基于交通状态估计的快速路交通联合控制

doi:10.13229/j.cnki.jdxbgxb201701012

摘要/Abstract

摘要：

采用模糊C均值聚类方法将快速路交通状态划分为畅通、轻度拥挤和拥挤状态。将快速路二阶宏观交通流模型与粒子滤波算法相结合,实现对快速路交通状态参数的估计,并将交通状态参数估计结果划分到对应状态中,得到交通状态估计结果。在交通状态估计的基础上,考虑3种交通状态下的交通运行特性,结合可变限速控制和入口匝道控制建立快速路联合控制模型。采集吉林省长春市东部快速路交通数据进行实例验证,结果表明:联合控制模型的应用减少了快速路交通流总时间费用消耗的4.55%,降低了交通流密度,在一定程度上缓解了交通拥挤。

关键词: 交通运输系统工程, 快速路, 交通状态估计, 可变限速控制, 入口匝道控制

Abstract:

Expressway traffic state is divided into unimpeded, slight smooth and congested sub-states by fuzzy C-means clustering method. Combining expressway second-order macroscopic traffic flow model with particle filter algorithm, the traffic state parameters are estimated. By clustering the estimation values of the parameters to one of the three kinds of traffic sub-states, the corresponding traffic state estimation is obtained. Based on the traffic state estimation and the characteristics of each traffic sub-state, an expressway joint control model is established, which combines variable speed-limit control and on-ramp control. The traffic data of Changchun East-expressway is used to validate the model. Results show that the total time spend of the expressway is reduced by 4.55% and the traffic flow density is also reduced. The traffic congestion is eased to certain extent.

Key words: engineering of communications and transportation system, expressway, traffic state estimation, variable speed-limit control, on-ramp control

中图分类号:

U491

贾洪飞, 李永行, 杨丽丽. 基于交通状态估计的快速路交通联合控制[J]. 吉林大学学报(工学版), 2017, 47(1): 76-81.

JIA Hong-fei, LI Yong-xing, YANG Li-li. Expressway traffic joint control based on traffic state estimation[J]. 吉林大学学报(工学版), 2017, 47(1): 76-81.

参考文献

[1] Chen D, Ahn S. Variable speed limit control for severe non-recurrent freeway bottlenecks[J]. Transportation Research Part C, 2015, 51: 210-230.
[2] 陈学文,王殿海,金盛,等. 城市快速路入口匝道控制方法[J]. 吉林大学学报:工学版,2008, 38(增刊): 43-48.
Chen Xue-wen,Wang Dian-hai,Jin Sheng,et al. On-ramp metering control strategy of urban expressway[J].Journal of Jilin University(Engineering and Technology Edition),2008,38(Sup.):43-48.
[3] Lim K,Kim J H, Shin E, et al. A signal control model integrating arterial intersections and freeway off-ramps[J]. KSCE Journal of Civil Engineering, 2011, 15(2): 385-394.
[4] Geroliminis N, Srivastava A, Michalopoulos P. A dynamic-zone-based coordinated ramp-metering algorithm with queue constraints for Minnesota's freeways[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4): 1576-1586.
[5] Carlson R C,Papamichail I, Papageorgion M, et al. Optimal motorway traffic flow control involving variable speed limits and ramp metering[J]. Transportation Science, 2010, 44(2): 238-253.
[6] 姜桂艳,郭海锋,吴超腾.基于感应线圈数据的城市道路交通状态判别方法[J].吉林大学学报:工学版,2008,38(增刊):37-42.
Jiang Gui-yan,Guo Hai-feng,Wu Chao-teng.Identification method of urban road traffic conditions based on inductive coil data[J].Journal of Jilin University(Engineering and Technology Edition),2008,38(Sup.):37-42.
[7] 岳立. 基于FCM的城市快速路交通状态动态识别研究[D]. 成都:西南交通大学数学学院,2013.
Yue Li. Dynamic discrimination of urban freeway traffic state based on fuzzy C-means[D]. Chengdu:School of Mathematics, Southwest Jiaotong University, 2013.
[8] Bi Jun, Guan Wei, Qi Long-tao. A genetic resampling particle filter for freeway traffic state estimation[J]. Chinese Physics B, 2012, 21(6):068901.
[9] Bi Jun,Chang Can,Fan Yang. Particle filter for estimating freeway traffic state in Beijing[J]. Mathematical Problems in Engineering,2013,2013:382042.
[10] 孙静怡,沈俊江,刘拥华,等. 城市快速路可变限速策略[J]. 公路交通科技,2012, 29(11): 98-103.
Sun Jing-yi, Shen Jun-jiang, Liu Yong-hua, et al. Variable speed limits strategy of urban expressway[J]. Journal of Highway and Transportation Research and Development, 2012, 29(11): 98-103.
[11] 柴干,谢永利. 高速公路匝道多性能指标优化控制方法[J]. 中国公路学报,2012, 25(6): 115-122.
Chai Gan, Xie Yong-li. Control method of multi-performance indexes optimizing on expressway ramp metering[J]. China Journal of Highway and Transport, 2012, 25(6): 115-122.
[12] 高祥云,柴干.高速公路入口匝道的协调优化控制[J].交通运输工程与信息学报,2013,11(3):106-112.
Gao Xiang-yun, Chai Gan. Optimal coordination control of entry ramp of freeway[J]. Journal of Transportation Engineering and Information, 2013, 11(3): 106-112.

相关文章 15

[1]	陈永恒,刘芳宏,曹宁博. 信控交叉口行人与提前右转机动车冲突影响因素[J]. 吉林大学学报(工学版), 2018, 48(6): 1669-1676.
[2]	常山,宋瑞,何世伟,黎浩东,殷玮川. 共享单车故障车辆回收模型[J]. 吉林大学学报(工学版), 2018, 48(6): 1677-1684.
[3]	曲大义,杨晶茹,邴其春,王五林,周警春. 基于干线车流排队特性的相位差优化模型[J]. 吉林大学学报(工学版), 2018, 48(6): 1685-1693.
[4]	宗芳, 齐厚成, 唐明, 吕建宇, 于萍. 基于GPS数据的日出行模式-出行目的识别[J]. 吉林大学学报(工学版), 2018, 48(5): 1374-1379.
[5]	刘翔宇, 杨庆芳, 隗海林. 基于随机游走算法的交通诱导小区划分方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1380-1386.
[6]	钟伟, 隽志才, 孙宝凤. 不完全网络的城乡公交一体化枢纽层级选址模型[J]. 吉林大学学报(工学版), 2018, 48(5): 1387-1397.
[7]	刘兆惠, 王超, 吕文红, 管欣. 基于非线性动力学分析的车辆运行状态参数数据特征辨识[J]. 吉林大学学报(工学版), 2018, 48(5): 1405-1410.
[8]	宗芳, 路峰瑞, 唐明, 吕建宇, 吴挺. 习惯和路况对小汽车出行路径选择的影响[J]. 吉林大学学报(工学版), 2018, 48(4): 1023-1028.
[9]	栾鑫, 邓卫, 程琳, 陈新元. 特大城市居民出行方式选择行为的混合Logit模型[J]. 吉林大学学报(工学版), 2018, 48(4): 1029-1036.
[10]	陈永恒, 刘鑫山, 熊帅, 汪昆维, 谌垚, 杨少辉. 冰雪条件下快速路汇流区可变限速控制[J]. 吉林大学学报(工学版), 2018, 48(3): 677-687.
[11]	王占中, 卢月, 刘晓峰, 赵利英. 基于改进和声搜索算法的越库车辆排序[J]. 吉林大学学报(工学版), 2018, 48(3): 688-693.
[12]	李志慧, 胡永利, 赵永华, 马佳磊, 李海涛, 钟涛, 杨少辉. 基于车载的运动行人区域估计方法[J]. 吉林大学学报(工学版), 2018, 48(3): 694-703.
[13]	陈松, 李显生, 任园园. 公交车钩形转弯交叉口自适应信号控制方法[J]. 吉林大学学报(工学版), 2018, 48(2): 423-429.
[14]	苏书杰, 何露. 步行交通规划交叉路口行人瞬时动态拥塞疏散模型[J]. 吉林大学学报(工学版), 2018, 48(2): 440-447.
[15]	孟品超, 李学源, 贾洪飞, 李延忠. 基于滑动平均法的轨道交通短时客流实时预测[J]. 吉林大学学报(工学版), 2018, 48(2): 448-453.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed