考虑环境影响的可变限速控制研究
发布时间：2018-09-08 13:55
【摘要】：本文提出了一种考虑环境影响下的高速公路可变限速控制方案的优化方法。其中方案评价模型包含几个子模型,分别为交通流仿真模型、车辆尾气排放量计算模型和排放物扩散模型。通过细胞传递模型,得到下一步模型需要的交通流数据,然后通过交通流数据判断车辆行驶状态,得出每辆车在每个时间步长内的排放值。接着利用高斯烟羽模型来模拟排放物扩散的过程,计算路侧排放物浓度。然后利用基于人口密度的相对排放物浓度来量化对环境的负面影响,由此评价一个方案的好坏。 方案的最优化采用基于细胞传递模型仿真的遗传算法。首先确定染色体的结构,然后通过选择,选出具有优良基因的父代,接着经过染色体交叉和变异生成子代,子代中的方案需要经过筛选、修正或淘汰,再进入评价模型来判断每个方案的适应度值,从而确定每个子代被选为下一代父代的概率。 最后通过若干算例分析来验证整个模型。
[Abstract]:In this paper, an optimization method of variable speed limit control scheme for freeway considering the influence of environment is proposed. The scheme evaluation model includes several sub-models, which are traffic flow simulation model, vehicle exhaust emission calculation model and emission diffusion model. Through the cell transfer model, the traffic flow data needed by the next model are obtained, and then the vehicle driving state is judged by the traffic flow data, and the emission value of each vehicle within each time step is obtained. Then, Gao Si smoke plume model was used to simulate the emission diffusion process and to calculate the roadside emission concentration. Then the relative emission concentration based on population density is used to quantify the negative impact on the environment and evaluate the effectiveness of a scheme. Genetic algorithm based on cell transfer model is used to optimize the scheme. The structure of the chromosomes is determined first, and then the parent generations with good genes are selected by selection, and then the offspring is generated by chromosome crossover and variation. The schemes in the offspring need to be screened, modified or eliminated. Then the evaluation model is used to judge the fitness of each scheme, and the probability of each offspring being selected as the next generation parent is determined. Finally, the whole model is verified by several examples.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491
[Abstract]:In this paper, an optimization method of variable speed limit control scheme for freeway considering the influence of environment is proposed. The scheme evaluation model includes several sub-models, which are traffic flow simulation model, vehicle exhaust emission calculation model and emission diffusion model. Through the cell transfer model, the traffic flow data needed by the next model are obtained, and then the vehicle driving state is judged by the traffic flow data, and the emission value of each vehicle within each time step is obtained. Then, Gao Si smoke plume model was used to simulate the emission diffusion process and to calculate the roadside emission concentration. Then the relative emission concentration based on population density is used to quantify the negative impact on the environment and evaluate the effectiveness of a scheme. Genetic algorithm based on cell transfer model is used to optimize the scheme. The structure of the chromosomes is determined first, and then the parent generations with good genes are selected by selection, and then the offspring is generated by chromosome crossover and variation. The schemes in the offspring need to be screened, modified or eliminated. Then the evaluation model is used to judge the fitness of each scheme, and the probability of each offspring being selected as the next generation parent is determined. Finally, the whole model is verified by several examples.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491
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