Effects of Adaptive Random Deceleration on Traffic Flow

Based on the Nagel-Schreckenberg model, an improved cellular automaton traffic flow model is proposed, in which the random deceleration probability of each vehicle is no longer fixed, but is adaptively adjusted according to the local traffic density in its vision and its current velocity. The numerical simulation results show that the maximum traffic capacity of the improved model under the same parameters is greater than that of the Nagel-Schreckenberg model, and is closer to the measured data. In addition, the traffic flow and vehicle velocity under different meteorological conditions are simulated by using the improved model, and the synchronized flow phenomenon consistent with the actual traffic is reproduced. Meanwhile, the results show that under the same parameters, when the traffic density is equal to 0.3, the traffic flow of the improved model increases by about 11% compared with the original model, and when the traffic density increases to 0.6, the traffic flow increases by about 27%. .

Effect of acceleration threshold on the phase transition in a cellular automaton traffic flow model

In this paper, we incorporate new parameters into a cellular automaton traffic flow model proposed in our previous paper [Jin et al. 2010 J. Stat. Mech. 2010 P03018]. Through these parameters, we adjust the anticipated velocity and the acceleration threshold separately. It turns out that the flow rate of synchronized flow mainly changes with the anticipated velocity, and the F →S phase transition feature mainly changes with the acceleration threshold. Therefore, we conclude that the acceleration threshold is the major factor affecting the F → S phase transition.

A modified weighted probabilistic cellular automaton traffic flow model

This paper modifies the weighted probabilistic cellular automaton model （Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366） which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers＇ desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.

The effect of stochastic acceleration and delay probability on the velocity and the gap between vehicles in traffic flow

This paper proposes a new combined cellular automaton （CA） model considering the driver behavior of stochastic acceleration and delay with the velocity of the preceding vehicle and the gap between the successive vehicles based on the WWH model and the noise-first NaSch model. It introduces the delay probability varying with the gap, adds the anticipation headway and increases the acceleration with a certain probability. Through these simulations, not only can the metastable state and start-stop wave be obtained but also the synchronized flow which the wide moving jam results in. Moreover, the effect of stochastic acceleration and delay on traffic flow is discussed by analyzing the correlation of traffic data. This indicates that synchronized flow easily emerges in the critical area between free flow and synchronized flow when acceleration and delay are synchronized or their probability is close to 0.5.

On the modeling of synchronized flow in cellular automaton models

In this paper, we further analyze our cellular automaton （CA） traffic flow model. By changing some parameters, the characteristics of our model can be significantly varied, ranging from the features of phase transitions to the number of traffic phases. We also review the other CA models based on Kerner＇s three-phase traffic theory. By comparisons, we find that the core concepts for modeling the synchronized flow in these models are similar. Our model can be a good candidate for modeling the synchronized flow, since there is enough flexibility in our framework.

Characteristics of synchronized traffic in mixed traffic flow

In this paper, the characteristics of synchronized traffic in mixed traffic flow are investigated based on the braking light model. By introducing the energy dissipation and the distribution of slowdown vehicles, the effects of the maximum velocity, the mixing ratio, and the length of vehicles on the synchronized flow are discussed. It is found that the maximum velocity plays a great role in the synchronized flow in mixed traffic. The energy dissipation and the distribution of slowdown vehicles in the synchronized flow region are greatly different from those in free flow and a traffic jamming region. When all of vehicles have the same maximum velocity with Vmax 〉 15, the mixed traffic significantly displays synchronized flow, which has been demonstrated by the relation between flow rate and occupancy and estimation of the cross-correlation function. Moreover, the energy dissipation in the synchronized flow region does not increase with occupancy. The distribution of slowdown vehicles shows a changeless platform in the synchronized flow region. This is an interesting phenomenon. It helps to deeply understand the synchronized flow and greatly reduce the energy dissipation of traffic flow.