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%。
In order to solve the problem of uneven distribution of toll lane resources in expressway toll stations, a method of toll lane opening and closing configuration based on traffic flow prediction is proposed by combining Bayesian optimization algorithm(BOA) and long short term memory(LSTM) neural network. First, the toll data is preprocessed to obtain basic data such as traffic volume, vehicle type proportion, toll method proportion and service time, which are used to build the model training dataset. Secondly, a M/G/K queueing model based on multiple charging method is proposed to achieve the theoretical description of toll station passing process and the calculation of key indicators such as average queue length, average stay time and traffic capacity. Thirdly, aiming at the difficult problem of hyperparameter setting, a combination model of BOA-LSTM is constructed with Bayesian optimization algorithm to achieve traffic flow prediction. Then, with the traffic flow prediction results as input and the number of lane openings as output, a lane opening and closing configuration model with the goal of minimum comprehensive cost is constructed. Finally, taking Hebei Xinyuan Expressway airport toll station as an example, the empirical analysis shows that the BOA-LSTM combination model can achieve good prediction results, in which the root mean square error of traffic volume and vehicle type proportion are 16.24 and 0.03 respectively, and the mean absolute percentage error is 13.32% and 1.77% respectively. Compared with the current scheme, the average daily comprehensive cost of working days is reduced by 2.30% and the average daily comprehensive cost of rest days is reduced by 5.14%.
史博,宋锋,李轶群,等. 基于交通流预测的高速公路收费站车道开闭配置[J]. 科学技术与工程, 2023, 23(30): 13157-13164.
Shi Bo, Song Feng, Li Yiqun, et al. Lane Opening and Closing Configuration of Expressway Toll Station Based on Traffic Flow Prediction[J]. Science Technology and Engineering,2023,23(30):13157-13164.