山区泥石流发育地段的河岸冲刷防护设计

结合国道314线喀什至红其拉甫公路冲刷防护工程实例,详细介绍山区泥石流发育的宽阔河床地段的冲刷防护设计,实践证明,该设计方法是行之有效的。     

基于发动机联合控制的AMT换挡控制策略

分析了AMT换挡类型,提出了基于CAN总线的发动机联合控制策略,即TCU通过CAN及ECU扭矩控制功能对发动机扭矩进行精确控制,同时基于发动机瞬态扭矩对离合器实现精确分离和接合控制.针对不同换挡工况给出了离合器分离/接合与发动机降扭/扭矩恢复协调控制策略,同时提出了选换挡过程动态调整转速控制策略.试验结果表明,所提策略可以增强AMT换挡过程的平顺性和动力性,减小离合器滑摩,且具有很好的鲁棒性,有助于提高AMT换挡品质.     

铁路隧道下穿既有公路地层变形特性研究

文章结合张唐铁路工程燕山隧道下穿公路出口段,采用三维有限差分程序,研究分析了其施工过程中的地层变形特性、力学响应、能量积聚及塑性区分布特征.研究结果表明:公路最大沉降量小于规范要求,围岩竖向最大变形为20 mm,水平变形为16 mm;掌子面前方挤出变形明显,最大值为38 mm;边墙能量密度集中现象较显著,位于距洞壁5 m深部围岩处;掌子面前方6 m左右围岩处出现能量积聚,为掌子面稳定关键部位:塑性区主要集中在掌子面前方、拱肩、边墙及墙脚.为此,建议对掌子面进行预加固,保证墙脚和拱肩部位配筋,提高结构整体稳定性.     

轨道交通自动售检票系统的RAMS设计

系统地阐述和分析轨道交通自动售检票AFC系统RAMS的基本要求,以及在设计阶段的主要任务.结合运营经验,针对AFC系统不同层面提出RAMS的设计指标.根据AFC系统对财务安全及系统安全的特殊需求,提出其安全体系应将技术与管理并重,按照安全系统工程的理念加以构建.     

市政中水引入地铁系统的可行性分析

阐述地铁系统中采用市政中水的可行性,针对中水的特点,对其应用方向、水质标准、产生的问题进行分析,并展望其发展前景.     

共享汽车行业健康发展的法律对策

共享汽车是共享经济的重要组成部分,共享汽车行业有交易风险可控性和交易方便的属性.共享汽车行业便利了人民群众的日常出行,同时给当地带来大量就业机会,促进当地经济社会发展.然而,共享汽车行业也有自身的风险,第一是对传统出租车行业的冲击给当地带来不稳定社会因素,第二是是共享汽车行业门槛较低,行业内有可能发生违法犯罪的情形,第...     

不同滑带角度滑坡作用下隧道衬砌结构受力特征

随着越来越多的隧道工程穿越滑坡区,滑坡与隧道相互作用过程的研究尤为重要. 为研究不同滑带角度滑坡对隧道衬砌结构受力的影响,以大（同）准（格尔）铁路南坪隧道为例,采用室内模型试验、数值模拟的方法,对0°、10°、20°、30°、40°、50°不同滑带角度条件下滑坡推力作用下隧道衬砌结构受力的影响特征及变化规律进行研究. 研究结果表明:滑带角度越小,隧道变形越大,作用在隧道衬砌结构上的弯矩、剪力及土压力越大,并在拱脚处出现最大值,形成隧道拱结构左右受力不对称特征,呈现偏压现象;通过计算隧道拱结构左右两侧的竖向偏压应力比显示,在拱肩位置且滑带为0时,偏压应力比为1.17,随着滑带角度的增大,隧道衬砌拱结构左右应力差越来越小,趋于平衡拱;在拱脚位置,偏压应力比随滑带角度的增大而逐渐增大,隧道衬砌拱结构左右两侧所受应力差越来越大,趋向于偏压隧道,最小偏压比和最大偏压比分别为1.08、1.87.      

An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles

Surveys of behavior could benefit from information about people’s relative ranking of choice alternatives. Rank ordered data are often collected in stated preference surveys where respondents are asked to rank hypothetical alternatives (rather than choose a single alternative) to better understand their relative preferences. Despite the widespread interest in collecting data on and modeling people’s preferences for choice alternatives, rank-ordered data are rarely collected in travel surveys and very little progress has been made in the ability to rigorously model such data and obtain reliable parameter estimates. This paper presents a rank ordered probit modeling approach that overcomes limitations associated with prior approaches in analyzing rank ordered data. The efficacy of the rank ordered probit modeling methodology is demonstrated through an application of the model to understand preferences for alternative configurations of autonomous vehicles (AV) using the 2015 Puget Sound Regional Travel Study survey data set. The methodology offers behaviorally intuitive model results with a variety of socio-economic and demographic characteristics, including age, gender, household income, education, employment and household structure, significantly influencing preference for alternative configurations of AV adoption, ownership, and shared usage. The ability to estimate rank ordered probit models offers a pathway for better utilizing rank ordered data to understand preferences and recognize that choices may not be absolute in many instances.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

Comparison on travel scheduling between driving and walking trips by habitual car users

Research on walking behavior has become increasingly more important in the field of transportation in the past decades. However, the study of the factors influencing the scheduling decisions related to walking trips and the exploration of the differences between travel modes has not been conducted yet. This paper presents a comparison of the scheduling and rescheduling decisions associated with car driving trips and walking trips by habitual car users using a data set collected in Valencia (Spain) in 2010. Bivariate probit models with sample selection are used to accommodate the influence of pre-planning on the decision to execute a travel as pre-planned or not. The explicative variables considered are: socio-economic characteristics of respondents, travel characteristics, and facets of the activity executed at origin and at destination including the scheduling decisions associated with them. The results demonstrate that a significant correlation exists between the choices of pre-planning and rescheduling for both types of trips. Whether for car driving or walking trips, the scheduling decisions associated with the activity at origin and at destination are the most important explicative factors of the trip scheduling and rescheduling decisions. However, the rescheduling of trips is mainly influenced by modifications in the activity at destination. Some interesting differences arise regarding the rescheduling decision processes between travel modes: if pre-planned, walking trips are less likely to be modified than car driving trips, showing a more rigid rescheduling behavior.