phases. The effect of driver experience heterogeneity is found to increase the probability of the rear-end crashes as well as the corresponding severity. The results of this study are expected to provide a scientific understanding of the mechanisms of crash occurrences and to provide application suggestions for improving traffic safety performance.

Effect of autonomous driving on traffic breakdown in mixed traffic flow: A comparison of classical ACC with three-traffic-phase-ACC (TPACC)

In this paper, an analysis of the effect of autonomous driving vehicles on traffic breakdown in mixed traffic flow consisting of randomly distributed human driving and autonomous driving vehicles is made. Autonomous vehicles based on classical (standard) adaptive cruise control (ACC) in a vehicle and on an ACC in the framework of three-phase traffic theory (TPACC – Three-traffic-Phase ACC) introduced recently [Phys. Rev. E 97 (2018) 042303] are considered. Due to the particular importance of characteristics of traffic breakdown (transition from free traffic flow to congested traffic) for almost all approaches to traffic control and management in traffic networks, the basis of this paper is a study of the effect of autonomous vehicles on the probability of traffic breakdown and on stochastic highway capacity in mixed traffic flow. We show that within a wide range of dynamic parameters of classical ACC, the ACC-vehicles can deteriorate the traffic system considerably while initiating traffic breakdown and reducing highway capacity at a bottleneck. Contrarily, in the same range of parameters of dynamic rules of TPACC, the TPACC-vehicles either do not effect on traffic characteristics or sometimes can even improve them. 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 depends on the dynamic parameters of the ACC. To emphasize that the deterioration of the characteristics of mixed traffic flow through classical ACC-vehicles is not associated with a well-known effect of string instability of platoons of autonomous vehicles, we limit by a consideration of only such classical ACC-vehicles whose platoon satisfies condition for string stability.

Prediction of moving bottleneck through the use of probe vehicles: a simulation approach in the framework of three-phase traffic theory

Based on simulations in the framework of Kerner’s three-phase traffic theory, we present a methodology for the prediction of a moving bottleneck (MB) with the use of a small share of probe vehicles (floating car data – FCD) randomly distributed in traffic flow. In this methodology, a conclusion of the three-phase traffic theory has been used that in the vicinity of any bottleneck there can be observed phase transitions between free flow and synchronized flow. The presented methodology is based on the recognition of phase transition points from synchronized flow to free flow on probe vehicle trajectories. For the simulations, we have used the Kerner–Klenov microscopic stochastic traffic flow model. It has been found that the MB can be predicted even if about 1% of probe vehicles are in traffic flow. The time-function of the probability of MB prediction in dependence of the share of probe vehicles in traffic flow has been calculated. We have found that the time-dependence of the probability of MB prediction as well as the accuracy of the estimation of MB location depend considerably on the occurrence of sequences of phase transitions from free flow to synchronized flow and back from synchronized flow to free flow occurring before traffic breakdown at the MB as well as speed oscillations in synchronized flow at the MB. The methodology of MB prediction presented in the paper can be used by either automated driving vehicles or other ITS-applications for speed harmonization, collision avoidance that should increase traffic safety and comfort.

Statistical physics of synchronized traffic flow: Spatiotemporal competition between S→F and S→J instabilities.

We have revealed statistical physics of synchronized traffic flow that is governed by a spatiotemporal competition between S→F and S→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_{S}, or an S→F transition occurs with probability P_{SF}, or else an S→J transition occurs with probability P_{SJ}. Space-gap dependencies of the probabilities P_{S}, P_{SF}, and P_{SJ} have been found. It has been also found that (i) an initial S→F instability can lead to sequences of S→F→S→J transitions; (ii) an initial S→J instability can lead to sequences of S→J→S→F transitions. Each of the phase transitions in the sequences S→F→S→J transitions and S→J→S→F transitions exhibits the nucleation nature; these sequences of phase transitions determine spatiotemporal features of traffic patterns resulting from the competition between S→F and S→J instabilities. 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→F and S→J instabilities occurring at random road locations of the homogeneous road, due to a permanent nonhomogeneity introduced by the bottleneck, nuclei for initial S→F and S→J instabilities appear mostly at the bottleneck.

Physics of automated driving in framework of three-phase traffic theory.

We have revealed physical features of automated 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 automated driving for which an automated driving vehicle tries to reach a fixed (desired or "optimal") time headway to the preceding vehicle has been made. It turns out that automated driving in the framework of the three-phase traffic theory can exhibit the following advantages in comparison with the classical model of automated driving: (i) The absence of string instability. (ii) Considerably smaller speed disturbances at road bottlenecks. (iii) Automated driving vehicles based on the three-phase theory can decrease the probability of traffic breakdown at the bottleneck in mixed traffic flow consisting of human driving and automated driving vehicles; on the contrary, even a single automated driving vehicle based on the classical approach can provoke traffic breakdown at the bottleneck in mixed traffic flow.

Autonomous driving in framework of three-phase traffic theory

We discuss a strategy for autonomous driving in the framework of three-phase traffic theory. The main reason for autonomous driving in the framework of the three-phase theory is that an autonomous driving vehicle should learn from driver behaviors in real traffic found in empirical data and explained in the three-phase theory. In contrast with the classical approach to autonomous driving in which at each given speed the vehicle tries to reach a fixed desired time headway, in the autonomous driving strategy based on the three-phase traffic theory there is no fixed time headway to the preceding vehicle.

Improved 2D intelligent driver model in the framework of three-phase traffic theory simulating synchronized flow and concave growth pattern of traffic oscillations

This paper firstly show that 2 Dimensional Intelligent Driver Model (Jiang et al., 2014) is not able to replicate the synchronized traffic flow. Then we propose an improved model by considering the difference between the driving behaviors at high speeds and that at low speeds, which is in the framework of three-phase traffic theory. Simulations show that the improved model can reproduce the phase transition from synchronized flow to wide moving jams, the spatiotemporal patterns of traffic flow induced by traffic bottleneck, and the concave growth pattern of traffic oscillations (i.e. the standard deviation of the velocities of vehicles increases in a concave/linear way along the platoon). Validating results show that the empirical time series of traffic speed obtained from Floating Car Data can be well simulated as well.

A theory of traffic congestion at moving bottlenecks

The physics of traffic congestion occurring at a moving bottleneck on a multi-lane road is revealed based on the numerical analyses of vehicular traffic with a discrete stochastic traffic flow model in the framework of three-phase traffic theory. We find that there is a critical speed of a moving bottleneck at which traffic breakdown, i.e. a first-order phase transition from free flow to synchronized flow, occurs spontaneously at the moving bottleneck, if the flow rate upstream of the bottleneck is great enough. The greater the flow rate, the higher the critical speed of the moving bottleneck. A diagram of congested traffic patterns at the moving bottleneck is found, which shows regions in the flow-rate–moving-bottleneck-speed plane in which congested patterns emerge spontaneously or can be induced through large enough disturbances in an initial free flow. A comparison of features of traffic breakdown and resulting congested patterns at the moving bottleneck with known ones at an on-ramp (and other motionless) bottleneck is made. Nonlinear features of complex interactions and transformations of congested traffic patterns occurring at on- and off-ramp bottlenecks due to the existence of the moving bottleneck are found. The physics of the phenomenon of traffic congestion due to ‘elephant racing’ on a multi-lane road is revealed.

Explaining traffic patterns at on-ramp vicinity by a driver perception model in the framework of three-phase traffic theory

In traffic system, driving behaviors change with the surrounding traffic perceived by drivers, resulting in the complex spatio-temporal traffic patterns. Accordingly, in the majority of traffic models, vehicle accelerations are described by dynamic equations based on driving behavior, system dynamics and some underlying steady-state velocity-gap (bumper-to-bumper spacing) relation in order to guarantee the realistic human behavior. This paper proposes a deterministic car-following model based on a multi-branch fundamental diagram with each branch representing a particular category of driving style. Furthermore, an additional dynamic perception equation is introduced to reflect the driving style adaptation in response to the change in surrounding traffic situations. With simulation based on the proposed “driver perception model” (DP model), empirical findings of traffic breakdown and observed spatio-temporal patterns at on-ramp vicinity are reproduced. Furthermore, comparison results show the consistency between numerical simulation and the real traffic data of Beijing urban freeway.

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.

Driver choice compared to controlled diversion for a freeway double on-ramp in the framework of three-phase traffic theory

Two diversion schemes that apportion demand between two on-ramps to reduce congestion and improve throughput on a freeway are analyzed. In the first scheme, drivers choose to merge or to divert to a downstream on-ramp based on information about average travel times for the two routes: (1) merge and travel on the freeway or (2) divert and travel on a surface street with merging downstream. The flow, rate of merging at the ramps, and the travel times oscillate strongly, but irregularly, due to delayed feedback. In the second scheme, diversion is controlled by the average mainline velocities just upstream of the on-ramps. Driver choice is not involved. If the average upstream velocity on the mainline drops below a predetermined value (20 m/s) vehicles are diverted to the downstream ramp. When the average mainline velocity downstream becomes too low, diversion is no longer permitted. The resultant oscillations in this scheme are nearly periodic. The period is dominated by the response time of the mainline to interruption of merging rather than delayed feedback, which contributes only a minor component linear in the distance separating the on-ramps. In general the second scheme produces more effective congestion reduction and greater throughput. Also the travel times for on-ramp drivers are less than that obtained by drivers who attempt to minimize their own travel times (first scheme). The simulations are done using the Kerner–Klenov stochastic three-phase theory of traffic [B.S. Kerner, S.L. Klenov, Phys. Rev. E 68 (2003) 036130].

A theory of traffic congestion at heavy bottlenecks

Spatiotemporal features and physics of vehicular traffic congestion occurring due to heavy highway bottlenecks caused for example 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. It is found that at a small enough flow rate within the congested pattern, the pattern exhibits a non-regular structure: a pinch region of synchronized flow within the pattern disappears and appears randomly over time; wide moving jams upstream of the pinch region exhibit a complex non-regular dynamics in which the jams appear and disappear randomly. At greater bottleneck strengths, wide moving jams merge onto a mega-wide moving jam (mega-jam) within which low-speed patterns with a complex non-regular spatiotemporal dynamics occur. We show that when the bottleneck strength is great enough, only the mega-jam survives and synchronized flow remains only within its downstream front separating free flow and congested traffic. Theoretical results presented can explain why no sequence of wide moving jams can often be distinguished in non-homogeneous traffic congestion measured at very heavy bottlenecks caused by bad weather conditions or accidents.