Modelling the impact of weather conditions on active transportation travel behaviour

Three weather sensitive models are used to explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data are restricted to non-captive commuters who have the option of selecting among five basic modes of auto driver, auto passenger, transit, bike and walk. Daily trip rates in various weather conditions are assessed. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.     

Factors influencing travel mode choice among families with young children (aged 0–4): a review of the literature

Life events, such as the birth of a child, disrupt habitual travel behaviour and provide a valuable opportunity to influence the adoption of sustainable transport practices. However, in order for sustainable travel practices to be adopted, an understanding is required of the factors that influence travel mode choice among families with young children. Research in this field is particularly timely given many in the millennial generation, a comparably large cohort, are approaching this life stage. This comprehensive literature review develops a framework of factors influencing travel mode choice among families with young children. The findings reveal a multitude of factors influence decisions about mode choice, and, in particular, encourage travel by car, when travelling with young children. The paper concludes with an agenda for future research about travel among families with young children, a largely overlooked group of transport users.     

长江口南汇边滩短期冲淤变化分析

南汇边滩位于长江口和杭州湾的交汇地带,受长江口和杭州湾北岸两股潮流的控制,近年来由于低潮滩促淤围垦工程导致其水流和泥沙运移、沉积和地貌发生了显著的变化。根据2006—2008年南汇边滩测图及2007年11月—2008年11月每个季度的9个断面测量资料,结合区域内的泥沙沉积特征,探讨南汇边滩对周边涉水围垦工程和流域来水来沙变异做出适应性地貌耦合过程之后的近期冲淤演变规律,着重探讨季节性冲淤特征。结果表明:年度上南汇东滩以淤长为主,南汇南滩以冲刷为主。不同季节南汇边滩冲淤变化过程存在很大差异:平面上,南汇边滩等深线夏、冬季以淤进为主,春、秋季以蚀退为主;垂向上,南汇东滩断面呈春夏秋冲淤交替、冬季淤积的态势,南汇嘴断面呈秋季冲刷、冬夏季淤积的态势,而位于南汇南滩的断面则呈秋冬季冲刷、春夏季淤积态势。南汇东滩沉积物粒径总体上较细,东滩与南滩交汇处的南汇嘴附近中值粒径相对较粗,南汇南滩浅滩沉积物颗粒中值粒径最粗。     

舰载机试飞数据的移动基准区间与牛顿插值处理

分析飞行试验数据具有数据量大,需分段加载和截取的特点,针对试飞数据预处理过程中常规全局统计误差分析方法有时难以满足要求的问题,建立移动基准区间和牛顿插值相结合的误差修正模型,提出移动基准区间牛顿插方法,并应用于飞行试验数据处理中,最后通过实例验证其有效性.     

城市快速路匝道最小间距模型

匝道间距是路线设计中的重要内容,对交通流有决定性的影响。根据城市快速匝道的特点,应用驾驶员行为理论,模拟了驾驶员城市快速匝道上的驾驶行为。认为匝道间距是影响城市快速路主线运行状况的关键因素。为了合理确定匝道最小间距,必须确定匝道组合模式和计算匝道加减速车道长度,并计算出车流从匝道汇入主线后,由于车流变道而形成交织车流长度。由此建立了不同匝道组合模式下的匝道最小间距模型。应用实例表明。当匝道间距不能满足最小间距时,车速降低,服务水平下降。     

带有最优流量记忆时间差的一类新格子模型

为了分析最优流量记忆时间差对交通流稳定性的影响,本文基于考虑驾驶员估计得到的最优流量信息,同时考虑驾驶员在驾车过程中受到记忆时间的影响,给出了一类新的格子流体动力学模型.首先,基于线性稳定性理论,获得了新模型的稳定性条件;随后,通过非线性分析方法,给出该模型的mKdV方程;然后,基于求解上述方程所得到的扭结-反扭结孤立波可用于描述交通拥挤的转化和传播过程.最后,通过仿真算例验证了上述理论分析的结论,即驾驶员的记忆时间和最优流量记忆时间差能够显著影响交通流的稳定性,同时增大记忆时间步长和强度系数可以有效地增强交通流的稳定性.     

船舶调度闸外编排算法

为了提高船闸的通过能力,优化船舶进闸调度,分析了三峡船闸船舶的平均过闸间隔时间,提出了闸外编排的概念,分析了船舶在进闸调度中的操作流程,以安全性和进闸耗时为目标,建立了闸外编排的数学模型,设计了相应的启发式求解算法,将模型的目标和约束条件通过启发式方法生成船舶在闸外的排序法则。数值试验分析结果表明闸外编排数学模型切实可行,排序算法可以生成安全高效的进闸方案,闸外编排的实现考虑了船舶进闸时间和安全性原则,缩短了闸次间隔时间,提高了日开闸次数,有效地提高了通航设施的整体通过能力。     

Port authorities view state coastal management programs

Abstract

An estuarine sanctuary is a store of public values due to the ecological, cultural, recreational, aesthetic, historic, and economic services provided by the preserve. These values may be expected to increase over time because of (1) growth in the population demanding estuarine services, (2) growth in the willingness to pay for such services, and (3) growth in the actual quality and quantity of services which are provided by a protected natural system. Thus an estuarine sanctuary will be more valuable to future generations than to current generations. When weighing the cost and benefits of a preservation or development decision, a preservation decision which seems currently undesirable may in fact be socially beneficial when growth in the value of estuarine services is included.     

浅谈公路工程估算编制的新规则

新的《公路工程基本建设项目投资估算编制办法》和《公路工程估算指标》自2012年1月1日正式实施。取代1996编办和指标,针对估算编制的新规则,分析总结新旧差异,为以后估算编制工作提供指导。     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.