| 引用本文: | 刘畅,魏丽英.考虑人均延误和人均排放的信号配时优化模型[J].哈尔滨工业大学学报,2018,50(9):83.DOI:10.11918/j.issn.0367-6234.201706174 |
| LIU Chang,WEI Liying.Signal timing optimization model considering per capita delay and per capita emissions[J].Journal of Harbin Institute of Technology,2018,50(9):83.DOI:10.11918/j.issn.0367-6234.201706174 |
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| 摘要: |
| 为将绿色交通、公交优先等理念融入交叉口信号配时优化的建模策略当中，建立以交叉口人均延误、人均CO排放为优化指标，以各相位有效绿灯时间为自变量的多目标信号配时优化模型.在人均延误公式中引入公交折减系数，用以避免公交绝对优先对社会车辆通行效率的负面影响.模型求解过程中运用模糊折中规划方法使量纲不同的两个目标函数实现无量纲化，令其取值在(0, l)；采用模糊偏好方法计算两个目标的隶属度函数的权重值，进而将多目标函数转化为单目标函数；然后利用自适应惯性权重和异步学习因子相结合的优化粒子群算法, 基于MATLAB软件平台实现单目标函数的求解; 最后将模型应用于实际案例，对各目标值进行比较分析.结果表明：优化后人均延误下降了0.94 s，下降幅度为3.87%.人均CO排放量下降了1.25 g，下降幅度为12.74%.说明优化后的信号配时方案对于延误和排放具有优化作用，验证了模型的有效性.
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| 关键词: 城市交通 信号配时 模糊折中规划 信号交叉口 粒子群算法 |
| DOI：10.11918/j.issn.0367-6234.201706174 |
| 分类号:U121 |
| 文献标识码:A |
| 基金项目: |
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| Signal timing optimization model considering per capita delay and per capita emissions |
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LIU Chang,WEI Liying
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（School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China）
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| Abstract: |
| To introduce the green traffic idea and the bus priority idea into the modeling strategy of signal timing optimization for intersections, a multi-objective signal timing optimization model varying with the phase effective green light time was proposed by considering the per capita delay and per capita CO emissions as the indexes. The bus deduction coefficient was introduced into the delay per capita to overcome the negative effect of absolute priority on private car. The fuzzy compromise method was used to transform the two objective functions of different dimensions into a single objective function, and to determine the values of two dimensions lie in (0, l). Fuzzy preference method was used to determine the membership function weights in the single objective function. The improved PSO (particle swarm optimization) which combines the SAPSO (self-adaptive particle swarm optimization) and the AsyLnCPSO (asynchronous learning-factor changing particle swarm optimization) were used to solve the single objective function based on the MATLAB software platform. Finally, the model was applied to an actual case and the target values were compared and analyzed. Results showed that the per capita delay reduced by 0.94s and decreased by 3.87% after optimization. The per capita CO emission reduced by 1.25g and decreased by 12.74%. The optimized signal timing scheme has an optimal effect on delay and emission, and the validity of the model was observed.
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| Key words: urban traffic signal timing fuzzy compromise programming signalized intersection particle swarm optimization |
