中国智能运输系统(ITS)的发展

论文概括论述了国内外智能文通系统工程的发展,特别是我国当前交通运输系统深化 的问题,论述了我国“十五”智能交通发展的指导方针政策以及开发的重点,论文对我国的发展智能交通的系统的重点问题都进行阐述.     

TGF-β1对成人骨髓CD105~+间充质干细胞增殖与分化的影响

目的分离并鉴定成人骨髓间充质干细胞(mesenchymalstemcells,MSCs),研究TGFβ1对骨髓MSCs增殖与分化的影响。方法分离成人骨髓单个核细胞;MACS磁珠分选CD105+细胞;FACS检测其免疫表型;诱导分选的CD105+细胞向脂肪及成骨细胞分化,油红O染色、VonKossa染色及RTPCR检测脂肪细胞及成骨细胞;观察TGFβ1对分选出的CD105+细胞分化与增殖的影响;免疫荧光染色检测诱导后的脂肪细胞CD105的表达情况;MTT法检测TGFβ1对CD105+细胞增殖的影响。结果成人骨髓来源的CD105+细胞体外可向脂肪及成骨细胞分化;在向脂肪细胞分化过程中,加入1～50ng/mLTGFβ1后,成脂诱导体系中无脂肪细胞出现;在向成骨诱导过程中,加入20ng/mLTGFβ1后,钙化基质沉淀明显降低;在脂肪诱导体系中,MTT染色检测显示TGFβ1对CD105+细胞的增殖有明显促进作用(P<0.05)。结论TGFβ1抑制成人骨髓源CD105+MSCs向脂肪及成骨细胞分化,在向脂肪诱导过程中,TGFβ1促进MSCs的增殖。     

Minimum acceptable time for turning off idling engines: Evidence from Taiwan

This paper examines the influence of different factors on motorist willingness to comply with idling stop regulations, as determined using stated preference analysis. Motorists were surveyed at urban roadsides in Taiwan, and the results obtained were analyzed using a partially adaptive model. The analysis showed that the standing time and turnoff idling engine while parking are both significant variables, and arise from risk aversion behavior. Environmental perceptions and convenience of use are the most influential factors, according to elasticity analysis. The study also verifies that a partially adaptive model is an appropriate model to consider censored data in a Triple-Bounded Dichotomous Choice analysis. These results will be useful as a reference for improving implementation of idling reduction regulations.     

BL 3-5和CAP 437中船舶直升机甲板设计的差异分析

为探讨丹麦民航局BL 3-5和英国民航局CAP 437对船舶直升机甲板设计部分要求的差异，以公司建造的GM-J180A自升式平台为依托，对这两部标准进行差异化分析，总结船舶直升机甲板设计和设施配备的要求和要点并提供相应的解决方案。     

考虑用户偏好的共享汽车混合运营模式优化

针对共享汽车运营商的油车和电车混合车队调度问题，本文将自由流动式和站点借还式两种运营模式相结合，提出考虑用户用车类型偏好的共享汽车系统优化模型。模型为油车和电车车队分别设置了自由流动式和站点借还式的运营模式，并进行运营范围决策、站点选址和车辆调度优化；运营商优先满足用户的用车类型偏好选择，对无法满足偏好的用户进行补贴。根据优化模型基本特征，设计基于梯度的启发式求解方法，对大规模非线性混合整数规划模型进行求解；针对案例区域，比较有无补贴的混合车队模式和单一车队模式的优化结果。结果表明：相比无补贴模式，有补贴模式能够鼓励偏好燃油汽车的用户更多地使用电动汽车，需求满足率从73.4%提高到78.2%，运营商利润提高了46.4%；相比单一类型车队，混合车队能够吸引更多用户使用共享汽车，用户需求数提高了40.6%。     

The impact of automated transit,pedestrian, and bicycling facilities on urban travel patterns

This article reports on an integrated modeling exercise, conducted on behalf of the US Federal Highway Administration, on the potential for frequent automated transit shuttles (‘community transit’), in conjunction with improvements to the walking and cycling environment, to overcome the last-mile problem of regional rail transit and thereby divert travelers away from car use. A set of interlocking investigations was undertaken, including development of urban visualizations, distribution of a home-based survey supporting a stated-preference model of mode choice, development of an agent-based model, and alignment of the mode-choice and agent-based models. The investigations were designed to produce best-case estimates of the impact of community transit and ancillary improvements in reducing car use. The models in combination suggested significant potential to divert drivers, especially in areas that were relatively transit-poor to begin with.     

Determining the Monetary Value of Quality Attributes in Freight Transportation Using a Stated Preference Approach

It is commonly accepted that the modal choice of a shipper is influenced not only by the pure economic attributes of transportation – time and cost – but also by more qualitative factors. These quality attributes relate to frequency, reliability, flexibility, transport duration and risk of loss or damage; they are usually difficult to quantify in monetary terms. Different techniques exist that help to understand better how these different quality attributes of freight transportation influence modal choice. In this paper we apply a stated preference design. Using real business data, the aim is then to derive partial utility functions that allow us to calculate monetary values for these different quality attributes.     

Consumers’ willingness to pay for alternative fuel vehicles: A comparative discrete choice analysis between the US and Japan

This paper conducts a comparative discrete choice analysis to estimate consumers’ willingness to pay (WTP) for electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) on the basis of the same stated preference survey carried out in the US and Japan in 2012. We also carry out a comparative analysis across four US states. We find that on average US consumers are more sensitive to fuel cost reductions and alternative fuel station availability than are Japanese consumers. With regard to the comparative analysis across the four US states, consumers’ WTP for a fuel cost reduction in California is considerably greater than in the other three states. We use the estimates obtained in the discrete choice analysis to examine the EV/PHEV market shares under several scenarios. In a base case scenario with relatively realistic attribute levels, conventional gasoline vehicles still dominate both in the US and Japan. However, in an innovation scenario with a significant purchase price reduction, we observe a high penetration of alternative fuel vehicles both in the US and Japan. We illustrate the potential use of a discrete choice analysis for forward-looking policy analysis, with the future opportunity to compare its predictions against actual revealed choices. In this case, increased purchase price subsidies are likely to have a significant impact on the market shares of alternative fuel vehicles.     

A cluster analysis approach for differentiating transportation modes using Bluetooth sensor data

A variety of automatic data collection technologies have been used to gather road and highway system data. The majority of these automatic data collection technologies are designed to collect vehicle-based data and either do not have the capability to collect other travel mode data (e.g., bicycles and pedestrians), or may need to be deployed differently to support this capability.

One type of wireless-based data collection system that has been deployed recently is based on Bluetooth technology. A key feature of Bluetooth-based data collection systems that makes travel mode identification feasible is that the Bluetooth-enabled devices within vehicles are also present on bicyclists and pedestrians. This research explores the effectiveness of applying cluster analysis methods when processing data collected via Bluetooth technology from vehicles, bicyclists, and pedestrians to automatically identify the associated travel modes. The results of several experiments utilizing multiple Bluetooth-based data collection units arranged linearly and in relatively close proximity on a simulated intersection demonstrate the potential of cluster analysis to accurately differentiate transportation modes from the collected data.     

基于FPGA的模糊PID控制器设计

模糊PID(Proportion Integration Differentiation)作为一种先进的智能控制算法,在工业中的实际应用范围却远远落后于传统PID算法,其原因是智能控制算法的复杂性使得控制器实现困难、占用资源多、运行效率低。分析了利用FPGA(Field Programmable Gate Array)实现智能控制算法的优势,提出了利用查找表来实现模糊算法的新的实现方式,具有设计灵活、开发期短、可靠性高、运行高速等优点。