Analyses of Lattice Traffic Flow Model on a Gradient Highway

The optimal current difference lattice hydrodynamic model is extended to investigate the traffic flow dynamics on a unidirectional single lane gradient highway. The effect of slope on uphill/downhill highway is examined through linear stability analysis and shown that the slope significantly affects the stability region on the phase diagram.Using nonlinear stability analysis, the Burgers, Korteweg-deVries(KdV) and modified Korteweg-deVries(mKdV) equations are derived in stable, metastable and unstable region, respectively. The effect of reaction coefficient is examined and concluded that it plays an important role in suppressing the traffic jams on a gradient highway. The theoretical findings have been verified through numerical simulation which confirm that the slope on a gradient highway significantly influence the traffic dynamics and traffic jam can be suppressed efficiently by considering the optimal current difference effect in the new lattice model.     

不同交通流状态下桥梁气动导数的风洞试验研究

为了考虑实际运营车辆对桥梁气动导数的影响,根据车辆密度模拟了三种交通流状态,基于强迫振动装置,分别对每个交通流和无车状态下的桥梁气动导数进行风洞试验研究,讨论了不同攻角下不同车流的车辆对桥梁气动导数的影响,探究了车辆对气动导数影响的百分比以及气动导数变化量的变化规律。研究结果表明:不同攻角下不同车流的车辆均对直接导数A*2、H*4和交叉导数A*4、H*2影响显著,A*2、A*3变化量随着折减风速有一定的变化规律。虽然不同攻角下不同车流的车辆对气动导数的影响程度及影响规律不同,并且车流的繁忙程度对大多数气动导数的影响规律不明显,但是车辆对桥梁气动导数的影响不容忽略。     

Traffic flow prediction based on BILSTM model and data denoising scheme

Accurate prediction of road traffic flow is a significant part in the intelligent transportation systems. Accurate prediction can alleviate traffic congestion, and reduce environmental pollution. For the management department, it can make effective use of road resources. For individuals, it can help people plan their own travel paths, avoid congestion, and save time. Owing to complex factors on the road, such as damage to the detector and disturbances from environment, the measured traffic volume can contain noise. Reducing the influence of noise on traffic flow prediction is a piece of very important work. Therefore, in this paper we propose a combination algorithm of denoising and BILSTM to effectively improve the performance of traffic flow prediction. At the same time, three denoising algorithms are compared to find the best combination mode. In this paper, the wavelet (WL) denoising scheme, the empirical mode decomposition (EMD) denoising scheme, and the ensemble empirical mode decomposition (EEMD) denoising scheme are all introduced to suppress outliers in traffic flow data. In addition, we combine the denoising schemes with bidirectional long short-term memory (BILSTM) network to predict the traffic flow. The data in this paper are cited from performance measurement system (PeMS). We choose three kinds of road data (mainline, off ramp, on ramp) to predict traffic flow. The results for mainline show that data denoising can improve prediction accuracy. Moreover, prediction accuracy of BILSTM+EEMD scheme is the highest in the three methods (BILSTM+WL, BILSTM+EMD, BILSTM+EEMD). The results for off ramp and on ramp show the same performance as the results for mainline. It is indicated that this model is suitable for different road sections and long-term prediction.     

不确定条件下的乡村中小学布局优化

学校的合理规划布局是实现教育资源优化配置、提高办学效益和推动教育均衡发展的重要途径。已有许多学者研究了学校的布局问题,但基本上都忽略了交通网络条件以及不确定因素对学校布局的影响。本研究将在前人研究基础上,重点考虑交通网络对乡村中小学选址的影响,并假设旅行时间具有不确定性,从而以最小化学生旅行成本、学校建设、道路修建和道路升级成本为目标,构建不确定条件下的设施区位设计模型。在算法求解方面提出混合模拟退火算法,用于确定新建学校的最佳位置,以及新道路的修建和原有道路的升级情况。最后,将提出的模型和算法应用到实际案例中。     

基于SD-VF理论的城市限行政策效应研究

随着我国城市化进程不断加快,城市交通供需矛盾日益突出,交通拥堵问题愈发严重,我国各地纷纷实行各种政策措施来缓解交通拥堵。本文以北京市为例,针对城市交通拥堵的现象,从系统的角度出发,运用系统动力学与灰色Verhulst预测相结合的方法(SD-VF),建立城市交通治堵模型,并采用Vensim软件对模型进行动态仿真分析,从经济、社会、环境等方面探究政策措施对城市环境生态承载力、道路生态承载力等的影响。研究结果表明,限行限号政策虽然在一定程度上提高道路生态承载力,但也可能引发“悖论”效应;修路政策并没有根本上解决城市交通拥堵问题,仅仅是把拥堵状况向后推迟;而相对于单一政策,将发展公共交通与限行政策相结合可以有效缓解交通拥堵,改善空气质量,提升环境承载力,是更加科学合理的政策措施。     

基于粒子群的模糊神经网络的短时交通流量组合预测

为了进一步提高短时交通流量预测的精度,提出了一种粒子群算法的模糊神经网络组合预测模型,模糊神经网络融合了神经网络的学习机制和模糊系统的语言推理能力等优点,弥补各自不足,将自回归求和滑动平均(ARIMA)和灰色Verhulst模型进行初步预测,并将两种初步预测的结果作为模糊神经网络的输入,构建基于改进模神经网络的组合预测模型,在此基础上进行训练和预测,其中模糊神经网络的相关参数由改进粒子群来优化,利用本方法来对南京市汉中路短时交通流量进行预测,结论表明:方法充分发挥了单一模型的优势,比单一的预测模型更加精确,是短时交通流量预测的一个有效方法。     

A 4D-sequencing approach for air traffic management

The current air traffic system is forecasted to face strong challenges due to the continuous increase in air traffic demand. Hence, there is a need for new types of organization permitting a more efficient air traffic management, with both a high capacity and a high level of safety, and possibly with a reduced environmental impact. In this article, we study a holistic approach, consisting in designing across Europe a very organized air traffic system, as opposed to free flight, to reduce costs while maintaining safety.     

Solving the logit-based stochastic user equilibrium problem with elastic demand based on the extended traffic network model

This paper proposes a novel extended traffic network model to solve the logit-based stochastic user equilibrium (SUE) problem with elastic demand. In this model, an extended traffic network is established by properly adding dummy nodes and links to the original traffic network. Based on the extended traffic network, the logit-based SUE problem with elastic demand is transformed to the SUE problem with fixed demand. Such problem is then further converted to a linearly constrained convex programming and addressed by a predictor–corrector interior point algorithm with polynomial complexity. A numerical example is provided to compare the proposed model with the method of successive averages (MSA). The numerical results indicate that the proposed model is more efficient and has a better convergence than the MSA.