To investigate drivers' lane-changing behavior under different information feedback strategies,a microscopic traffic simulation based on the cellular automaton model was made on the typical freeway with a regular ...To investigate drivers' lane-changing behavior under different information feedback strategies,a microscopic traffic simulation based on the cellular automaton model was made on the typical freeway with a regular lane and a high-occupancy one. A new dynamic tolling scheme in terms of the real-time traffic condition on the high-occupancy lane was further designed to enhance the whole freeway's flow throughput. The results show that the mean velocity feedback strategy is generally more efficient than the travel time feedback strategy in correctly guiding drivers' lane choice behavior. Specifically,the toll level,lane-changing rate and freeway's throughput and congestion coefficient induced by the travel time feedback strategy oscillate with larger amplitude and longer period. In addition,the dynamic tolling scheme can make the high-occupancy lane less congested and maximize the freeway's throughput when the regular-lane inflow rate is larger than 0.45.展开更多
针对高速公路收费站的收费车道资源分配不均问题,结合贝叶斯优化算法(bayesian optimization algorithm,BOA)和长短时记忆神经网络(long short term memory,LSTM),提出了一种基于交通流预测的收费车道开闭配置方法。首先,对收费数据进...针对高速公路收费站的收费车道资源分配不均问题,结合贝叶斯优化算法(bayesian optimization algorithm,BOA)和长短时记忆神经网络(long short term memory,LSTM),提出了一种基于交通流预测的收费车道开闭配置方法。首先,对收费数据进行预处理,得到交通量、车型比例、收费方式占比和服务时间等基础数据,用于构建模型训练数据集。其次,提出了一种基于多元收费方式的M/G/K排队模型,实现收费站通行过程的理论描述和平均排队长度、平均逗留时间、通行能力等关键指标的计算。然后,针对超参数设置困难问题,引入贝叶斯优化算法构建了BOA-LSTM组合模型实现交通流预测。接着,以交通流预测结果为输入,以车道开启数目为输出,构建了一种以综合成本最小为目标的车道开闭配置模型。最后,以河北新元高速机场收费站为例展开实证分析,结果表明,BOA-LSTM组合模型能够取得良好的预测效果,其中交通量和车型比例的均方根误差分别为16.24和0.03,平均绝对百分比误差分别为13.32%和1.77%;相比于实际方案,工作日平均每天的综合成本降低了2.30%,休息日平均每天的综合成本降低了5.14%。展开更多
基金Project(70521001) supported by the National Natural Science Foundation of ChinaProject(2006CB705503) supported by the National Basic Research Program of ChinaProject supported by the Innovation Foundation of BUAA for PhD Graduates
文摘To investigate drivers' lane-changing behavior under different information feedback strategies,a microscopic traffic simulation based on the cellular automaton model was made on the typical freeway with a regular lane and a high-occupancy one. A new dynamic tolling scheme in terms of the real-time traffic condition on the high-occupancy lane was further designed to enhance the whole freeway's flow throughput. The results show that the mean velocity feedback strategy is generally more efficient than the travel time feedback strategy in correctly guiding drivers' lane choice behavior. Specifically,the toll level,lane-changing rate and freeway's throughput and congestion coefficient induced by the travel time feedback strategy oscillate with larger amplitude and longer period. In addition,the dynamic tolling scheme can make the high-occupancy lane less congested and maximize the freeway's throughput when the regular-lane inflow rate is larger than 0.45.
文摘针对高速公路收费站的收费车道资源分配不均问题,结合贝叶斯优化算法(bayesian optimization algorithm,BOA)和长短时记忆神经网络(long short term memory,LSTM),提出了一种基于交通流预测的收费车道开闭配置方法。首先,对收费数据进行预处理,得到交通量、车型比例、收费方式占比和服务时间等基础数据,用于构建模型训练数据集。其次,提出了一种基于多元收费方式的M/G/K排队模型,实现收费站通行过程的理论描述和平均排队长度、平均逗留时间、通行能力等关键指标的计算。然后,针对超参数设置困难问题,引入贝叶斯优化算法构建了BOA-LSTM组合模型实现交通流预测。接着,以交通流预测结果为输入,以车道开启数目为输出,构建了一种以综合成本最小为目标的车道开闭配置模型。最后,以河北新元高速机场收费站为例展开实证分析,结果表明,BOA-LSTM组合模型能够取得良好的预测效果,其中交通量和车型比例的均方根误差分别为16.24和0.03,平均绝对百分比误差分别为13.32%和1.77%;相比于实际方案,工作日平均每天的综合成本降低了2.30%,休息日平均每天的综合成本降低了5.14%。
