提升正立式结构摩托车前减震器装配一次合格率的探讨

减震器是摩托车中仅次于发动机的关键部件，其示功特性与前弹簧共同作用直接影响摩托车的减振效果和舒适性。受国内零部件加工尺寸离散率较大的影响，导致产品装配一次合格率仅为80％左右。通过采取一系列相应措施，并对供应商进行指导和提升，确保了配套件的产品质量，逐步修订了关键尺寸的公差范围，提高了减震器的一次装配合格率。     

如何提高路基分层压实系数一次验收合格率

通过包西铁路通道陕西段路基土方填筑施工过程的实践,分析总结影响路基分层压实系数一次验收合格率的多种因素,有针对性地制定相应工程措施,指导施工生产。     

上海地区细砂路基施工控制浅析

现行规范中没有明确细砂路基施工的质量控制与验收标准,从施工角度提出了填砂路基检测和施工过程控制要点,有关经验可供类似工程参考。     

Mobility, social exclusion and well-being: Exploring the links

Building on a growing research foundation, transport policy makers have begun to associate the ability to be mobile with having a role in the facilitation of social inclusion. However, the further connection to well-being is not as well understood. This paper explores the association between a person’s travel patterns, their risk of social exclusion and self-assessed well-being. Key influences on social exclusion are discussed, with trip making emerging as a significant influence. Trip making is not a significant direct influence on well-being but does exercise an indirect influence through the impact on risk of social exclusion. The modelling process enables a value for additional trips to be estimated, the value being about four times the values derived from conventional generated traffic approaches. Similar high values are found in separate metropolitan and regional case studies, confirming the significance of the results.     

美国社区学院全面服务社会的启示与借鉴——参加教育部“高职院校领导能力海外培训”感悟(一)

文章从服务理念、服务方式、服务内容、服务体系等方面分析了美国阿拉莫学院的办学特色,并在此基础上对我国的高职教育进行了反思,结合南通航院在国家骨干(示范)院校建设实践,从树立服务理念、深化招生制度改革、健全终身教育体制、推进校企合作等方面就如何借鉴美国社区学院服务社会的经验,提升我国高职院校社会服务能力提出了初步的想法。     

The social context of informal commuting: Slugs, strangers and structuration

Despite considerable interest in the role of social interactions and social context on transportation, there have been very few attempts to explore specific cases of social interaction influencing transportation systems. This paper explores the social practice of slugging, an informal system of carpooling in the Washington, DC area. Slugging emerged in response to the establishment of Virginia’s High Occupancy Vehicle (HOV) lanes in the early 1970s, as single drivers picked up riders alongside the road (slugs) in order to meet the requirements for driving in the less congested HOV lanes. Drawing on the work of sociologist Anthony Giddens, as well as the sociological insights of Georg Simmel and Stanley Milgram, we suggest that the practice of slugging highlights the processes of institutionalization and structuration. This paper details how the region’s mass transportation policies and urban culture have combined to result in an institutionalized practice with particular norms and logics of behavior. We conclude that looking at specific cases where social context has affected transportation, like slugging, could provide useful insights on the impact of social context on transportation policies and systems.     

高速公路左侧路肩设置必要性研究

尽管<公路工程技术标准>(JTG B01-2003)中规定八车道的高速公路应当设置2.5 m的左侧硬路肩,但国内几条刚刚改建完成的八车道高速公路中没有一条设置了左侧硬路肩,甚至没有宽于0.75 m的路缘带.研究运用可接受间隙理论计算了不同流量和车道数条件下车辆从最内侧车道穿插变道停驶到右侧路肩这一过程的概率和所需距离,并通过交通事故数据调研,分析了左侧路肩设置对提高交通安全的影响,从运行效率和交通安全两个方面定性和定量分析了左侧路肩设置的必要性.     

Social networks and joint/solo activity–travel behavior

The social dimension of activity–travel behavior has recently received much research attention. This paper aims to make a contribution to this growing literature by investigating individuals’ engagements in joint activities and activity companion choices. Using activity–travel diary data collected in Hong Kong in 2010, this study examines the impact of social network attributes on the decisions between solo and joint activities, and for joint activities, the choices of companions. Chi-square difference tests are used to assess the importance of social network variables in explaining joint activity behavior. We find that the inclusion of social network attributes significantly improves the goodness-of-fit of the model with only socioeconomic variables. Specifically, individuals receiving emotional support and social companionship from family members/relatives are found to more likely undertake joint activities with their family members/relatives; the size of personal social networks is found to be a significant determinant of companion choices for joint activities; and activity companions are found to be significant determinants of travel companions. The findings of this study improve the understanding about activity–travel, especially joint activity–travel decisions.     

A measurement to driving situation awareness in signalized intersections

Drivers get involved easily in Left-Turn Across Path with Opposite Direction Traffic (LTAP-OD) conflicts at signalized intersection with unprotected left-turn phasing. This study classified the left-turn drivers’ performance into four types: (1) the correct acceptance of safe lags/gaps, (2) the correct rejection of dangerous lags/gaps, (3) the false rejection of safe lags/gaps and (4) the false acceptance of dangerous lags/gaps. Based on the high mounted video camera data, the logistic regression model was used to obtain the critical gaps for estimating whether the lags/gaps were safe or not. The results show that the cognition behavior of the left-turn drivers should be improved while the gap/lag is drawn near the critical gap. Furthermore, the conservative drivers are more likely to reject the larger lags/gaps and yield the right-of-way to the opposing vehicles. Simultaneously the poor response execution may cause drivers to have difficulties during the turning performance when the lags/gaps are large enough. These results could be used as the basis for a discussion of the right time to support the drivers.     

From Twitter to detector: Real-time traffic incident detection using social media data

The effectiveness of traditional incident detection is often limited by sparse sensor coverage, and reporting incidents to emergency response systems is labor-intensive. We propose to mine tweet texts to extract incident information on both highways and arterials as an efficient and cost-effective alternative to existing data sources. This paper presents a methodology to crawl, process and filter tweets that are accessible by the public for free. Tweets are acquired from Twitter using the REST API in real time. The process of adaptive data acquisition establishes a dictionary of important keywords and their combinations that can imply traffic incidents (TI). A tweet is then mapped into a high dimensional binary vector in a feature space formed by the dictionary, and classified into either TI related or not. All the TI tweets are then geocoded to determine their locations, and further classified into one of the five incident categories.We apply the methodology in two regions, the Pittsburgh and Philadelphia Metropolitan Areas. Overall, mining tweets holds great potentials to complement existing traffic incident data in a very cheap way. A small sample of tweets acquired from the Twitter API cover most of the incidents reported in the existing data set, and additional incidents can be identified through analyzing tweets text. Twitter also provides ample additional information with a reasonable coverage on arterials. A tweet that is related to TI and geocodable accounts for approximately 5% of all the acquired tweets. Of those geocodable TI tweets, 60–70% are posted by influential users (IU), namely public Twitter accounts mostly owned by public agencies and media, while the rest is contributed by individual users. There is more incident information provided by Twitter on weekends than on weekdays. Within the same day, both individuals and IUs tend to report incidents more frequently during the day time than at night, especially during traffic peak hours. Individual tweets are more likely to report incidents near the center of a city, and the volume of information significantly decays outwards from the center.