车流密度变化条件下的跟驰模型研究

把车流密度的跳跃性变化作为车流波现象,在高峰小时或者异常情况下(如雨、雪、雾等异常天气),快速路的瓶颈地段经常出现堵塞以及由堵塞引起的车流波。车流波不仅影响瓶颈点下游车辆的运行,还会降低瓶颈点上游路段的有效通过能力。通过大量的交通数据采集,构建基于模糊推理的驾驶员感知——预测行为模型和车流波传播条件下驾驶员微观跟驰模型。结果表明,模型可以有效、准确地模拟车流波传播过程中驾驶员行为。

The Car Following Model During Traffic Flow Density Diversification

When the traffic flow density change sharply, we call this phenomenon shockwaves. Many traffic accidents in high- speed urban expressways in Beijing are attributed to shockwaves. During morning and evening peak hours or bad weather (like rainy, snowy or foggy), congestions often happen at the bottleneck of urban expressway, which may lead to shockwaves happening. Shockwaves not only affect capacities of expressways, but also aggravate energy consumption and air pollution to the surrounding environment. The thesis begins with basic data, build a fuzzy logic model of driving anticipation effect during shockwave propagation and a modified car-following model based on driving anticipation effect and show good results.