拥堵指数自适应调节的交通运行状态识别方法及应用研究

Traffic Performance Identification Method Based on Adaptive Congestion Index

拥堵指数是客观评价城市交通运行状态的有效指标。针对当前拥堵指数模型中对交通畅行速度时空特性考虑不足的问题,本文在车辆定位与路网时空匹配数据的基础上,引入概率密度分段原理对车辆速度进行距离和时间分段,建立了具有自适应调节能力的拥堵指数模型,用于城市交通运行状态的分类与识别。以厦门市节假日浮动车辆定位数据为例,仿真分析了拥堵指数模型在复杂道路和城市交通中的适用性,并揭示了城市交通运行状态的变化规律。分析结果表明:拥堵指数模型能有效区分道路的空闲和繁忙时段,并依据对应时段的畅行速度进行自适应调节;针对复杂互通立交和专用共线道路,拥堵指数计算结果相较传统方法平均提升了6.5%和3.2%;厦门市交通为单一晚高峰拥堵形态,平均拥堵指数介于1.0~3.0之间,拥堵时间为16:10-21:00,空间分布集中在厦门市进出岛方向的主干道枢纽位置,以及厦门岛内东西走向主干道。该项研究对于快速建立不同城市及具有特殊时段需求的交通运行识别方法起到积极作用。

The congestion index is a useful tool for objectively assessing the performance of urban traffic.The current congestion index model does not take into account the spatial-temporal characteristics of traffic free-flow speed sufficiently.The probability density segmentation method is introduced into the spatial-temporal matching of vehicle positioning and road network in this study to divide the vehicle speed into distance and time segments.A congestion index with adaptive adjustment capability is proposed for the classification and identification of urban traffic performance.Using Xiamen's holiday floating vehicle positioning data as an example,the applicability of the congestion index model in complex roads and urban traffic is investigated,and the change law of urban traffic performance is revealed.The results show that the congestion index model can effectively distinguish the idle and busy periods of the roads,and adjust the traffic speed adaptively according to the traffic speed in the corresponding period.For complex interchanges and dedicated collinear roads,the calculation results of the congestion index are increased by 6.5%and 3.2%compared with the traditional methods.Xiamen's traffic is characterized by a single evening peak.The average congestion index is between 1.0 and 3.0,and the peak time for congestion is 18:10 to 21:00.The spatial distribution is concentrated in the hub of the main road in and out of Xiamen Island and the East-West main road in the island.The result plays a positive role in quickly establishing traffic performance identification methods for different cities and the needs of special periods.