物联网技术在物流园区货物配送中的应用研究

本文以物流园区货物配送系统的运行管理为研究对象,分析物联网技术在货物配送系统中的应用情况,并以物流配送中的带时间窗的车辆路径问题(VRPTW)为例,研究外包形式的配送模式在利用物联网技术提高服务效率的情形下,物流配送运行管理中的配送路径可能发生的变化,以说明物联网技术应用在物流园区货物配送管理中的应用效果。     

带时间窗约束的集装箱接驳运输问题模型研究

集装箱接驳运输是集装箱运输过程中的重要环节。针对带有时间窗约束的集装箱接驳运输问题,本文首先考虑四种集装箱接驳运输任务(进口重箱,出口重箱,进口空箱,出口空箱)的实际运输要求,确定其时间窗约束,其次,基于图论知识,采用一种确定的活动在顶点上的图的描述方法,将集装箱接驳运输问题转化为一个混合0-1线性规划模型,考虑其计算复杂度,设计了一种改进的遗传算法对该问题进行求解。最后给出算例,运用本文的求解方法进行计算,结果与其他方法相比较,本文所提出的算法比目前已知的最优解差了2.1%,但是计算速度提高了51.4%。总体上在目标函数值和计算时间上都较优。     

路段通行时间不确定下取送货车辆路径优化研究

城市高峰期交通拥堵呈常态化趋势,各运输路段的通行时间很难用精确值表达,而配送车辆的路径仍需具体指定,亟需研究路段通行时间不确定情况下的物流配送车辆的具体运输路径。文章统筹考虑配送时间与环境成本,结合Bertsimas鲁棒离散优化理论,以总行程时间和碳排放量最小为优化目标,构建了路段时间阻抗不确定情况下的同时取送货多配送中心多车路径鲁棒优化模型,采用遗传算法进行求解,并以呼和浩特市部分路网为例进行实证研究。研究结果表明:车辆路径鲁棒优化模型及其改进的遗传算法能快速生成鲁棒性能较好的车辆行驶路径,而且得到的是一条条具体的运输路径,而非配送顺序。该模型与算法能为物流配送车辆路径导航系统提供技术支撑。     

插电式混合动力汽车绿色路径规划研究

为了降低插电式混合动力汽车(Plug-in Hybrid Electric Vehicle,PHEV)在驾驶过程中的能耗,本文对插电式混合动力汽车绿色路径规划问题(Plug-in Hybrid Electric Vehicle Green Routing Problem,PHEVGRP)进行了研究。基于脉冲耦合神经网络提出了用时间依赖中继神经网络求解时间依赖车辆路径规划问题。基于可实时获取的道路交通状态量建立PHEV能耗计算模型。采用硬参数共享多任务学习建立道路交通状态量的预测模型。结合两个模型,将时间依赖中继神经网络应用于PHEVGRP的求解。采用真实数据进行试验,结果表明所提出的方法能够求得PHEVGRP的基于预测模型的最优解且求解速度优于启发式算法。     

基于AFC数据的客流路径选择

在单一路径旅行时间近似服从正态分布的假设下,建立了描述多路径OD对旅行时间分布的高斯混合模型,并引入无监督聚类算法——EM算法求解模型。首先,根据单路径无换乘和单路径一次换乘的OD,分别估计进出站时间消耗和换乘时间消耗的分布参数;然后,生成多路径OD的有效路径集并估计路径旅行时间参数;最后,将贝叶斯信息准则确定的混合模型个数及其对应的路径旅行时间分布参数,作为初始值输入到EM算法中,计算得到各路径的客流分配比例。以成都地铁两对典型OD为例,编程求解了客流分配比例和旅行时间分布参数,计算结果显示模型的拟合结果较好。     

基于OBD、GPS与3G技术的车辆性能远程监控系统

为提高车队管理和车辆维修技术水平,提出并设计一套车辆性能远程监控系统,该系统整合OBD、GPS、3G无线通信模块和GIS平台,可将采集的车辆运行状态信息和定位信息等透过3G网络回传至企业监控中心,便于使用者实时掌握车辆的运行状况,包括车辆OBD故障信息、车速、引擎转速、电瓶电压、冷却水温、行车日期与时间、行车地点与路径信息等。该系统可使车辆保修人员与车队管理人员远程了解车辆的实时状况与所在位置,从而做出相应的维修和管理对策,对保持车辆正常的技术状况、实现节能、环保、安全运营具有较高的应用价值。     

定制公交多目标鲁棒优化模型与算法

为了确定定制公交在路网中的行驶路径,文章研究了乘客等车时间不确定环境中定制公交行驶路线的鲁棒优化问题:(1)以最小化运营公司的经营费用、最小化乘客的出行时间为优化目标,以车辆的容量限制、乘客的上、下车时间窗、不确定的乘客等车时间等为约束条件,建立了定制公交多目标鲁棒优化模型;(2)采用改进的NSGA-Ⅱ算法(Nondominated Sorting Genetic AlgorithmⅡ)进行求解,用基于未到达交通节点顺序的自然数编码方法进行编码,以锦标赛选择策略进行选择操作以及采用均匀变异方式进行变异操作;(3)选取兰州市局部路网进行案例研究。研究结果表明,运用本文建立的定制公交多目标鲁棒优化模型及求解算法,能快速得到满足优化目标的行驶路径。选用合理的行驶路线能够节约乘客的出行成本,增加运营公司的收益。     

公路隧道紧急停车带智慧引导系统设计及应用分析

高速公路隧道内的空间密闭性及容易受光线、温湿度、能见度等环境条件影响,会造成紧急停车带的标志和指示牌的模糊和不易辨认,导致提醒效果不佳:当隧道内发生交通事故或者出现异常状况时,由于紧急停车带的不规范停车,降低了停车带的使用效率,容易导致二次事故。为解决上述问题,文章结合AI边缘计算技术、物联网、传感器等先进技术,设计了高速公路隧道紧急停车带智慧引导系统。经实际应用可知,该系统可提高事故应急处置能力和效率,对进入紧急停车带的车辆人员提供引导帮助和安全预警,对驶离停车带的车辆进行安全行驶引导,并及时对进出紧急停车带车辆后方车辆做出预警和诱导,对高速公路隧道行车安全起到了至关重要的作用。     

“货车+无人机”配送模式下订单拣选与配送联合优化研究

电子商务环境下订单特有的特征要求企业必须进行拣选与配送的联合决策,而"货车+无人机"的配送模式结合了货车运量大和无人机配送速度快的特点,可以有效的提高配送效率。本文以拣选和配送总成本最低,综合考虑"货车+无人机"配送模式、多拣选批次、多配送批次、带时间窗等因素,研究"货车+无人机"配送路径、拣选分批、拣选路径等联合决策问题,并设计了PVRPTW-D遗传算法和"S"型拣选策略进行求解,通过算例验证了本文所提出的模型和算法的有效性。     

混合动力客车排放测试及分析

混合动力车辆在节能和环保方面相对于传统车辆有很明显的优势,文章采用车载排放设备对混合动力客车和传统客车进行了排放对比测试试验,验证了混合动力车辆可以减少车辆污染物的排放,为混合动力车辆环保效能的评估提供了依据。     

Isolated intersection control for various levels of vehicle technology: Conventional,connected, and automated vehicles

Connected vehicle technology can be beneficial for traffic operations at intersections. The information provided by cars equipped with this technology can be used to design a more efficient signal control strategy. Moreover, it can be possible to control the trajectory of automated vehicles with a centralized controller. This paper builds on a previous signal control algorithm developed for connected vehicles in a simple, single intersection. It improves the previous work by (1) integrating three different stages of technology development; (2) developing a heuristics to switch the signal controls depending on the stage of technology; (3) increasing the computational efficiency with a branch and bound solution method; (4) incorporating trajectory design for automated vehicles; (5) using a Kalman filter to reduce the impact of measurement errors on the final solution. Three categories of vehicles are considered in this paper to represent different stages of this technology: conventional vehicles, connected but non-automated vehicles (connected vehicles), and automated vehicles. The proposed algorithm finds the optimal departure sequence to minimize the total delay based on position information. Within each departure sequence, the algorithm finds the optimal trajectory of automated vehicles that reduces total delay. The optimal departure sequence and trajectories are obtained by a branch and bound method, which shows the potential of generalizing this algorithm to a complex intersection.Simulations are conducted for different total flows, demand ratios and penetration rates of each technology stage (i.e. proportion of each category of vehicles). This algorithm is compared to an actuated signal control algorithm to evaluate its performance. The simulation results show an evident decrease in the total number of stops and delay when using the connected vehicle algorithm for the tested scenarios with information level of as low as 50%. Robustness of this algorithm to different input parameters and measurement noises are also evaluated. Results show that the algorithm is more sensitive to the arrival pattern in high flow scenarios. Results also show that the algorithm works well with the measurement noises. Finally, the results are used to develop a heuristic to switch between the different control algorithms, according to the total demand and penetration rate of each technology.     

An improved Dial's algorithm for logit-based traffic assignment within a directed acyclic network

Abstract

Dial's algorithm is one of the most effective and popular procedures for a logit-type stochastic traffic assignment, as it does not require path enumeration over a network. However, a fundamental problem associated with the algorithm is its simple definition of ‘efficient paths’, which sometimes produces unrealistic flow patterns. In this paper, an improved algorithm based on the route extension coefficient is proposed in order to circumvent this problem, in which ‘efficient paths’ simultaneously consider link travel cost and minimum travel cost. Path enumeration is still not required and a similar computing efficiency with the original algorithm is guaranteed. A limitation of the algorithm is that it can only be applied to a directed acyclic network because a topological sorting algorithm is used to decide the order of the sequential calculation. A numerical example based on the Beijing subway network illustrates the effectiveness of the proposed algorithm. It is found that it is able to exclude most unrealistic paths, but include all reasonable paths when compared with path enumeration and the original Dial's algorithm.     

基于改进鱼群算法在管道最优抢修路径的研究

当油气管道发生安全事故时,为保证在最短的时间内达到事故现场,需选择最优的抢维修路径。文中提出了一种新型的最优路径计算方法——鱼群算法,并针对其在搜索空间、收敛性以及寻求最优解等方面存在的不足,提出了改进鱼群算法。结合实际工程案例,对鱼群算法和改进鱼群算法在相同循环次数下寻求最短路径做了对比,结果显示改进的鱼群算法成功率高、收敛快,具有一定的应用价值。     

Classifiers for driver activity monitoring

The goal of this work is the detection and classification of driver activities in an automobile using computer vision. To this end, this paper presents a novel two-step classification algorithm, namely, an unsupervised clustering algorithm for grouping the actions of a driver during a certain period of time, followed by a supervised activity classification algorithm. The main contribution of this work is the combination of the two methods to provide a computationally fast solution for deployment in real-world scenarios that is robust to illumination and segmentation issues under most conditions experienced in the automobile environment. The unsupervised clustering groups the actions of the driver based on the relative motion detected using a skin-color segmentation algorithm, while the activity classifier is a binary Bayesian eigenimage classifier. Activities are grouped as safe or unsafe and the results of the classification are shown on several subjects obtained from two distinct driving video sequences.     

Method for investigating intradriver heterogeneity using vehicle trajectory data: A Dynamic Time Warping approach

After first extending Newell’s car-following model to incorporate time-dependent parameters, this paper describes the Dynamic Time Warping (DTW) algorithm and its application for calibrating this microscopic simulation model by synthesizing driver trajectory data. Using the unique capabilities of the DTW algorithm, this paper attempts to examine driver heterogeneity in car-following behavior, as well as the driver’s heterogeneous situation-dependent behavior within a trip, based on the calibrated time-varying response times and critical jam spacing. The standard DTW algorithm is enhanced to address a number of estimation challenges in this specific application, and a numerical experiment is presented with vehicle trajectory data extracted from the Next Generation Simulation (NGSIM) project for demonstration purposes. The DTW algorithm is shown to be a reasonable method for processing large vehicle trajectory datasets, but requires significant data reduction to produce reasonable results when working with high resolution vehicle trajectory data. Additionally, singularities present an interesting match solution set to potentially help identify changing driver behavior; however, they must be avoided to reduce analysis complexity.     

Adaptive control algorithm to provide bus priority with a pre-signal

In urban areas, where road space is limited, it is important to provide efficient public and private transportation systems to maximize person throughput, for example from a signalized intersection. To this end, this research looks at providing bus priority using a dedicated bus lane which is terminated upstream of the intersection, and placing an additional signal at this location, called a pre-signal. Although pre-signals are already implemented in some countries (e.g. UK, Denmark, and Switzerland), an adaptive control algorithm which responds to varying traffic demands has not yet been proposed and analyzed in the literature. This research aims to fill that gap by developing an adaptive control algorithm for pre-signals tailored to real-time private and public transportation demands. The necessary infrastructure to operate an adaptive pre-signal is established, and guidelines for implementation are provided. The relevant parameters regarding the boundary conditions for the adaptive algorithm are first determined, and then quantified for a typical case using a micro-simulation model. It is demonstrated with case studies that, under all considered scenarios, implementing a pre-signal with the proposed adaptive control algorithm will result in the least average person delay at the intersection. The algorithm is expected to function well with a wide range of car demands, bus frequencies, and bus passenger occupancies. Moreover, the algorithm is robust to errors in these input values, so exact information is not required.     

A route-based solution algorithm for dynamic user equilibrium assignments

The aim of this study is to establish a method to calculate good quality user equilibrium assignments under time varying conditions. For this purpose, it introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it shows a novel route-based solution algorithm. This novel algorithm turns out to be convenient and logically plausible compared to the conventional [Frank, M., Wolfe, P., 1956. An algorithm for quadratic programming. Naval Research Logistics Quarterly 3, 95–110] algorithm, because the former does not require evaluation of an objective function and it finds solutions maintaining correct flow propagation in the time-varying network conditions. The application of novel dynamic network loading method and solution algorithm to test networks shows that we can find high quality dynamic user equilibrium assignment. This is illustrated in an example network using the deterministic queuing model for a link performance function and associating costs and flows in a predictive way in discrete time.     

Development of realistic shortest path algorithm considering lane changes

Lane changes occur as many times as turning movements are needed while following a designated path. The cost of a route with many lane changes is likely to be more expensive than that with less lane changes, and unrealistic paths with impractical lane changes should be avoided for drivers' safety. In this regard, a new algorithm is developed in this study to find the realistic shortest path considering lane changing. The proposed algorithm is a modified link‐labeling Dijkstra algorithm considering the effective lane‐changing time that is a parametric function of the prevailing travel speed and traffic density. The parameters were estimated using microscopic traffic simulation data, and the numerical test demonstrated the performance of the proposed algorithm. It was found that the magnitude of the effect of the effective lane‐changing time on determining the realistic shortest path is nontrivial, and the proposed algorithm has capability to exclude links successfully where the required lane changes are practically impossible. Copyright © 2015 John Wiley & Sons, Ltd.     

基于RBF神经网络的发动机怠速抖动故障诊断

针对难以获取发动机怠速抖动的精确数学模型,文章提出一种基于RBF神经网络的模型逼近算法。该算法利用RBF神经网络良好的模型逼近能力,对造成发动机怠速抖动的几种典型故障原因进行了诊断。实验结果表明该算法具有良好的逼近效率和诊断效果。     

An application of the CUSUM algorithm to freeway incident detection based on two contiguous detectors

The CUSUM (cumulative sum of log‐likelihood ratio) algorithm is a detection algorithm that shows potential for the improvement of incident detection algorithms because it is designed to minimize the mean detect delay for a given false alarm constraint and it can also detect changes with different patterns. In this study, the CUSUM algorithm was applied to freeway incident detection by integrating traffic measurements from two contiguous loop detectors and the non‐stationarity of traffic flows. The developed algorithm was tested based on incident data from the PATH program, with consideration given to the impact of different geometric conditions on algorithm performance. It was also compared with two existing algorithms, in order to address the influence of traffic patterns. The evaluation results show that the CUSUM incident detection algorithm can perform equally well in comparison with the selected algorithms.