From the macroscopic viewpoint for describing the acceleration behaviour of drivers, a weighted probabilistic cellular automaton model （the WP model, for short） is proposed by introducing a kind of random accelerati...From the macroscopic viewpoint for describing the acceleration behaviour of drivers, a weighted probabilistic cellular automaton model （the WP model, for short） is proposed by introducing a kind of random acceleration probabilistic distribution function. The fundamental diagrams, the spatiotemporal patterns, are analysed in detail. It is shown that the presented model leads to the results consistent with the empiricaZ data rather well, nonlinear flow-density relationship existing in lower density regions, and a new kind of traific phenomenon called neo-synchronized flow. Furthermore, we give the criterion for distinguishing the high-speed and low-speed neo-synchronized flows and clarify the mechanism of this kind of traffic phenomenon. In addition, the result that the time evolution of distribution of headways is displayed as a normal distribution further validates the reasonability of the neo-synchronized flow. These findings suggest that the diversity and the randomicity of drivers and vehicles have indeed a remarkable effect on traffic dynamics.展开更多
The conventional car-following theory is based on the assumption that vehicles will travel along the center line of lanes. However, according to the field survey data, in complex traffic conditions, a lateral separati...The conventional car-following theory is based on the assumption that vehicles will travel along the center line of lanes. However, according to the field survey data, in complex traffic conditions, a lateral separation between the leader and the follower frequently occurs. Accordingly, by taking lateral separation into account, we redefined the equation of time-to-collision (TTC) using visual angle information. Based on the stimulus-response framework, TTC was introduced into the basic General Motors (GM) model as a stimulus, and a non-lane-based car-following model of steady-state traffic flow was developed. The property of flow-density relationship was further investigated after integrating the proposed car-following model with different parameters. The results imply that the property of steady-state traffic flow and the capacity of each lane are highly relevant to the microscopic staggered car-following behavior, and the proposed model significantly enhances the practicality of the human driving behavior model.展开更多
基金supported by the National Basic Research Program of China (Grant No 2006CB705500)the National Natural Science Foundation of China (Grant Nos 10532060 and 10562001)+1 种基金the Special Research Fund for the Doctoral Program in Higher Education of China (Grant No SRFDP 20040280014)the Shanghai Leading Academic Discipline Project of China (Grant NoY0103)
文摘From the macroscopic viewpoint for describing the acceleration behaviour of drivers, a weighted probabilistic cellular automaton model （the WP model, for short） is proposed by introducing a kind of random acceleration probabilistic distribution function. The fundamental diagrams, the spatiotemporal patterns, are analysed in detail. It is shown that the presented model leads to the results consistent with the empiricaZ data rather well, nonlinear flow-density relationship existing in lower density regions, and a new kind of traific phenomenon called neo-synchronized flow. Furthermore, we give the criterion for distinguishing the high-speed and low-speed neo-synchronized flows and clarify the mechanism of this kind of traffic phenomenon. In addition, the result that the time evolution of distribution of headways is displayed as a normal distribution further validates the reasonability of the neo-synchronized flow. These findings suggest that the diversity and the randomicity of drivers and vehicles have indeed a remarkable effect on traffic dynamics.
基金Project supported by the National Natural Science Foundation of China (No. 70971053)the National High-Tech R&D Program (863) of China (No. 2011AA110304)the China Postdoctoral Science Foundation (No. 20100481419)
文摘The conventional car-following theory is based on the assumption that vehicles will travel along the center line of lanes. However, according to the field survey data, in complex traffic conditions, a lateral separation between the leader and the follower frequently occurs. Accordingly, by taking lateral separation into account, we redefined the equation of time-to-collision (TTC) using visual angle information. Based on the stimulus-response framework, TTC was introduced into the basic General Motors (GM) model as a stimulus, and a non-lane-based car-following model of steady-state traffic flow was developed. The property of flow-density relationship was further investigated after integrating the proposed car-following model with different parameters. The results imply that the property of steady-state traffic flow and the capacity of each lane are highly relevant to the microscopic staggered car-following behavior, and the proposed model significantly enhances the practicality of the human driving behavior model.
