挖掘机电子控制系统(Ⅰ)

简述小松、大宇等挖掘机电子控制系统、电子功率优化系统和工作模式控制系统,介绍自动怠速装置的原理及故障诊断,详细论述电子油门和发动机电子控制系统工作原理及故障诊断。     

意大利威尼斯集装箱深水港投资模式分析

全球经济回暖以及"一带一路"倡议给中资企业参与海外港口投资提供了良好契机,但海外港口投资也存在政治、经济、文化等多方面的风险。针对目前中资企业海外港口投资中存在的问题,系统分析中资企业海外港口投资模式及其优劣和适用情况,并结合国外主要港口管理模式,以意大利威尼斯集装箱深水港投资实践为典型案例,提出海外港口投资策略。     

大连新建地铁对公交出行选择的影响

为了分析城市新建地铁项目对居民公共交通出行的影响，改善公交服务水平，提高公共交 通的分担率，针对大连市新建地铁线路展开研究。以大连市地铁1 号线沿线站点作为研究区域， 采用SP （Stated Preference） 调查方法，收集了300 名地铁沿线居民对常规公交以及新建地铁两种 出行方式的选择数据。通过建立二项Logit 模型，分析出行成本、换乘时间等选择方案特性变 量，出行特性变量以及出行者特性变量对于居民出行方式选择行为的影响，并计算弹性值及模型 精度。结果表明，通过调整出行成本及换乘时间可有效提高地铁分担率。由此提出相关政策建 议：对于出行成本，可从出行者年龄及出行次数两方面制定不同的优惠政策；对于换乘时间，可 从提高可达性、完善购票系统以及调整发班频率三方面进行改善。     

Experimental evaluation of Heavy Duty Vehicle speed patterns in urban and port areas and estimation of their fuel consumption and exhaust emissions

Exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) in urban and port areas were evaluated through a dedicated investigation. The HDV fleet composition and traffic driving from highways to the maritime port of Genoa and crossing the city were analysed. Typical urban trips linking highway exits to port gates and HDV mission profiles within the port area were defined. A validation was performed through on-board instrumentation to record HDV instantaneous speeds in urban and port zones. A statistical procedure enabled the building-up of representative speed patterns. High contrasts and specific driving conditions were observed in the port area. Representative speed profiles were then used to simulate fuel consumption and emissions for HDVs, using the Passenger car and Heavy duty Emission Model (PHEM). Complementary estimations were derived from Copert and HBEFA methodologies, allowing the comparison of different calculation approaches and scales. Finally, PHEM was implemented to assess the performances of EGR or SCR systems for NO_X reduction in urban driving and at very low speeds.The method and results of the investigation are presented. Fuel consumption and pollutant emission estimation through different methodologies are discussed, as well as the necessity of characterizing very local driving conditions for appropriate assessment.     

机器人生产线在船舶智能制造中的应用研究

智能制造是“中国制造2025”的主攻方向。本文先浅谈了智能船厂，并结合国内首个智能船厂试点对智能船厂的初级发展建设等进行初步探索，主要对船舶智能制造机器人生产线应用进行梳理分析，如工艺流程及布置、生产模式改进、提质增效和人员减配等。     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

Factors influencing bike share membership: An analysis of Melbourne and Brisbane

The number of bike share programs has increased rapidly in recent years and there are currently over 700 programs in operation globally. Australia’s two bike share programs have been in operation since 2010 and have significantly lower usage rates compared to Europe, North America and China. This study sets out to understand and quantify the factors influencing bike share membership in Australia’s two bike share programs located in Melbourne and Brisbane. An online survey was administered to members of both programs as well as a group with no known association with bike share. A logistic regression model revealed several significant predictors of membership including reactions to mandatory helmet legislation, riding activity over the previous month, and the degree to which convenience motivated private bike riding. In addition, respondents aged 18–34 and having docking station within 250 m of their workplace were found to be statistically significant predictors of bike share membership. Finally, those with relatively high incomes increased the odds of membership. These results provide insight as to the relative influence of various factors impacting on bike share membership in Australia. The findings may assist bike share operators to maximize membership potential and help achieve the primary goal of bike share – to increase the sustainability of the transport system.     

Autonomous cars: The tension between occupant experience and intersection capacity

Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks.In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation.On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda.This paper concludes with a brief discussion of research needs to advance this line of inquiry.     

Flying with climate liability? Economic valuation of voluntary carbon offsets using forced choices

This study aims to examine how key aspects of voluntary climate action influence economic values of aviation carbon offsets using an Australian case study, where voluntary carbon offset programs for the aviation sector were active under a carbon tax between July 01, 2012 and July 17, 2014. An online survey was administered during the period using choice experiments. This rare and short-lived Australian experience is useful to gain insights into how individuals respond to the new public policy in terms of the perceived economic value of voluntary offsets for air travel. According to the estimation results, supporters of the mandatory tax policy held a welfare value of voluntary carbon offsets for their domestic flights that is three times larger than non-supporters (i.e., $AU27.83 vs. $AU9.40). It is $AU12.27 on average per ton of carbon offsets per person for domestic flights and $AU0.92 for international long-haul flights. The findings endorse that individuals seem to attach personal responsibility for carbon emissions (i.e. climate liability or carbon conscience) to frequent domestic flights, but not so much to intercontinental flights. Furthermore, reported flight frequencies by respondents did not place any significant impact on economic values of voluntary carbon offsets in both domestic and international frameworks. A coupled approach between forced choices and certainty responses was adapted, where no-choice options were retrieved, potentially improving choice experiments. Results suggest that airlines should consider simplifying their carbon offset programs to fixed levels (e.g. £3, £10, and £20 as in the case of British Airways), regardless of geographical boundaries, while governments should promote both mandatory and voluntary climate measures in tandem.