Optimization method of configuration of traffic flow guidance information board in urban
-
摘要: 为合理进行城市交通流诱导, 提出了一种基于提高诱导覆盖率和减小诱导重复率双重约束下的信息板配置优化方法。在分区的道路网络条件和交通需求点分布确定的情况下, 以追求分区内被诱导的交通量最大为前提, 建立信息板优化布局函数, 并通过遗传算法设计了信息板优化布局函数求解算法, 在提高整个诱导覆盖率和减少诱导重复率的双重约束下确定信息板的合理数量。通过一个15个节点的网络实例验证, 当设置6块信息板时, 诱导重复率为1.000, 且其诱导覆盖率也达到了0.978, 为最优配置。结果显示该信息板配置方法能在一定交通诱导重复率的基础上达到交通诱导覆盖率最大, 是一种提高交通流诱导效率的有效方法。Abstract: In order to distribute traffic flow guidance information board(TFGIB) in urban properly, the optimization model of configuration of TFGIB was put forward based on the restriction of improving guidance coverage rate and reducing guidance repeat rate.The layout optimization function of TFGIB to maximize the guiding rate of traffic volume was established on the presumption that road network condition and traffic demand area were ensured, the algorithm of the layout function was designed on the basis of genetic algorithm, and the reasonable quantity of TFGIB was confirmed under the restriction.The model was proved through a road network with 15 nodes.It is pointed that when 6 TFGIB are collocated in the net, the guidance repeat rate is 1.000, the guiding coverage rate reaches 0.978, and it is optimal configuration.The result indicates that the method can get the maximum guiding coverage rate under determinate guiding repeat rate, and is an effective method to improve traffic guidance efficiency.
-
表 1 交通流量分布
Table 1. Traffic flow distribution
编号 交通量 分配路径 修正路径 q1A 100 1→2→3→DA 1→2→3→DA q5A 60 5→4→3→DA 5→4→3→DA q6A 100 6→7→8→DA 6→7→8→DA q10A 90 10→9→8→DA 10→9→8→DA q11A 70 11→12→13→8→DA 11→12→13→8→DA q15A 80 15→14→9→8→DA 15→14→9→8→DA q1B 60 1→2→DB 1→2→DB q5B 40 5→4→9→8→7→DB 4→9→8→7→DB q6B 90 6→7→DB 6→7→DB q10B 100 10→9→8→7→DB 10→9→8→7→DB q11B 50 11→12→7→DB 11→12→7→DB q15B 60 15→14→9→8→7→DB 14→9→8→7→DB q1C 80 1→2→7→8→DC 1→2→7→8→DC q5C 90 5→4→3→8→DC 5→4→3→8→DC q6C 120 6→7→8→DC 6→7→8→DC q10C 100 10→9→8→DC 10→9→8→DC q11C 130 11→12→13→DC 11→12→13→DC q15C 80 15→14→9→8→DC 15→14→9→8→DC q1D 30 1→2→7→8→DD 1→2→7→8→DD q5D 60 5→4→9→DD 5→4→9→DD q6D 50 6→7→8→DD 6→7→8→DD q10D 80 10→9→DD 10→9→DD q11D 30 11→12→13→8→DD 11→12→13→8→DD q15D 50 15→14→9→DD 15→14→9→DD 
下载: 导出CSV
表 2 不同数量下TFGIB的优化选择
Table 2. Optimization Choices with different TFGIB quantities
TFGIB的块数 设置路段 诱导的总交通量 诱导覆盖率 诱导重复率 1 L9-8 550 0.306 1.000 2 L7-8, L9-8 930 0.517 1.000 3 L7-8, L9-8, L11-12 1 210 0.672 1.000 4 L1-2, L6-7, L9-8, L11-12 1 460 0.811 1.000 5 L1-2, L5-4, L6-7, L9-8, L11-12 1 670 0.928 1.000 6 L1-2, L5-4, L6-7, L10-9, L11-12, L14-9 1 760 0.978 1.000 7 L1-2, L5-4, L4-9, L6-7, L10-9, L11-12, L14-9 1 800 1.000 1.033
下载: 导出CSV
-
[1] Daxwanger W, Schmidt G. Skill-based vehicle guidance by use of artificial neural network[J]. Mathematics in Simulation, 1996, 41(3): 263-27. [2] Russell G, Thompson G, Kunimichi T, et al. Understanding the demand for access information[J]. Transportation Research: Part C, 1998, 6(4): 231-245. doi: 10.1016/S0968-090X(98)00017-5 [3] Ben A M, De P A, Isam K. Dynamic network models and driver information systems[J]. Transportation Research: Part A, 1991, 25(5): 251-266. doi: 10.1016/0191-2607(91)90142-D [4] 曾松. 城市道路网络交通导行策略研究[D]. 上海: 同济大学, 2000. [5] 周永华. 交通流预测控制的机制与方法[J]. 中国公路学报, 2007, 20(1): 107-111. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200701019.htmZhou Yong-hua. Mechanism and approach of traffic flow predictive control[J]. China Journal of Highway and Transport, 2007, 20(1): 107-111. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200701019.htm [6] 许世燕, 贺昱曜, 李渊. 基于最大车速的广义力跟驰模型[J]. 长安大学学报: 自然科学版, 2007, 27(1): 72-75. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL200701016.htmXu Shi-yan, He Yu-yao, Li Yuan. Generalized force model of car's following based on maximum velocity[J]. Journal of Chang'an University: Natural Science Edition, 2007, 27(1): 72-75. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL200701016.htm [7] 黎冬平. 城市停车诱导信息板配置的优化技术研究[D]. 南京: 东南大学, 2006. [8] 陈峻, 周智勇, 王炜. 不对等信息显示的城市停车预调度方法[J]. 中国公路学报, 2006, 19(4): 103-108. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200604018.htmChen Jun, Zhou Zhi-yong, Wang Wei. Urban parking pre-dispatch methods with non-opposite information appearance[J]. China Journal of Highway and Transport, 2006, 19(4): 103-108. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200604018.htm [9] 张红彦, 赵丁选, 陈宁, 等. 基于遗传算法的工程车辆自动变速神经网络控制[J]. 中国公路学报, 2006, 19(1): 117-121. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200601024.htmZhang Hong-yan, Zhao Ding-xuan, Chen Ning, et al. Neural network control of automatic shift for construction vehicle based on genetic algorithm[J]. China Journal of Highway and Transport, 2006, 19(1): 117-121. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200601024.htm -
点击查看大图
图(4) / 表(2)
计量
- 文章访问数: 343
- HTML全文浏览量: 124
- PDF下载量: 449
- 被引次数: 0
