Guanghan Peng

A NEW LATTICE MODEL OF TRAFFIC FLOW WITH THE CONSIDERATION OF THE HONK EFFECT

In this paper, a new lattice model is presented with the consideration of the honk effect. The stability condition is obtained by the linear stability analysis. The modified Korteweg–de Vries (KdV) equation is derived to describe the phase transition of traffic flow through nonlinear analysis. The space is divided into three regions: the stable region, the metastable region and the unstable region, respectively. And numerical simulation is carried out to validate the analytic results. The results implied that the honk effect could stabilize traffic flow and suppress the traffic jam in lattice model of traffic flow.

Prevision of vehicle headway effect on urban traffic with a new car-following model

In this study, a new car-following model is established aiming to predict the variation of vehicle headways on urban road. The linear stability condition is derived corresponding to the prevision of headway in moving. The modified Korteweg–de Vries (mKdV) equation is deduced through the nonlinear analysis. The kink–antikink soliton solution of the mKdV equation can interpret the urban traffic jams near the critical point under the prevision of vehicle headway. Moreover, it is clear that the prevision of headway effect did improve the stability of urban traffic flow since the traffic jams are alleviated efficiently by taking into account the prevision of headway term in numerical simulations, which are consistent with the theoretical analysis.

Multifractal property and long-range cross-correlation behavior of particulate matters at urban traffic intersection in Shanghai

At urban road intersection, the levels of particulate matters within different size groups present multi-variable relationships and have been attracting increasing attentions. In this study, we attend to apply the recently developed multifractal detrended cross-correlation analysis method to investigate the fractal property and the cross-correlation behavior among the non-stationary time series of particulate matters. Six groups of particulate matters with different sizes are measured at a typical traffic intersection of street canyon under different seasons and weather conditions. Based on the collected database, the statistical analyses are carried out and the results indicate close relationships among these groups. Then the multifractal detrended cross-correlation analyses are performed to explore the interaction patterns among all groups, i.e., the fine particulate matters group of 0.3–0.49xa0cm with other groups, the coarse particulate matters group of 10xa0μm above with other groups, and the groups of particulate matters between the sizes of 0.5–9.99xa0μm respectively. In terms of the results, the multifractal property and long-range cross-correlation behavior are observed among all pairs. Comparing to coarse particulate matters, the distinct multifractal spectrum between fine particulate matters with other size groups are observed, which imply that the relevant cross-correlation behaviors are stronger than that in coarse group. It is also found that the cross-correlation behaviors between fine particulate matters with other size groups are highly dependent on the weather conditions while the cross-correlation behaviors between coarse particulate matters with others tend to more depend on the season variations. Finally, the long-range cross-correlation behaviors between them are also confirmed with randomly shuffled series of the observed particulate matters.

Nonlinear analysis of a new car-following model accounting for the global average optimal velocity difference

In this paper, a new car-following model is proposed by considering the global average optimal velocity difference effect on the basis of the full velocity difference (FVD) model. We investigate the influence of the global average optimal velocity difference on the stability of traffic flow by making use of linear stability analysis. It indicates that the stable region will be enlarged by taking the global average optimal velocity difference effect into account. Subsequently, the mKdV equation near the critical point and its kink–antikink soliton solution, which can describe the traffic jam transition, is derived from nonlinear analysis. Furthermore, numerical simulations confirm that the effect of the global average optimal velocity difference can efficiently improve the stability of traffic flow, which show that our new consideration should be taken into account to suppress the traffic congestion for car-following theory.