基于相位队列演进的单交叉口自适应控制策略

doi:10.13229/j.cnki.jdxbgxb.20240359

摘要/Abstract

摘要：

针对现阶段交叉口自适应控制算法存在控制迭代效率低、模型复杂度高的问题，基于相位内队列消散情况提出了一种自适应控制算法。首先，建立参数预测模型实现配时参数优化，并基于车流波动理论计算得到车辆在交叉口处的停车延误；其次，基于速度变化曲线计算得到车辆进入和驶出交叉口时的加、减速延误；最后，提出状态转移矩阵用于延误最小化动态优化模型的构建，进而实现交叉口信号控制的全阶段优化。将固定配时控制和感应控制作为对照组，发现超高负荷交通流场景下本文方法相较于两个对照组，车均延误分别减少了55%和27.8%，平均停车次数减少了58.5%和10.1%；高负荷交通流场景下车均延误分别减少了36.1%和14.6%，平均停车次数减少了23.4%和8.7%；中负荷交通流场景下车均延误分别减少了22.8%和10.5%，平均停车次数减少了3.3%和2.6%。结果表明：在不同的交通流负荷条件下，本文算法均能有效提高交叉口的运行效率。

关键词: 交通运输系统工程, 自适应控制, 相位队列演进, 流量预测, 动态优化

Abstract:

An adaptive control algorithm based on the in-phase queue dissipation was proposed to address the issues of low control efficiency and high model complexity in existing signal control algorithms. Firstly， a prediction model was established to optimize signal timing parameters， and calculate the vehicle's stopping delay based on traffic shockwave theory. Secondly， the acceleration and deceleration delays of vehicles were calculated based on the speed variation curve. Finally， state transition matrix for constructing dynamic optimization model was proposed to minimize delays， thereby realizing full-stage optimization of intersection signal control. Compared with fixed-time control and actuated control methods， the proposed method respectively reduced the average delay by 55% and 27.8% per vehicle in ultra-high-traffic demand scenario and reduced the average number of stops by 58.5% and 10.1%. In high-traffic demand scenario， the average delay decreased by 36.1% and 14.6% per vehicle， and the average number of stops decreased by 23.4% and 8.7%， respectively. In medium-traffic scenario， the average delay decreased by 22.8% and 10.5% per vehicle， and the average number of stops decreased by 3.3% and 2.6%. The results indicate that the algorithm proposed in this study can effectively improve the traffic operational efficiency at isolated intersections under different traffic demand conditions.

Key words: engineering of communication and transportation, adaptive signal control, phase queue simulation, flow prediction, dynamic optimization

中图分类号:

U491

王道斌,赵慧慧,徐缘缘,柳祖鹏. 基于相位队列演进的单交叉口自适应控制策略[J]. 吉林大学学报(工学版), 2025, 55(12): 3862-3874.

Dao-bin WANG,Hui-hui ZHAO,Yuan-yuan XU,Zu-peng LIU. Adaptive control strategy for isolated intersection based on phase queue simulation[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(12): 3862-3874.

图/表 17

图1

图2

图3

图4

图5

图6

图7

图8

表1

表2

表3

表4

配时方案"

进口	直行时间/s	左转时间/s	左转放行顺序
进口	固定/感应 $G m i n$	固定/感应 $G m i n$	左转放行顺序
东	45/35	30/25	lead
西	30/25	15/15	lag
南	60/35	20/15	lag
北	60/35	20/15	lag

表4

图9

图10

图11

图12

图13

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进口	直行/行人 /［（veh·h^-1）/（p·h^-1）］	左转/（veh·h^-1）	右转/（veh·h^-1）	合计/（veh·h^-1）
东	297/161	147	114	558
西	213/137	78	120	411
南	694/251	111	60	865
北	660/140	102	33	795

进口	直行/行人 /［（veh·h^-1）/（p·h^-1）］	左转/（veh·h^-1）	右转/（veh·h^-1）	合计/（veh·h^-1）
东	396/214	196	152	744
西	284/182	104	160	584
南	925/334	148	80	1 153
北	880/186	136	44	1 060

进口	直行/行人 /［（veh·h^-1）/（p·h^-1）］	左转/（veh·h^-1）	右转/（veh·h^-1）	合计/（veh·h^-1）
东	495/268	245	190	930
西	355/228	130	200	685
南	1 156/418	185	100	1 441
北	1 100/233	170	55	1 325