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随着高速公路监测手段的完善,高速公路运行数据日益丰富。通过深入挖掘、分析加州高速公路运行监测系统5年来收集的数据,从不同角度定量理解拥堵产生的原因,包括拥堵动态分析、交通瓶颈识别、匝道控制效益评价、出行时间预测等。此外,基于上述数据,以加州湾区HOV车道为例,通过分析通行能力损失、对比路段相同位置HOV限制与非限制时段车道流量及速度变化,定量评价了HOV车道的实施效果及其给其他车道带来的拥堵后果。上述各项研究均衡量了拥堵的严重程度及产生原因,并给出了相应的缓堵方法。
With the improvement of expressway monitoring methods, the running data of expressways is increasingly enriched. Through in-depth excavation and analysis of the data collected by the California Freeway Operation Monitoring System over the past five years, we can quantitatively understand the causes of congestion from different perspectives, including the dynamic analysis of congestion, traffic bottleneck identification, ramp control benefit evaluation, travel time forecasting and so on. In addition, based on the above data, taking HOV lanes in California Bay as an example, this paper quantitatively evaluates the effect of HOV lanes and gives other lanes by analyzing loss of capacity, comparing HOV and unrestricted lane traffic and speed changes in the same position of the road sections, Congestion brought by the consequences. The above studies all measure the seriousness of congestion and its causes, and give the corresponding methods of blockage.