Dynamic characteristics and simulation of traffic flow with slope

This paper proposes a new traffic model to describe traffic flow with slope under consideration of the gravity effect. Based on the model, stability analysis is conducted and a numerical simulation is performed to explore the characteristics of the traffic flow with slope. The result shows that the perturbation of the system is an inherent one, which is induced by the slope. In addition, the hysteresis loop is represented through plotting the figure of velocity against headway and highly depends on the slope angle. The kinematic wave at high density is also obtained through reproducing the phenomenon of stop-and-go traffic, which is significant to explore the phase transition of traffic flow and the evolution of traffic congestion.     

A new car-following model with consideration of the traffic interruption probability

In this paper, we present a new car-following model by taking into account the effects of the traffic interruption probability on the car-following behaviour of the following vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg--de Vries (KdV) equation is constructed and solved, and three types of traffic flows in the headway sensitivity space---stable, metastable, and unstable---are classified. Both the analytical and simulation results show that the traffic interruption probability indeed has an influence on driving behaviour, and the consideration of traffic interruption probability in the car-following model could stabilize traffic flow.     

元胞自动机混合交通流模型的能耗研究

基于元胞自动机交通流NaSch模型,提出元胞自动机混合交通流能耗公式,对混合交通流的能耗进行研究,通过数值模拟研究不同最大速度、不同车长的混合交通流的能耗;研究表明不同车长、不同最大速度以及混合比对混合交通流能耗均有不同的影响. 关键词： 交通流 元胞自动机 能耗 混合交通     

Locating Active Sensors on Traffic Networks

Sensors are used to monitor traffic in networks. For example, in transportation networks, they may be used to measure traffic volumes on given arcs and paths of the network. This paper refers to an active sensor when it reads identifications of vehicles, including their routes in the network, that the vehicles actively provide when they use the network. On the other hand, the conventional inductance loop detectors are passive sensors that mostly count vehicles at points in a network to obtain traffic volumes (e.g., vehicles per hour) on a lane or road of the network.This paper introduces a new set of network location problems that determine where to locate active sensors in order to monitor or manage particular classes of identified traffic streams. In particular, it focuses on the development of two generic locational decision models for active sensors, which seek to answer these questions: (1) “How many and where should such sensors be located to obtain sufficient information on flow volumes on specified paths?”, and (2) “Given that the traffic management planners have already located count detectors on some network arcs, how many and where should active sensors be located to get the maximum information on flow volumes on specified paths?”The problem is formulated and analyzed for three different scenarios depending on whether there are already count detectors on arcs and if so, whether all the arcs or a fraction of them have them. Location of an active sensor results in a set of linear equations in path flow variables, whose solution provide the path flows. The general problem, which is related to the set-covering problem, is shown to be NP-Hard, but special cases are devised, where an arc may carry only two routes, that are shown to be polynomially solvable. New graph theoretic models and theorems are obtained for the latter cases, including the introduction of the generalized edge-covering by nodes problem on the path intersection graph for these special cases. An exact algorithm for the special cases and an approximate one for the general case are presented.     

Existence and generic stability of solutions for multiclass multicriteria traffic equilibrium problems with capacity constraints of arcs

ABSTRACT

In this paper, we introduce the multiclass multicriteria traffic equilibrium problem with capacity constraints of arcs and its equilibrium principle. Using Fan–Browder's fixed points theorem and Fort's lemma to prove the existence and generic stability results of multiclass multicriteria traffic equilibrium flows with capacity constraints of arcs.     

药品物流多中心选址优化研究

为降低药品物流配送成本、提高药品配送效率。本文针对国家带量集中采购药品配送问题,构建了药品物流多中心选址-路径优化双目标模型。并结合模糊C-均值聚类算法(FCMA)、模拟退火算法和禁忌搜索算法各自优点,设计出了FCM-TS-SA混合算法,最后通过真实案例进行了验证、对比和分析。     

竞争环境下供应链的BOPS合作策略及其对交通拥堵改善的影响

针对由一个拥有线上直销渠道的制造商以及一个线下零售商组成的供应链,考虑消费者对不同渠道的偏好构建了供应链博弈模型,研究了竞争环境下制造商与零售商的最优BOPS合作策略,并分析了BOPS合作在改善交通拥堵方面的作用。研究表明,BOPS合作在缓解供应链双重边际效应的同时会加剧渠道之间的价格竞争,所以并不总是对供应链有利;仅当消费者线上渠道偏好程度比较低且线下麻烦成本比较大时,制造商和零售商才会都从BOPS合作中受益从而自愿达成合作,其他情形下制造商可根据供应链利润变化设计转移支付契约促成与线下零售商的BOPS合作并实现双赢;此外,一定条件下BOPS合作能够通过调整渠道需求结构,在保证供应链成员利润的同时对交通拥堵改善也带来正向作用。     

基于局域相关向量机回归模型的小尺度网络流量的非线性预测

基于非线性时间序列局域预测法与相关向量机回归模型, 本文提出了局域相关向量机预测方法, 并应用于预测实际的小尺度网路流量序列. 应用基于信息准则的局域预测法邻近点的选取方法来选取局域相关向量机回归模型的邻近点个数. 对比分析了局域相关向量机预测法、前馈神经网络模型与局域线性预测法对网络流量序列的预测性能, 其中前馈神经网络模型的参数采用粒子群优化算法来优化. 实验结果表明: 邻近点优化后的局域相关向量机回归模型能够有效地预测小尺度网络流量序列, 归一化均方误差很小; 局域相关向量机回归模型生成的时间序列具有与原网络流量时间序列相一致的概率分布; 局域相关向量机回归模型的预测精度好于前馈神经网络模型的与局域线性预测法的. 关键词： 小尺度网络流量 非线性时间序列预测方法 局域预测法 相关向量机回归模型     

基于多重分形去趋势波动分析法的交通流多重分形无标度区间自动识别方法

无标度区间是时间序列在统计意义上存在分形自相似性的尺度范围,是交通流多重分形特征研究中的重要组成部分.为解决交通流多重分形研究中多重分形去趋势波动分析法(multi-fractal detrended fluctuation analysis,MF-DFA)缺乏有效识别无标度区间方法的问题,本文在分析算法过程中交通流波动函数对数曲线突变点性质的基础上,结合传统无标度区间识别方法的构建思想,建立基于MF-DFA算法的无标度区间自动识别方法.以北京市二环快速路外环方向的部分道路为例开展实例研究,通过与传统无标度区间识别方法的结果对比,验证新方法的有效性.研究结果表明:本文方法能自动识别交通流多重分形无标度区间,且稳定性好;案例研究可知交通流短时间内波动较小、自相似性较强,随着研究时间段变长、交通流波动逐渐变大,自相似性逐渐消失,进一步解释了交通流无标度区间的有限性.     

大数据背景下基于5S的城市交通拥堵评价模型研究

近几年来,城市交通拥堵问题日益突出,极大制约了城市发展。在大数据背景下,为了准确掌握交通实时拥堵状况,改善城市交通,便利市民出行,本文深入挖掘城市交通拥堵的影响因素,构建了基于交通5S要素的城市拥堵理论模型,运用径向基函数神经网络方法工具,以上海静安寺、上海站、陆家嘴周围三大拥堵路段的交通数据集为例,验证了该模型的有效性。实验结果表明,由该模型获得的城市交通拥堵预测值与上海实际交通路况具有较好的拟合效果,表明交通5S模型与方法能够准确有效地评价城市交通拥堵。