| 郭海锋*,黄贤恒*,徐甲**,乔洪帅*.基于动态自适应混沌粒子群优化算法的干线协调控制方法[J].高技术通讯(中文),2021,31(11):1189~1201 |
| 基于动态自适应混沌粒子群优化算法的干线协调控制方法 |
| Arterial coordinated control method based on dynamic self-adaptive chaotic particle swarm optimization algorithm |
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| DOI：10.3772/j.issn.1002-0470.2021.11.009 |
| 中文关键词: 双向绿波； Robertson离散模型； 粒子群优化算法(PSOA)； SUMO |
| 英文关键词: bidirectional green wave， Robertson’s dispersion model， particle swarm optimization algorithm (PSOA)， SUMO |
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| 摘要点击次数: 1884 |
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| 中文摘要: |
| 针对城市道路连续交叉口控制效益较低的问题，提出一种基于动态自适应混沌粒子群优化算法（DACPSOA）的干线协调控制方法。首先，通过分析上下游断面交通需求的相关性，考虑交叉口信号配时、车辆转出、车队离散等因素，在Robertson离散模型的基础上，提出了基于上游交叉口信号配时参数的车流到达率预测。在此基础上，根据车队头车、尾车到达时间与协调相位的绿灯开启时间、结束时间以及非协调相位（左转、右转）车流释放结束时间的关系，建立干线交通双向绿波控制总延误模型；其次，根据总延误模型的特征，设计了一种动态自适应混沌粒子群优化算法；最后，利用微观仿真软件SUMO建立典型的交通环境，仿真结果表明，与传统的数解法和单点控制相比，协调相位的平均延误分别降低了24.97%和57.23%，协调相位的平均停车次数分别降低了27.88%和64.01%，有效提高了交叉口的通行效率。 |
| 英文摘要: |
| Aiming at the problem of low efficiency of arterial coordinated control of urban road intersections, a method for arterial coordinated control based on dynamic self-adaptive chaotic particle swarm optimization algorithm (DACPSOA) is proposed. First, by analyzing the correlation between the traffic demands at upstream and downstream section, a method for calculating the vehicle arrival rate based on the signal control parameters of the upstream intersection is proposed, which is based on Robertson’s dispersion model and takes into account some contributing factors, such as signal control parameters, turning vehicles and platoon dispersion, etc. Second, based on the vehicle arrival rate, according to the relationship between the arrival time of the head vehicle and the tail vehicle of the fleet, the green starting and ending time of coordinated phase, and the end time of the non-coordinated phase (left turn, right turn) traffic flow release, the total delay model of bidirectional green wave for coordinated control is established. Third, based on the characteristics of delay model, a dynamic self-adaptive chaotic particle swarm optimization algorithm is designed. Last, a typical traffic environment is established by using the micro-simulating software SUMO. Simulation results show that, compared with the traditional numerical solution and the single point control, the average delay of coordinated phase is reduced by 24.97% and 57.23%, and the average stop times of coordinated phase are reduced 27.88% and 64.01%, respectively, which effectively improves the traffic efficiency of the intersection. |
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