Optimization method of configuration of traffic flow guidance information board in urban
Article Text (Baidu Translation)
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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.
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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 
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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
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