不同整体式转向梯形机构分析方法的对比研究

介绍了一种整体式转向梯形机构的空间运动学分析方法，并利用该方法计算了某轻型货车的前轴内、外轮转角关系，计算结果与实测的该车前轴内、外轮转角关系曲线吻合较好。应用不同的整体式转向梯形机构的平面分析方法对同一辆货车进行了分析，对所得分析结果与试验结果进行比较，结果表明我国目前采用较多的汽车设计教材中介绍的转向梯形分析方法误差较大。     

Estimating Missing Traffic Volume Using Low Multilinear Rank Tensor Completion

Traffic volume data have been collected and used for various purposes in some aspects of intelligent transportation systems (ITS) applications. However, the unavoidable detector malfunction can cause data to be missing. It is often necessary to develop an effective approach to recover the missing data. In most previous methods, temporal correlation is explored to reconstruct missing traffic volume. In this article, a new missing traffic volume estimation approach based on tensor completion is proposed by exploring traffic spatial–temporal information. The tensor model is utilized to represent traffic volume, which allows for exploring the multicorrelation of traffic volume in spatial and temporal information simultaneously. In order to estimate the missing traffic volume represented by the tensor model, a novel tensor completion algorithm, called low multilinear rank tensor completion, is proposed to reconstruct the missing entries. The proposed approach is evaluated on the PeMS database. Experimental results demonstrate that the proposed method is more effective than the state-of-art methods, especially when the ratio of missing data is high.     

空间数据挖掘技术

随着数据挖掘技术的不断发展与成熟,空间数据挖掘已成为人们研究的热点之一。虽然现在还没有一个空间数据挖掘的实用系统,但展望前景空间数据挖掘可广泛用于遥感图象处理、地理信息系统、计算机地图制作等领域。 本文基于知识种类的划分,展现了一些具有代表性的新的空间数据挖掘技术。     

A three-stage computational approach to network matching

Network matching is frequently needed for integrating data that come from different sources. Traditional ways of finding correspondences between networks are time-consuming and require considerable manual manipulation. This paper describes a three-stage matching algorithm (node matching, segment matching, and edge matching) that combines bottom-up and top-down procedures to carry out the matching computation. As it uses sensitive matching measures, the proposed algorithm promises good improvement to existing algorithms. An experiment of matching two waterway networks is reported in the paper. The results of this experiment demonstrate that a reasonable matching rate and good computational efficiency can be achieved with this algorithm. The paper also briefly discusses necessary improvements in areas of linear alignment, aspatial matching and higher-level matching.     

Telecommuting and urban sprawl

This study examines what happens to city size when telecommuting occurs. It assumes that more telecommuting occurs when telecommuters’ labor cost share increases and/or workers adopt a more favorable attitude toward working from home. The study shows that telecommuting produces opposing forces that regulate the city size, one centralizing and the other decentralizing urban activities. These forces are examined in a city where workers and firms are given the option to freely mix working at the office and at home, and the city’s land use is endogenously determined. A rise in the productivity of an economy due to telecommunications technology could work to centralize urban activities, while urban contraction can occur with a fixed city population.     

北京就业与交通时空变动及计量关系研究

文章结合北京就业的时空变动特征以及对道路交通需求的变化特征,从区域要素角度考察城市交通和就业的关系。通过构建就业交通需求与交通供给量之间的计量关系模型,进行时间序列关系研究和横截面关系研究,分析得到北京市就业与交通道路建设之间的关系。     

A spatial Difference-in-Differences estimator to evaluate the effect of change in public mass transit systems on house prices

Evaluating the impact of public mass transit systems on real-estate values is an important application of the hedonic price model (HPM). Recently, a mathematical transformation of this approach has been proposed to account for the potential omission of latent spatial variables that may overestimate the impact of accessibility to mass transit systems on values. The development of a Difference-in-Differences (DID) estimator, based on the repeat-sales approach, is a move in the right direction. However, such an estimator neglects the possibility that specification of the price equation may follow a spatial autoregressive process with respect to the dependent variable. The objective of this paper is to propose a spatial Difference-in-Differences (SDID) estimator accounting for possible spatial spillover effects. Particular emphasis is placed on the development of a suitable weights matrix accounting for spatial links between observations. Finally, an empirical application of the SDID estimator based on the development of a new commuter rail transit system for the suburban agglomeration of Montréal (Canada) is presented and compared to the usual DID estimator.     

A hierarchical rule-based land use extraction system using geographic and remotely sensed data: A case study for residential uses

Lack of detailed land use (LU) information and of efficient data gathering methods have made modeling of urban systems difficult. This study aims to develop a hierarchical rule-based LU extraction system using very high resolution (VHR) remotely sensed imagery and geographic vector data. Land cover information extracted from remote sensing and several types of geographic data from the study area, City of Fredericton, Canada, are fused into a comprehensive database, in order to develop a sophisticated LU Extraction Expert System (LUEES). This paper illustrates how the proposed LUEES though a case study for residential uses in the study area. Morphological (individual-based) analysis at the building-level is carried out through a step-wise binary logistic regression model, which differentiates residential and non-residential buildings and results in an overall accuracy of 93.1%. The results derived from morphological analysis are then subject to a post-correction process using a spatial arrangement analysis, in order to further mitigate the misclassification issues arising from the morphological analysis. In this regard, Gabriel Graph connectivity examines the spatial structure and arrangements of urban features concerning different LU types. It is found that the spatial arrangement analysis further enhances the residential LU classification accuracy, which gives rise to an overall accuracy of 97.4%. It is believed that, equipped with such a powerful LU data collection tool and resulting detailed/accurate LU data, urban planners/modelers should be able to more reliably and precisely represent/predict economic interactions, activity locations, space and housing developments, business expansion, and trip patterns.     

Economic analyses of sea-level rise adaptation strategies in transportation considering spatial autocorrelation

This paper reports the impacts of economic analysis results on sea-level rise adaptation decision making with different economic analysis methods. The methodology was applied to Hillsborough County, Florida. A general conclusion is that partial shoreline protection should be implemented to reduce the potential impacts of sea-level rise on important land use, then transportation infrastructure is preferred to be protected or accommodated, and finally managed relocation should be adopted. More specifically, the results show that the best adaptation strategy is shoreline protection plus transportation infrastructure accommodation; the length of shoreline protection plays an important role in the economic analysis results, and shoreline protection and accommodation adaptation strategies for all areas are not recommended because of either high costs or low benefits; the value of travel time saving and spatial autocorrelation play important roles in the economic analysis results of accommodation strategy, which highlights the importance of including indirect economic factors and spatial autocorrelation impacts when making sea-level rise adaptation decisions.     

Optimal biofuel supply chain design under consumption mandates with renewable identification numbers

The Renewable Identification Number (RIN) system is a tracking mechanism that enforces the U.S. Renewable Fuel Standard by monitoring obligated parties’ compliance with the biofuel consumption mandates. This paper incorporates the RIN system into the design of a biofuel supply chain that addresses independent decisions of non-cooperative farmers, biofuel manufacturers, and blenders. Game-theoretic models are developed to examine the impacts of the RIN system on individual stakeholders’ decisions (e.g., on farmland use, bio-refinery investment, biofuel production) and the competition between food and biofuel industries, in both a perfectly competitive scenario and a monopoly scenario. For the perfectly competitive scenario, Nash equilibrium can be obtained by solving a convex optimization problem. For the monopoly scenario, a bi-level Stackelberg leader–follower model is developed, from which we found that a rigid mandate on blenders may suppress the total biofuel production. To avoid such unintended consequences, a relaxed unit-RIN based penalty scheme is proposed and shown to improve the overall biofuel supply chain performance. Managerial insights are drawn from a numerical case study for the state of Illinois.