A driver’s memory lattice model of traffic flow and its numerical simulation

Abstract

A new lattice model of traffic flow based on Nagatani's model is proposed by taking the effect of driver's memory into account. The linear stability condition of the extended model is obtained by using the linear stability theory. The analytical results show that the stabile area of the new model is larger than that of the original lattice hydrodynamic model by adjusting the driver's memory intensity parameter p of the past information in the system. The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis, and the phase space could be divided into three regions: the stability region, the metastable region, and the unstable region, respectively. Numerical simulation also shows that our model can stabilize the traffic flow by considering the information of driver's memory.

An Improved Car-Following Model Accounting for Impact of Strong Wind

“…In recent years, car-following theory has been rapidly developed and many models have been proposed to describe traffic phenomena and driving behavior. These new models focused on many different factors that influence car-following behavior, like the effects of time delay [6][7][8][9], multiple-vehicle in front [10][11][12][13], lane changing [14][15][16][17][18][19], the heavy vehicles [20][21][22][23], driver's behaviors [24][25][26][27][28][29][30][31][32][33], and some other factors in the literatures [34][35][36][37][38][39][40][41][42][43][44]. Nagatani [12] found that the car interaction before the next car ahead can stabilize the traffic flow.…”

Analysis of two-lane lattice hydrodynamic model with consideration of drivers’ characteristics

“…Later, many extended researches have been performed to improve the performance of Nagatani's model more realistically. Among them, some were developed by introducing the flux difference effect [18][19][20][21], the density difference effect [22][23][24], the multi-lattices effect [25,26], and the others were extended by considering drivers' physical delay [27], drivers' anticipation effect [28][29][30][31] and drivers' memory effect [32].…”

Lattice hydrodynamic model based delay feedback control of vehicular traffic flow considering the effects of density change rate difference

“…To understand the complex mechanism behind the traffic phenomenon, various traffic flow models including the microscopic and macroscopic models have been proposed. At the microscopic level, car-following models are used to describe the interactions between each pair of leading and following vehicles, and many related achievements have been obtained [1][2][3][4][5][6][7][8][9][10][11][12][13][14]; while at the macroscopic level, lattice hydrodynamic models have drawn considerable attention recently [15][16][17][18][19][20][21][22][23][24]. An important issue of traffic study is to avoid traffic jam and make the traffic flow move homogeneously.…”