The satisfaction rate of desired velocity in the case of a mixture of fast and slow vehicles is studied by using a cellular automaton method. It is found that at low density the satisfaction rate depends on the maxima...The satisfaction rate of desired velocity in the case of a mixture of fast and slow vehicles is studied by using a cellular automaton method. It is found that at low density the satisfaction rate depends on the maximal velocity. However, the behavior of the satisfaction rate as a function of the coefficient of variance is independent of the maximal velocity. This is in good agreement with empirical results obtained by Lipshtat [Phys. Rev. E 79 066110 （2009）]. Furthermore, our numerical result demonstrates that at low density the satisfaction rate takes higher values, whereas the coefficient of variance is close to zero. The coefficient of variance increases with increasing density, while the satisfaction rate decreases to zero. Moreover, we have also shown that, at low density the coefficient variance depends strongly on the probability of overtaking.展开更多
In this paper, we have investigated two observed situations in a multi-lane road. The first one concerns a fast merging vehicle. The second situation is related to the case of a fast vehicle leaving the fastest lane b...In this paper, we have investigated two observed situations in a multi-lane road. The first one concerns a fast merging vehicle. The second situation is related to the case of a fast vehicle leaving the fastest lane back into the slowest lane and targeting a specific way out. We are interested in the relaxation time T, i.e., which is the time that the merging （diverging） vehicle spends before reaching the desired lane. Using analytical treatment and numerical simulations for the NaSch model, we have found two states, namely, the free state in which the merging （diverging） vehicle reaches the desired lane, and the trapped state in which T diverges. We have established phase diagrams for several values of the braking probability. In the second situation, we have shown that diverging from the fast lane targeting a specific way out is not a simple task. Even if the diverging vehicle is in the free phase, two different states can be distinguished. One is the critical state, in which the diverging car can probably reach the desired way out. The other is the safe state, in which the diverging car can surely reach the desired way out. In order to be in the safe state, we have found that the driver of the diverging car must know the critical distance （below which the way out will be out of his reach） in each lane. Furthermore, this critical distance depends on the density of cars, and it follows an exponential law.展开更多
文摘The satisfaction rate of desired velocity in the case of a mixture of fast and slow vehicles is studied by using a cellular automaton method. It is found that at low density the satisfaction rate depends on the maximal velocity. However, the behavior of the satisfaction rate as a function of the coefficient of variance is independent of the maximal velocity. This is in good agreement with empirical results obtained by Lipshtat [Phys. Rev. E 79 066110 （2009）]. Furthermore, our numerical result demonstrates that at low density the satisfaction rate takes higher values, whereas the coefficient of variance is close to zero. The coefficient of variance increases with increasing density, while the satisfaction rate decreases to zero. Moreover, we have also shown that, at low density the coefficient variance depends strongly on the probability of overtaking.
文摘In this paper, we have investigated two observed situations in a multi-lane road. The first one concerns a fast merging vehicle. The second situation is related to the case of a fast vehicle leaving the fastest lane back into the slowest lane and targeting a specific way out. We are interested in the relaxation time T, i.e., which is the time that the merging （diverging） vehicle spends before reaching the desired lane. Using analytical treatment and numerical simulations for the NaSch model, we have found two states, namely, the free state in which the merging （diverging） vehicle reaches the desired lane, and the trapped state in which T diverges. We have established phase diagrams for several values of the braking probability. In the second situation, we have shown that diverging from the fast lane targeting a specific way out is not a simple task. Even if the diverging vehicle is in the free phase, two different states can be distinguished. One is the critical state, in which the diverging car can probably reach the desired way out. The other is the safe state, in which the diverging car can surely reach the desired way out. In order to be in the safe state, we have found that the driver of the diverging car must know the critical distance （below which the way out will be out of his reach） in each lane. Furthermore, this critical distance depends on the density of cars, and it follows an exponential law.
