In order to develop the intelligent transportation system, this paper presents an extended car-following model called Multiple Information(MI) model based on Multiple Velocity Difference(MVD) model. It attempts to enhance the stability of the traffic flow by using the acceleration and the velocity differences of multiple vehicles. It can be found that the critical value of the sensitivity in MI model decreases and the stable region is apparently enlarged, compared with MVD model. Simulations are made repeatedly, in which the driver’s sensitivity is different value. Results show that MI model is more realistic than traditional ones, and can better describe the dynamics and complexity of traffic flow.%为开发智能交通系统，在多速度差(MVD)模型的基础上，提出一个扩展模型，即多信息(MI)模型。在MI模型中，采用前车的加速度信息以及速度差信息提高交通流的稳定性。通过稳定性理论，得到MI模型下线性稳定临界曲线。MI模型比它相应的MVD模型有明显的改善，稳定敏感系数临界值变小，稳定区域明显增加。对驾驶员灵敏度系数在不同取值情况下，分别进行反复数值模拟仿真，结果表明，MI模型能更好地描述交通流的波动特性。
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