海上勘察作业中安全生产规范化管理的探讨

勘察设计单位安全生产工作具有项目工种和设备种类多、作业环境复杂、人员轮换频繁等特点,实行安全生产的标准化管理具有重要意义.从海上勘察作业的条件和基本组织形式出发,分析海上勘察作业在安全生产方面存在的主要问题;根据影响安全生产的关键环节理论,提出安全生产规范化管理的系统性对策.     

Eliciting preferences for adoption of fully automated vehicles using best-worst analysis

Autonomous mobility is one of the rapidly evolving aspects of smart transportation which carries the potential of reshaping both demand and supply sides of transportation systems. While understanding public opinions about autonomous vehicles (AVs) is a compelling step towards their successful implementation, still little is known about to which extent people will embrace this new technology and how the vehicle features will affect their adoption decision. This study presents a new approach for modeling the adoption behavior of fully AVs using the profile-case best-worst scaling model. In this approach, an AV profile which is characterized in terms of the main vehicle attributes and their associated levels is presented to the decision maker and he/she is asked to select the most and the least attractive attributes. Further, a binary adoption question at the end of the choice task inquires if the respondent is willing to purchase the described AV. Utilizing this method, we can recognize the difference between the intrinsic impacts of the vehicle attributes and the impact of the attribute levels on the adoption decision. Results of the analysis indicate that people are much more sensitive to the purchase price and incentive policies such as taking liability away from the “driver” in case of accidents and provision of exclusive lanes for AVs compared to other factors such as fuel efficiency, safety, or environmental friendliness. Further, it is found that millennials with higher income, those who live in the downtown area, and the majority of people who have experienced an accident in the past have greater interests in adopting this technology.     

Flexing service schedules: Assessing the potential for demand-adaptive hybrid transit via a stated preference approach

This paper assesses the demand for a flexible, demand-adaptive transit service, using the Chicago region as an example. We designed and implemented a stated-preference survey in order to (1) identify potential users of flexible transit, and (2) inform the service design of the flexible transit mode. Multinomial logit, mixed-logit, and panel mixed-logit choice models were estimated using the data obtained from the survey. The survey instrument employed a d_p-efficient design and the Google Maps API to capture precise origins and destinations in order to create realistic choice scenarios. The stated-preference experiments offered respondents a choice between traditional transit, car, and a hypothetical flexible transit mode. Wait time, access time, travel time, service frequency, cost, and number of transfers varied across the choice scenarios. The choice model results indicate mode-specific values of in-vehicle travel time ranging between $16.3 per hour (car) and $21.1 per hour (flexible transit). The estimated value of walking time to transit is $25.9 per hour. The estimated value of waiting time at one’s point of origin for a flexible transit vehicle is $11.3 per hour; this value is significantly lower than the disutility typically associated with waiting at a transit stop/station indicating that the ‘at-home’ pick-up option of flexible transit is a highly desirable feature. The choice model results also indicate that respondents who use active-transport modes or public transit for their current commute trip, or are bikeshare members, were significantly more likely to choose flexible and traditional transit than car commuters in the choice experiments. The implications of these and other relevant model results for the design and delivery of flexible, technology-enabled services are discussed.     

大数据背景下的交通模型发展思考

将传统交通调查和模型与新的信息技术相结合,根据大数据的特征改进交通模型的方法体系,是交通模型发展面临的极大挑战.分析交通大数据对交通模型研发的促进作用,特别是在人口及就业岗位分布、综合交通网络数据和基于交通调查的模型参数等核心数据方面的支撑作用.从相关定义、市场细分以及信息完整性三个方面阐述大数据与交通模型的一致性问题.深入讨论应用大数据改进交通调查技术、4D模型研发、出行分布目的地选择模型、轨道交通出行接驳模型、出行成本校核等交通模型关键技术.通过对比大数据和交通模型的决策分析过程,指出大数据与交通模型互动发展的途径.     

Individual exposure to traffic related air pollution across land-use clusters

In this study, we estimated the transportation-related emissions of nitrogen oxides (NO_x) at an individual level for a sample of the Montreal population. Using linear regression, we quantified the associations between NO_x emissions and selected individual attributes. We then investigated the relationship between individual emissions of NO_x and exposure to nitrogen dioxide (NO₂) concentrations derived from a land-use regression model. Factor analysis and clustering of land-uses were used to test the relationships between emissions and exposures in different Montreal areas. We observed that the emissions generated per individual are positively associated with vehicle ownership, gender, and employment status. We also noted that individuals who live in the suburbs or in peripheral areas generate higher emissions of NO_x but are exposed to lower NO₂ concentrations at home and throughout their daily activities. Finally, we observed that for most individuals, NO₂ exposures based on daily activity locations were often slightly more elevated than NO₂ concentrations at the home location. We estimated that between 20% and 45% of individuals experience a daily exposure that is largely different from the concentration at their home location. Our findings are relevant to the evaluation of equity in the generation of transport emissions and exposure to traffic-related air pollution. We also shed light on the effect of accounting for daily activities when estimating air pollution exposure.     

Qualitative evaluation study of urban shared spaces in New Zealand

This paper presents the findings of a qualitative analysis using on-street perception and expert interview surveys of city centre streets that have been transformed into shared spaces in Auckland, New Zealand. The principal purpose was to investigate how well the shared streets performed, especially in relation to movement, access and place functions. The shared space sites at the Elliott, Lorne and Fort Street areas were measured against the performance criteria of Placemaking, Pedestrian Focus, Vehicle Behaviour Change, Economic Impetus and Safety for all users. On-street perception surveys totalling 360 responses (120 per site) were used in this study, together with an additional set of 40 responses from a survey of a control site in O’Connell Street that remained as a traditional street. Fifteen professionals with background in transportation and urban planning participated in semi-structured expert interviews. The main results of the Median Perception Ratings from the on-street surveys confirmed that the shared spaces generally performed positively. The statistical analysis revealed that the performance criteria of ‘Pedestrian’ and ‘Safety’ had a commanding influence over the other performance measures, and with the interconnectivity of the five objectives the perceived success of the urban shared spaces.     

基于小波奇异性检测的发动机故障诊断方法研究

针对通过二进离散小波变换计算出的Lipschitz指数不够精确且不能描述奇异点能量的不足,提出了模极大值点能量法并用于信号的奇异性检测。通过仿真证明采用该方法不仅能准确定位奇异点发生的位置,并且能描述其能量。将该方法应用于发动机曲轴轴承故障诊断时,为了突出局部时间段的信号特征,采用抽区间采样方法抽取特定时间段的信号。试验结果表明,两种方法的结合能有效区分出曲轴轴承的不同技术状况,并得出最佳诊断部位和最佳检测转速。     

大型抓斗式挖泥船起重机基座支撑结构强度及建造要点分析

针对现场工程技术条件对抓斗式挖泥船起重机基座支撑结构的结构强度的高要求,以60 m3抓斗式挖泥船中700 t起重机为例,运用有限元软件对其基座支撑结构进行有限元分析,对该结构设计、制造、检验中的相关问题结合有限元分析结果进行讨论,总结出该结构的设计、制造、检验要点,提出相关建议。     

多潮位站数据程序化处理及其在远岸水深测量中的应用

为实现远岸水深测量的需要,本文利用三角分带改正法,快速准确地获得潮位改正数,实现多潮位站的数据程序化处理,自动生成测点高程,并与传统方法进行比较,分析该方法在水深测量中的优越性。     

学龄儿童出行方式特征及其影响因素

小学阶段学龄儿童处于出行有人陪伴与无人陪伴的过渡期,其上下学时间与城市交通高峰时段重叠,常引发区域性的交通拥堵或其他社会问题。基于北京市西城区5所不同类型小学的学生及家庭成员早高峰出行调查数据,分析表明步行是儿童最主要的出行方式,儿童出行方式选择与小学类型存在明显相关性。重点探讨儿童及家长出行方式选择的影响因素,包括儿童自身特征、家庭及其成员特征、城市交通与环境特征。结果显示,家庭及其成员特征对儿童出行方式选择具有决定性影响;现状城市公共交通无法满足儿童上下学的出行需求;家长对学校周边的交通环境满意度较低,导致儿童上下学以个体出行方式为主。