科技创新助力资源节约型环境友好型港口发展 访上海国际港务(集团)股份有限公司副总裁包起帆

<正>在今日之中国,国民经济快速增长与资源瓶颈矛盾日益突出;建设资源节约型、环境友好型社会已经成为国家重要发展战略之一。因此,交通运输部明确提出"加快建设创新型交通行业,走资源节约型、环境友好型交通行业发展之路";而建设节能降耗型的港口是交通行业走"两型"发展道路的重要工作之一。上海国际港务(集团)股份有限公司持续开展节能创新工作、降低运营成本,不但体现了行业的发展方向,更体现了交通行业企业的社会责任,树立了上海国际航运中心的良好形象。我们通过对上海国际港务(集团)股份有限公司副总裁包起帆先生的采访,把上海国际港务(集团)股份有限公司的经验介绍给大家。     

江西高速公路行业文化品牌建设探讨

江西省高速集团作为国有大型企业,要实施文化大品牌战略,在经营管理中注入文化"基因",打造具有江西省高速公路行业特色的文化品牌。阐述了江西省高速集团概况,分析了公路文化品牌的内涵和本质特征,并探讨了加强公路文化品牌建设的重要性和必要性,对加强江西省高速集团文化品牌建设的措施进行了较为深入的研究,具有一定的参考价值。     

不忘初心 砥砺前行——广西路建工程集团有限公司

正广西路建工程集团有限公司(简称"广西路建集团")是广西新发展交通集团有限公司的直属企业。广西路建集团始创于1959年的广西公路管理局筑路机械队,历经"广西筑路机械大队""广西路桥机械施工处""广西远航路桥""广西路桥建设"等时期,于2014年10月升级更名为广西路建工程集团有限公司。几代广西路建人经过近60年的努力,构建形成了路桥施工业务、房地产及土地开发、钢结构工程、     

薛志刚：构建天地一体的人民邮政服务

正秉承"人民邮政为人民"的宗旨,中国邮政作为唯一承担国家普遍服务的国有企业,长期以来为广大人民群众提供着高效优质服务。依托自有运力及能力建设,辅以社会力量参与其中,中国邮政遵循着科技引领和科技赋能的发展思路,围绕收寄、分拣、运输、投递的全环节生产链条为社会和大众提供服务。在中国邮政集团有限公司运营管理部总经理薛志刚看来,所谓"路空协同",核心应体现在"协同"二字,这个"协同"既包含运行的路、空的协同,也包含内部的系统协同,比如在收寄、分拣、运输、投递等环节上的协同。     

建设高品质高速公路 贯彻落实“交通强国”战略——广西交通投资集团匠心打造品质工程

正党的十九大提出"交通强国"战略,广西"县县通高速"攻坚战进入关键时期。广西交通投资集团有限公司(以下简称广西交投集团)作为广西交通建设"主力军",成立10年来承担了广西近70%的高速公路建设任务,先后建成、续建、筹建高速公路项目38个,总里程约3696公里。广西交投集团按照交通运输部品质工程示范创建部署以及自治区交通运输厅品质工程公关行动有关要求,注重规模、速度、质量、效益的均衡统一,推     

汽车燃油消耗统计考核

文章介绍了苏州汽车客运集团有限公司加强节能管理工作的网络建设、汽车燃油消耗定额确定、油料消耗统计方法的具体做法、相关的管理措施和成效,并提出了"十一五"期间节能工作的几点思考。     

践行“三个维度”新理念 开启“百亿强企”新征程——广西路建工程集团有限公司

正党的十九大立足新时代新征程,作出了"建设交通强国"的重大决策部署,这是全体交通人为之奋斗的新使命。作为传统交通建设的继承者和现代交通建设的开拓者,广西路建工程集团有限公司认真贯彻落实新发展理念,积极应对交通发展新形势,紧紧围绕"再造一个新发展"战略目标,坚持"转作风、强基础、促发展"工作主线,2017年市场开拓成绩显著,     

实干担当 砥砺奋进 奋力开启新时代企业发展新征程——广西路桥工程集团有限公司

正2019年是"十三五"战略实施关键的一年,也是广西路桥工程集团有限公司发展浓墨重彩的一年。在北投集团的正确领导和大力支持下,公司坚持稳中求进的总基调,坚持谦虚务实和艰苦奋斗的工作作风,持续推进"品质路桥"建设,坚持强品质、稳增长、挖潜力、控风险的总体思路,以信息化和标准化为手段,创新管理,克难攻坚、真抓实干,企业高质量发展平稳推进,较好地实现了全年既定工作目标,亮眼的成绩单再次刷新纪录。     

技术创造优势 信息推动发展——广西路桥工程集团有限公司技术与信息分公司

正广西路桥工程集团有限公司技术与信息分公司成立于2018年4月,作为路桥集团旗下将技术研发、信息建设有效整合的新兴分支,秉持"以技术创造优势,以信息推动发展"的理念,塑造好"品质路桥"的公众形象,致力于成为国内领先的科技研发和信息化平台。公司前身为路桥集团技术中心,后与集团公司信息部联合升格为分公司。公司本部现设有科技研发部、信息化中心、试验检测中心、工程事业部、综合管理部、财务部等部门,     

汪劭祎:高品质生态公路的践行者

正汪劭祎,男,40岁,中共党员,研究生学历,教授级高级工程师,注册一级建造师,现任中国公路工程咨询集团有限公司(以下简称中咨集团)建设事业部副总经理、海南琼乐高速(琼中至五指山段)代建指挥部指挥长。长期工作于公路勘察设计及工程项目管理一线,曾担任勘察设计项目负责人、"投资+EPC"项目合约部负责人、总工程师、代建项目指挥长等岗位职务。荣获中国公路学会科学技术奖一等奖、中国建筑业协会项目管理成果奖一等奖、中咨集团"十大杰出青年"、中国海员建设工会重点工程建设劳动竞赛先进个人、海南省五一劳动奖章等奖项。     

<Emphasis Type="Italic">Not</Emphasis> driving alone? American commuting in the twenty-first century

This paper investigates recent commuting trends by American workers. Unlike most studies of commuting that rely on data from the American Community Survey this study utilizes the American Time Use Survey to detail the complex commuting patterns of modern-day workers. Changes in the price of gasoline in recent years suggest that the incidence of “driving alone” should be on the decline. Indeed, results show that the sensitivity of modal commuting with respect to changes in gasoline prices appears to be relatively large. We estimate the gasoline-price elasticity of driving alone to be 0.057 and the gasoline-price elasticity of carpooling to be 0.502. Additional factors also affect commuting, including socio-economic characteristics and social desires. However, it is changes in gasoline prices that appear to account for nearly all of the recent variation in the mode chosen for commuting.     

汽油机国五与国六法规对比研究

随着汽车保有量的不断增加和排放法规的日益严格,排放法规也在不断更新,我国机动车排放标准主要参考欧盟体系,已历经五个阶段,实施期间机动车单车排放量大幅度下降,但也暴露出一些不足有待修订,2015年5月20日"国六标准编制工作组"成立,由上汽、东风、北汽、一汽牵头组织国六的标准研究制定工作,就在2016年12月23日国家正式发布了轻型汽车污染物排放限值及测量方法 (中国第六阶段)GB18352.6-2016。     

Short‐term prediction of traffic parameters—performance comparison of a data‐driven and less‐data‐required approaches

The travel decisions made by road users are more affected by the traffic conditions when they travel than the current conditions. Thus, accurate prediction of traffic parameters for giving reliable information about the future state of traffic conditions is very important. Mainly, this is an essential component of many advanced traveller information systems coming under the intelligent transportation systems umbrella. In India, the automated traffic data collection is in the beginning stage, with many of the cities still struggling with database generation and processing, and hence, a less‐data‐demanding approach will be attractive for such applications, if it is not going to reduce the prediction accuracy to a great extent. The present study explores this area and tries to answer this question using automated data collected from field. A data‐driven technique, namely, artificial neural networks (ANN), which is shown to be a good tool for prediction problems, is taken as an example for data‐driven approach. Grey model, GM(1,1), which is also reported as a good prediction tool, is selected as the less‐data‐demanding approach. Volume, classified volume, average speed and classified speed at a particular location were selected for the prediction. The results showed comparable performance by both the methods. However, ANN required around seven times data compared with GM for comparable performance. Thus, considering the comparatively lesser input requirement of GM, it can be considered over ANN in situations where the historic database is limited. Copyright © 2016 John Wiley & Sons, Ltd.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost

Developing demand responsive transit systems are important with regard to meeting the travel needs for elderly people. Although Dial‐a‐ride Problems (DARP) have been discussed for several decades, most researchers have worked to develop algorithms with low computational cost under the minimal total travel costs, and fewer studies have considered how changes in travel time might affect the vehicle routes and service sequences. Ignoring such variations in travel time when design vehicle routes and schedules might lead to the production of inefficient vehicle routes, as well as incorrect actual vehicle arrival times at the related nodes. The purpose of this paper is to construct a DARP formulation with consideration of time‐dependent travel times and utilizes the traffic simulation software, DynaTAIWAN, to simulate the real traffic conditions in order to obtain the time‐dependent travel time matrices. The branch‐and‐price approach is introduced for the time‐dependent DARP and tested by examining the sub‐network of Kaohsiung City, Taiwan. The numerical results reveal that the length of the time window can significantly affect the vehicle routes and quantitative measurements. As the length of the time window increases, the objective value and the number of vehicles will reduce significantly. However, the CPU time, the average pickup delay time, the average delivery delay time and the average actual ride time (ART)/direct ride time (DRT) will increase significantly as the length of the time window increases. Designing the vehicle routes to reduce operating costs and satisfy the requirements of customers is a difficult task, and a trade‐off must be made between these goals. Copyright © 2014 John Wiley & Sons, Ltd.     

Variation of households<Emphasis Type="Bold">’</Emphasis> car ownership across time: application of a panel data model

For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important to study the changing characteristics of car ownership in a household through time as well as factors responsible of these variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated the socio-economic background of the decision maker, the built environment and the perception associated with owning a car as determinant factors of car ownership and use. In most cases, these analyses have been carried out using cross-sectional data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996–2006) is used to examine variation of car ownership through time and across households. The panel data modeling results showed that there are variations of car ownership between households whereas changes in car ownership of a given household over time (within household variations) are insignificant. The influence of other factors such as the households’ socio-economic background, the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction with existing public transportation services on the car owning characteristics of households is also presented and discussed in this paper.

Improved waveform‐feature‐based vehicle classification using a single‐point magnetic sensor

Vehicle classification systems have important roles in applications related to real‐time traffic management. They also provide essential data and necessary information for traffic planning, pavement design, and maintenance. Among various classification techniques, the length‐based classification technique is widely used at present. However, the undesirable speed estimates provided by conventional data aggregation make it impossible to collect reliable length data from a single‐point sensor during real‐time operations. In this paper, an innovative approach of vehicle classification will be proposed, which achieved very satisfactory results on a single‐point sensor. This method has two essential parts. The first concerns with the procedure of smart feature extraction and selection according to the proposed filter–filter–wrapper model. The model of filter–filter–wrapper is adopted to make an evaluation on the extracted feature subsets. Meanwhile, the model will determine a nonredundant feature subset, which can make a complete reflection on the differences of various types of vehicles. In the second part, an algorithm for vehicle classification according to the theoretical basis of clustering support vector machines (C‐SVMs) was established with the selected optimal feature subset. The paper also uses particle swarm optimization (PSO), with the purpose of searching for an optimal kernel parameter and the slack penalty parameter in C‐SVMs. A total of 460 samples were tested through cross validation, and the result turned out that the classification accuracy was over 99%. In summary, the test results demonstrated that our vehicle classification method could enhance the efficiency of machine‐learning‐based data mining and the accuracy of vehicle classification. Copyright © 2014 John Wiley & Sons, Ltd.     

Modeling the evolutions of day‐to‐day route choice and year‐to‐year ATIS adoption with stochastic user equilibrium

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.