How the environmental impact affects the design of logistics networks based on cost minimization

The degree of centralization of the logistics network is one of the important strategic decisions to take. This issue has often been studied but mainly from a cost minimization focus. This research studies the influence of incorporating the environmental impact in logistics network design models, comparing the results with those obtained considering cost minimization only. A fuzzy biobjective optimization model is used to carry out a number of experiments. By weighting the relative importance of the two objectives, the differences with respect to the base cost minimization solution can be ascertained. Our results show that in general more material is moved through warehouses when the environmental impact is considered and more decentralized facilities are opened.     

Generating lane-based intersection maps from crowdsourcing big trace data

Lane-based road information plays a critical role in transportation systems, a lane-based intersection map is the most important component in a detailed road map of the transportation infrastructure. Researchers have developed various algorithms to detect the spatial layout of intersections based on sensor data such as high-definition images/videos, laser point cloud data, and GPS traces, which can recognize intersections and road segments; however, most approaches do not automatically generate Lane-based Intersection Maps (LIMs). The objective of our study is to generate LIMs automatically from crowdsourced big trace data using a multi-hierarchy feature extraction strategy. The LIM automatic generation method proposed in this paper consists of the initial recognition of road intersections, intersection layout detection, and lane-based intersection map-generation. The initial recognition process identifies intersection and non-intersection areas using spatial clustering algorithms based on the similarity of angle and distance. The intersection layout is composed of exit and entry points, obtained by combining trajectory integration algorithms and turn rules at road intersections. The LIM generation step is finally derived from the intersection layout detection results and lane-based road information, based on geometric matching algorithms. The effectiveness of our proposed LIM generation method is demonstrated using crowdsourced vehicle traces. Additional comparisons and analysis are also conducted to confirm recognition results. Experiments show that the proposed method saves time and facilitates LIM refinement from crowdsourced traces more efficiently than methods based on other types of sensor data.     

基于传播模型的非机动车违规过街行为研究

为研究信号交叉口非机动车违规过街行为，选取西安市的7个信号交叉口，通过视频拍摄获取资料，应用复杂网络来分析非机动车网络的结构特征和演化规律.建立了交叉口非机动车网络，基于SI模型的基本思想，提出了非机动车违规过街行为的传播模型.并通过python程序进行模拟分析，在不同的网络结构和不同的传播率下，获取了非机动车违规过街的行为趋势.结果表明：随着等待时间的增加，一旦有骑行者闯红灯，更多的骑行者将加入到违规过街的行列；在内向度和外向度方面，电动自行车均高于普通自行车；非机动车违规行为随着传播率及非机动车流量的增加而增加.     

A traffic-condition-based route guidance strategy for a single destination road network

Most of existing route guidance strategies achieves user optimal equilibrium by comparing travel time. Measuring travel time, however, might be uneasy on an urban road network. To contend with the issue, the paper mainly considers easily obtained inflow and outflow of a link and road capacity as input, and proposes a route guidance strategy for a single destination road network based on the determination of free-flow or congested conditions on alternative routes. An extended strategy for a complex network and a feedback approximation for avoiding forecast are further explored. Weaknesses of the strategy are also explicitly analyzed. To test the strategy, simulation investigations are conducted on two networks with multiple parallel routes. The results indicate that the strategy is able to provide stable splitting rates and to approximate user optimal equilibrium in different conditions, in particular when traffic demand is high. This strategy has potential to be applied in an urban road network due to its simplicity and easily obtained input data. The strategy is also applicable for single destination if some alternatives and similar routes are available.     

Obsolete Maps and Coastal Management: Case Studies from Northwest Ireland

On dynamic coastal sites, subject to rapid and sometimes unpredictable shoreline changes, management problems can be aggravated if legally authoritative maps are obsolete. These difficulties are illustrated by two case studies from County Donegal in northwest Ireland. The first case study outlines the problems that arise where statutory functional area boundaries are based on a near century-old map. The second case study deals with the problems of planning development on a site where a customized map only a few years old has been rendered obsolete by rapid coastal erosion. Other problems are caused by the inappropriate use of maps. Suggestions are made to mitigate the effects of outdated maps.     

基于GOOSE机制的城市轨道交通中压环网继电保护方案优化

针对目前城市轨道交通中压环网继电保护存在的问题,提出了基于GOOSE(面向通用对象的变电站事件)机制的中压环网的继电保护优化方案,有效地解决了传统过流保护级差配合困难的问题.该方案是以GOOSE光纤以太网为基础,以闭锁逻辑为核心的数字通信电流保护方案.将GOOSE信号进行分类,并对中压供电环网系统各种可能出现的故障进行动作行为分析.最后,通过RTDS(动态数字仿真系统)仿真试验,证明该方案在各种故障情况下,都能保证继电保护的选择性、速动性、灵敏性和可靠性.     

Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.     

多元评价体系组合模型在铁路隧道变形预测中的应用

为克服传统预测模型结构单一、预测精度及稳定性不足等缺陷,提出多元体系组合预测模型的建模思路。首先,基于支持向量机、BP神经网络及ARMA模型3种单一预测模型,构建铁路隧道变形预测体系;再以均方根误差、误差平方和及平均绝对误差等为评价准则或指标,构建各预测结果的误差评价体系,求解各单项预测模型的权值贡献指数,得到最优组合权值;然后利用后验差检验、残差检验和关联度检验构建预测精度校验体系,对组合预测结果进行检验,评价预测模型的有效性;最后,结合工程实例,对多元体系组合预测模型在特大断面隧道中的变形预测效果进行检验。结果表明:多元评价体系组合模型预测相对误差值均小于2%,具有较高的预测精度,且较单一预测模型具有更高的预测精度,也一致通过相关检验,验证了多元体系组合预测模型的有效性。     

基于 EM D桘BPN 方法的高速铁路短期客流预测

高速铁路短期客流预测是铁路运输系统的重要组成部分。无论是对列车开行方案的制定,还是对如何采取正确的营销策略,都具有重大的现实意义。通过混合经验模态分解方法和神经网络方法相结合的EMD-BPN方法来预测高速铁路短期客流量。组合方法主要分为三步：首先,使用经验模态分解方法将客流时间序列分解;其次,将IM Fs作为BP神经网络的输入;最后,应用神经网络对客流量做出预测。数值实例表明,该方法对于高速铁路短期客流预测在精度和稳定性上都有良好的表现。