开放式参数化零件模型直接驱动的数控加工系统

阐述了开放式参数化模型直接驱动的数控加工系统的原理、方法、应用、以及其应用前景.在对比了当前工业界仍在沿用的数控系统以及从20世纪80年代兴起的开放式数控系统的优缺点以后,提出了将数控加工系统与CAD/CAM系统无缝式连接的解决方案.克服了通过后处理器将零件加工的参数化几何信息转化成G＆M加工代码（ISO 6983）以供数控机床进行加工所带来的诸多缺点.     

Design of Continuous and Discrete LQI Control Systems with Stable Inner Loops

Design approaches were proposed for both continuous and discrete LQI (linear quadratic with integral) controllers, if exist, to stabilize the inner loops in addition to stabilizing the closed loops and minimizing the quadratic cost functionals. Derived from the algebraic Riccati equations involved in continuous and discrete LQI control, the design approaches were straightforward obtained by setting the quadratic cost functionals to decoupled forms with positive definite weighting matrices. Examples were provided to verify the effectiveness of the approaches.     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

Impact of vehicle usage on consumer choice of hybrid electric vehicles

We analyze the vehicle usage and consumer profile attributes extracted from both National Household Travel Survey and Vehicle Quality Survey data to understand the impact of vehicle usage upon consumers’ choices of hybrid electric vehicles in the US. In addition, the key characteristics of hybrid vehicle drivers are identified to determine the market segmentations of hybrid electric vehicles and the critical attributes to include in the choice model. After a compatibility test of two datasets, a pooled choice model combining both data sources illustrates the significant influences of vehicle usage upon consumers’ choices of hybrid electric vehicles. Even though the data-bases have in the past been used independently to study travel behavior and vehicle quality ratings, here we use them together.     

Network impacts of a road capacity reduction: Empirical analysis and model predictions

In spite of their widespread use in policy design and evaluation, relatively little evidence has been reported on how well traffic equilibrium models predict real network impacts. Here we present what we believe to be the first paper that together analyses the explicit impacts on observed route choice of an actual network intervention and compares this with the before-and-after predictions of a network equilibrium model. The analysis is based on the findings of an empirical study of the travel time and route choice impacts of a road capacity reduction. Time-stamped, partial licence plates were recorded across a series of locations, over a period of days both with and without the capacity reduction, and the data were ‘matched’ between locations using special-purpose statistical methods. Hypothesis tests were used to identify statistically significant changes in travel times and route choice, between the periods of days with and without the capacity reduction. A traffic network equilibrium model was then independently applied to the same scenarios, and its predictions compared with the empirical findings. From a comparison of route choice patterns, a particularly influential spatial effect was revealed of the parameter specifying the relative values of distance and travel time assumed in the generalised cost equations. When this parameter was ‘fitted’ to the data without the capacity reduction, the network model broadly predicted the route choice impacts of the capacity reduction, but with other values it was seen to perform poorly. The paper concludes by discussing the wider practical and research implications of the study’s findings.     

Investigating the effects of psychological factors on commuting mode choice behaviour

This paper utilizes socio-psychometric survey data to investigate the influence of attitudes, affective appraisal and habit formation on commuting mode choice. The data-set was collected in 2009–2010 in Edmonton, Alberta. In addition to conventional socio-economic, demographic and modal attributes, the survey gathered psychological information regarding habitual behaviour, affective appraisal and personal attitudes. Different psychometric tools were used to capture psychological factors affecting mode choice. Habitual behaviour was measured using Verplanken's response-frequency questionnaire. Affective appraisal was indirectly estimated using the Osgood's semantic differential. Five-point Likert scales were used to measure attitude. The structural equation modelling (SEM) approach was used to investigate the effects of psychological factors on mode choice behaviour. SEM captures the latent nature of psychological factors and uses path diagrams to identify the directionality as well as intensity of the relationships. The investigation reveals that passengers have positive emotions towards their chosen mode. Further, evidence of the superiority of the car as a travel alternative was established in terms of strong habit towards it, such that passengers would use the car for almost every single trip.     

基于大数据的交通规划技术创新应用实践——以深圳市为例

深圳市长期坚持数据和模型驱动的交通规划理念,经过20年的积累,建立了面向规划决策支持的综合交通大数据应用体系,在多元数据融合与大数据挖掘应用方面进行了探索。总结深圳市交通大数据平台包含的三类数据:偏静态的城市空间数据、传统调查数据、偏动态的交通多元数据,阐述大数据对交通规划技术创新的影响。基于大数据对交通模型和运行仿真的影响,深圳市积极推动交通规划技术创新,建立区域–宏观–中观–微观一体化的交通仿真模型体系、融合实时数据的交通运行和评价系统,也使得绿色交通优先等规划理念更易实施。最后,对车联网、智慧交叉口、交通主动控制、个性化信息交互等影响交通规划创新的技术进行展望。     

超限超载货物运输系统结构模型分析

对超限超载货物运输形成机理的研究是长效治理超限超载的基础工作。运用系统解释结构模型法（ISM法）,分析了超限超载货物运输影响因素间的层次作用关系．明确了各影响因素在超限超载货物运输形成过程中所发挥的不同作用．指出相关法制建设的滞后与交通规费收取模式的不合理是导致超限超载货物运输的根源．而市场经济利益驱动是其直接诱因．为长效治理超限超载货物运输提供了理论支持。     

港口对腹地城市经济增长的空间溢出效应研究

将港城关系研究视角拓展至空间维度,利用2003—2016年中国沿海港口数据和城市数据,采用空间面板模型实证检验港口对腹地城市经济增长的影响.结果表明:港口不仅产生地区内溢出,也产生空间溢出;不仅促进所在城市经济增长,对腹地城市经济增长也具有显著的空间溢出效应;2008年金融危机后,港口空间溢出效应的显著性大幅增强;分区域检验中,环渤海港口对所在城市经济增长有明显的促进作用,但港口对腹地城市的空间溢出效应有限.     

地铁民用通信设备管理维保模式探讨

分析我国地铁民用通信设备管理维保模式的现状和特点,将其划分为独立维保、联合维保和完全委外维保等.提出社会化、市场化的维保模式,即在现行的设备管理模式中引入市场机制,以社会化手段进行通信设备的维护、维修和保养工作,追求以最小的资源投入获得最佳的配置模式,实现民用通信经营效益的最大化.从多个角度,研究了该模式面临的风险,以及相应的规避和实时保障的措施.