An Intelligent Driver Model Simulation Considering Both Backward Looking Effect and Velocity Difference

doi:10.16182/j.issn1004731x.joss.22-0341

Abstract

Abstract:

Aiming at the phenomenon that driver adjusts vehicle movement by observing the following vehicles through rearview mirror in the actual car-following driving, an improved intelligent driver model accounting forboth backward looking effect and velocity difference is proposed, and the critical stability condition of the new model is obtained by employing the linear stability analysis. Based on the numerical simulation experiments, the car following characteristics analysis during the acceleration process of the vehicle and the traffic safety evaluation are carried out. A small disturbance simulation under the periodic boundary condition is used to verify the conclusion consistency of stability theoretical analysis and numerical simulation. Results show that the vehicle acceleration changes more smoothly, and the time for the vehicle to reach the maximum speed and enter a constant speed state is shorter; the simultaneous consideration of the backward looking effect and velocity difference also plays an important role in strengthening the traffic flow stability and traffic safety.

Key words: intelligent driver model, backward looking effect, traffic flow stability, traffic safety, numerical simulation

CLC Number:

TP391.9

Yin Xu, Yun Pu, Haixu Liu, Yifan Tan. An Intelligent Driver Model Simulation Considering Both Backward Looking Effect and Velocity Difference[J]. Journal of System Simulation, 2023, 35(7): 1562-1571.

Figures/Tables 6

Fig. 1

Fig. 2

Table 1

Impacts of different values p on TET index

k	不同 $T E T$ 计算值
k	2.0	2.5	3.0	3.5
0.10	11.4	30.9	42.5	51.5
0.15	5.0	17.2	33.1	43.0
0.20	4.8	8.1	18.4	33.9
0.25	3.0	8.0	11.4	13.4
0.30	2.9	6.8	10.4	12.7

Table 1

Table 2

Impacts of different values p on TIT index

k	不同 $T I T$ 计算值
k	2.0	2.5	3.0	3.5
0.10	1.57	13.01	31.50	55.07
0.15	1.29	5.66	18.86	37.99
0.20	1.10	4.37	9.87	23.45
0.25	0.91	3.91	8.53	14.32
0.30	0.83	3.13	7.58	13.41

Table 2

Fig. 3

Fig. 4

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