基于多源数据的干线协调控制策略

Arterial Coordinate Control Strategy Based on Multi-Source Data

为针对不同的交通流状态选取合适的干线协调控制策略,基于线圈、视频、微波获取的多源实时交通数据,利用车队离散模型和卡尔曼滤波模型获取各转向流量,采用HCM(Highway Capacity Manual)公式计算排队长度和延误,并根据干道交叉口排队长度界定干线交通流状态:欠饱和、接近饱和、过饱和,从而选择相应的干线协调控制策略:在欠饱和状态下采用最大绿波带法,在接近饱和状态下采用改进的多带宽协调模型,在过饱和状态下采用排队占比最小模型。以青岛市香港中路为例,通过VISSIM仿真软件对算法和策略进行仿真测试和评价,结果表明:不同交通状态下的干线协调策略与原始控制方案相比,平均延误减少了19.4%,平均停车次数减少了22.8%,平均排队长度减少了7.4%。

In order to select appropriate arterial coordinate control strategies for different traffic flowstates, based on the multi-source data from coil, video and microwave, the turning flows were obtainedby using Platoon Dispersion Model and Kalman Filter Model, while the queue length and delay were cal-culated through the formula in Highway Capacity Manual. Traffic flow states, including under-saturated,near-saturated and over-saturated, were identified according to queue length and then corresponding ar-terial coordination strategies were chosen. The MAX Green Wave Band Model was used in the under-saturated state, the improved Bandwidth Coordination Model in the near-saturated state and the MinimalQueue Proportion Model in the over-saturate state. Taking Hong Kong Road in Qingdao as the example,simulation assessment results of VISSIM show the proposed model decreases the average delay by19.4%, average number of stops by 22.8%and average queue length by 7.4% compared with originalstrategies.