Qing-Song Wu

A new continuum model for traffic flow and numerical tests

A new continuum traffic flow model is developed in this paper based on an improved car-following model. In this new continuum model, the speed gradient replaces the density gradient in the equation of motion, and this replacement guarantees the property that the characteristic speeds are always less than or equal to the macroscopic flow speed. This new model also overcomes the backward travel problem that exists in many high-order continuum models. Shock waves, rarefaction waves, stop-and-go waves, and local cluster effects can be obtained from this new model and are consistent with the diverse nonlinear dynamical phenomena observed in the freeway traffic.

Cellular automata models for synchronized traffic flow

This paper presents a new cellular automata model for describing synchronized traffic flow. The fundamental diagrams, the spacetime plots and the 1 min average data have been analysed in detail. It is shown that the model can describe the outflow from the jams, the light synchronized flow as well as heavy synchronized flow with average speed greater than approximately 24 km h−1. As for the synchronized flow with speed lower than 24 km h−1, it is unstable and will evolve into the coexistence of jams, free flow and light synchronized flow. This is consistent with the empirical findings (Kerner B S 1998 Phys. Rev. Lett. 81 3797).

Traffic experiment reveals the nature of car-following

As a typical self-driven many-particle system far from equilibrium, traffic flow exhibits diverse fascinating non-equilibrium phenomena, most of which are closely related to traffic flow stability and specifically the growth/dissipation pattern of disturbances. However, the traffic theories have been controversial due to a lack of precise traffic data. We have studied traffic flow from a new perspective by carrying out large-scale car-following experiment on an open road section, which overcomes the intrinsic deficiency of empirical observations. The experiment has shown clearly the nature of car-following, which runs against the traditional traffic flow theory. Simulations show that by removing the fundamental notion in the traditional car-following models and allowing the traffic state to span a two-dimensional region in velocity-spacing plane, the growth pattern of disturbances has changed qualitatively and becomes qualitatively or even quantitatively in consistent with that observed in the experiment.

Spatial?temporal patterns at an isolated on-ramp in a new cellular automata model based on three-phase traffic theory

This paper studies the spatial–temporal patterns at an isolated on-ramp using a new cellular automata model based on three-phase traffic theory. The model may describe the synchronized flow quite satisfactorily (Jiang and Wu 2003 J. Phys. A: Math. Gen. 36 381). The simulations show that six different regions may be classified in the new model induced by an isolated on-ramp. The spacetime plots of the patterns as well as the metastability are investigated. Comparison with the empirical data is made and the qualitative similarity is pointed out. The future work of extension from single-lane simulation to the multi-lane case is pointed out.

Stochastic multi-value cellular automata models for bicycle flow

In this paper, the stochastic randomization is introduced in two different multi-value cellular automata (CA) models in order to model the bicycle flow. It is shown that with the randomization effect considered, the multiple states in the deterministic multi-value CA models disappear and the unique flow-density relations (fundamental diagrams) exist. The fundamental diagrams, the spacetime plots of the two models, are studied in detail. It is found that the transition from free flow to congested flow is smooth in one model while it is of second order in the other model. The comparison of the results of the two models indicates that in the bicycle flow, the priority of the movement should be given to slow bicycles in order to reach a larger maximum flow rate.

Urban traffic from the perspective of dual graph

Abstract.Urban traffic is modeled using a dual graph representation of the urban transport network, where roads are mapped to nodes and intersections are mapped to links. The proposed model considers both the navigation of the vehicles in the network and the motion of the vehicles along roads. The vehicle-holding ability of roads and the vehicle-turning ability at intersections are also incorporated. The overall handling ability of the system can be quantified by a phase transition from free flow to congestion. Simulations show that the systems handling ability greatly depends on the topology of the transportation network. In general, a well-planned grid can hold more vehicles, and its overall handling ability is much greater than that of a growing self-organized network.

A new dynamics model for traffic flow

As a study method of traffic flow, dynamics models were developed and applied in the last few decades. However, there exist some flaws in most existing models. In this note, a new dynamics model is proposed by using carfollowing theory and the usual connection method of micro-macro variables, which can overcome some ubiquitous problems in the existing models. Numerical results show that the new model can very well simulate traffic flow conditions, such as congestion, evacuation of congestion, stop-and-go phenomena and phantom jam.

The effect of bandwidth in scale-free network traffic

This paper models the effects of bandwidth on the traffic capacity of scale-free networks. We investigate the decrease of the system traffic capacity and the variation of the optimal local routing coefficient αc, induced by the restriction of bandwidth. For low bandwidth, the same optimal value of αc emerges for two different cases of node capacity, namely C = constant and Ci = ki, where ki denotes the degree of the i-th node. By investigating the number of packets at each node in the free-flow state, we provide analytical explanations for the optimal value of αc. Average packet travelling time, distribution of packet travelling time, and average visits per node divided by the node connectivity are also studied.

Inefficient emergent oscillations in intersecting driven many-particle flows

Oscillatory flow patterns have been observed in many different driven many-particle systems. It seems reasonable to assume that the emergent oscillations in opposing flows are due to or related to an increased efficiency (throughput). In this contribution, however, we will study intersecting pedestrian and vehicle flows as an example for inefficient emergent oscillations. In the coupled vehicle–pedestrian delay problem, oscillating pedestrian and vehicle flows form when pedestrians cross the street with a small time gap to approaching cars, while both pedestrians and vehicles benefit, when they keep some overcritical time gap. That is, when the safety time gap of pedestrians is increased, the average delay time of pedestrians decreases and the vehicle flow goes up. This may be interpreted as a slower-is-faster effect. The underlying mechanism of this effect is explained.

A unified framework for the pareto law and Matthew effect using scale-free networks

Abstract.We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)∼m-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agents personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.