城市浅埋及超浅埋隧道非爆技术设备选型与配套研究

随着我国铁路建设事业的迅猛发展,隧道开挖作业所面临的环境越来越复杂.重庆铁路枢纽规模宏大,穿越城市繁华区,尤以新红岩隧道埋深浅,上部楼房林立、人口密集,重要建(构)筑物和精密设备保护点较多.如何控制隧道施工对周边环境及邻近居民的影响是本工程重难点所在.文章针对非爆破开挖技术方案进行比选并结合隧道工程实际情况最终选择了悬臂式掘进机方案.     

铁路旅客运输推行碳普惠制的思考

双碳目标是实现我国经济高质量发展、能源结构清洁转型的必然要求,节能降碳是达成目标的有效途径.碳普惠制旨在构建引领和激励公众践行绿色低碳行为的正向引导机制,降低生活领域的碳排放量.本文总结了我国碳普惠制的发展现状以及国外碳普惠制实践经验,从应用领域、数据采集、核算规则和激励方式四个方面,提出铁路推广碳普惠制的几点思考.     

Understanding successful workplace travel initiatives in the UK

Across the world, there is increasing interest in managing car traffic. One approach developed for addressing the journey to work is known as ‘workplace travel planning’. This paper primarily reports on 20 case studies of UK employers undertaking travel planning, who had cut commuter driving by an average of 18%. It concludes that considerable behavioural change can be achieved in a variety of contexts – but employers usually need an overall strategy that addresses car parking, in addition to improving alternative travel modes. Moreover, a more comprehensive national strategy is needed, if travel planning is to achieve its potential.     

Using Focus and NomiNal Group Techniques for a Better Understanding of the Transit Disadvantaged Needs

The research presented in this paper explores the context, method, and value of focus group research in transit needs assessments. Group participatory research can generate data that are not easily obtained by other methods. The paper focuses on lessons from three Nebraska communities whose transit disadvantaged rely on community-based paratransit services. Because of the size of the paratransit population and the inability to control who showed up to the focus group sessions, a modified group research protocol was adopted in order to garner information from whomever attended the session. The population parameters and the number of people at the meetings were anticipated by the researchers and mitigated by incorporating nominal group techniques. Research findings from the focus group sessions are discussed paying particular attention to the candid and policy-specific comments made by the focus group participants. The paper concludes with an application of focus group research in transit planning.     

Analyzing the preference for non-exclusive forms of telecommuting: Modeling and policy implications

This study examines three models of the individual's preference for home- and center-based telecommuting. Issues concerning the estimation of discrete models when the alternatives are non-exclusive are discussed. Two binary logit models are presented, one on the preference to telecommute from a center versus not telecommuting from a center (adjusted ² = 0.24), and the other on the preference to telecommute from a center over telecommuting from home (adjusted ² = 0.64). A nested logit model is also estimated on the following four alternatives: preferring not to telecommute, preferring either form of telecommuting, preferring to telecommute from home, and preferring to telecommute from a center (adjusted ² = 0.35).The results of the models illustrated the importance of attitudinal measures in measuring an individual's preference to telecommute. Oblique factor scores representing workplace interaction, stress, workaholism, internal control, and commute stress were statistically significant in some or all of the models. Other explanatory variables which were found to be consistently significant were education, job suitability, and age. Most respondents preferred either to telecommute from home or were indifferent between either form of telecommuting, which raises the question as to whether there really is a sizeable market niche to be filled by telecommuting centers, and hence whether they may make a significant contribution to transportation demand reduction.     

Willingness to accept longer commutes for better salaries: Understanding the differences within and between couples

This paper reports on an analysis aiming to understand differences across individual people in their willingness to accept increased commuting time in return for higher salary, using Hierarchical Bayes (HB) analysis of a dataset collected in Sweden. We find that socio-demographic and attitudinal differences are significant in explaining the variations in values of time for individuals, in particular income, who drives when carpooling and hours worked per week. Additionally we also examine the values of individuals when their choices also impact on the salary and commute of their partner, finding that incomes, income differentials, driving behaviour when carpooling, division of housework and car user decisions significantly explain the values assigned to others and variations in an individual’s own values once their partner is affected. The overall richness of the results reflect the benefits that posterior analysis can bring, and highlight the computational efficiency of Bayesian methods in producing such conditionals at an individual level.     

Modeling schedule recovery processes in transit operations for bus arrival time prediction

Many existing algorithms for bus arrival time prediction assume that buses travel at free‐flow speed in the absence of congestion. As a result, delay incurred at one stop would propagate to downstream stops at the same magnitude. In reality, skilled bus operators often constantly adjust their speeds to keep their bus on schedule. This paper formulates a Markov chain model for bus arrival time prediction that explicitly captures the behavior of bus operators in actively pursuing schedule recovery. The model exhibits some desirable properties in capturing the schedule recovery process. It guarantees provision of the schedule information if the probability of recovering from the current schedule deviation is sufficiently high. The proposed model can be embedded into a transit arrival time estimation model for transit information systems that use both real‐time and schedule information. It also has the potential to be used as a decision support tool to determine when dynamic or static information should be used.     

Modeling stochastic perception error in the mean-excess traffic equilibrium model

In this paper, we extend the α-reliable mean-excess traffic equilibrium (METE) model of Chen and Zhou (Transportation Research Part B 44(4), 2010, 493-513) by explicitly modeling the stochastic perception errors within the travelers’ route choice decision processes. In the METE model, each traveler not only considers a travel time budget for ensuring on-time arrival at a confidence level α, but also accounts for the impact of encountering worse travel times in the (1 − α) quantile of the distribution tail. Furthermore, due to the imperfect knowledge of the travel time variability particularly in congested networks without advanced traveler information systems, the travelers’ route choice decisions are based on the perceived travel time distribution rather than the actual travel time distribution. In order to compute the perceived mean-excess travel time, an approximation method based on moment analysis is developed. It involves using the conditional moment generation function to derive the perceived link travel time, the Cornish-Fisher Asymptotic Expansion to estimate the perceived travel time budget, and the Acerbi and Tasche Approximation to estimate the perceived mean-excess travel time. The proposed stochastic mean-excess traffic equilibrium (SMETE) model is formulated as a variational inequality (VI) problem, and solved by a route-based solution algorithm with the use of the modified alternating direction method. Numerical examples are also provided to illustrate the application of the proposed SMETE model and solution method.     

基于TAM与认知理论的无人驾驶汽车接受度研究

为深入了解消费者对无人驾驶汽车的认知接受机制,探究影响无人驾驶汽车接受意向的主要因素,本文在认知理论的框架上,引入隐私关注与隐私损失变量,结合TAM模型构建无人驾驶汽车接受模型。实证研究结果表明,无意识的自动认知和经过深思熟虑的理性认知会对消费者的接受意向产生影响。自动认知产生的两种技术倾向(促进技术使用与抑制技术使用)不仅会直接影响接收新技术意向的形成,而且还会通过理性认知中的隐私关注间接调节感知易用性、感知有用性对接受意向的作用,隐私损失对接受意向的影响不大。研究结果可以为提高无人驾驶汽车的接受程度提供理论和实践上的启示。     

Understanding the relationships between private automobile availability, overall physical activity, and travel behavior in adults

In most developed countries motorized transportation is the dominant form of travel for long and short journeys. Transport-related physical activity (TPA), however, is advocated as an appropriate transport mode for traveling short distances. The purpose of this study is to explore the associations between private automobile availability, overall physical activity levels, and TPA engagement in the adult population. A population-representative telephone survey assessed socio-demographics, private automobile availability, overall physical activity levels, and travel to place of work/study and the convenience shop with an adult sample (n = 2,000) residing in North Shore City, Auckland, New Zealand in April 2005. The majority of respondents reported unrestricted (80%) or frequent (12%) private automobile availability. After controlling for covariates, binary logistic regression analyses revealed those with no private automobile available were less likely to be classified as sufficiently active for health benefits when compared to respondents with unrestricted private automobile availability. However, this finding was based on a small minority (4%). Also, those reporting no private automobile availability were more likely to walk or cycle to place of employment and the convenience shop when compared to those with unrestricted private automobile availability. Similar to other self-report travel and physical activity survey tools, the questionnaire used potentially did not adequately capture TPA engagement. Future TPA research needs to incorporate objective measures to address this issue.

Modeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon

Transportation - This study investigates the current and potential uptake of ridesourcing services, such as Uber and Careem, by the students of the American University of Beirut, Lebanon. A hybrid...     

Modeling intermodal equilibrium for bimodal transportation system design problems in a linear monocentric city

This paper investigates the intermodal equilibrium, road toll pricing, and bus system design issues in a congested highway corridor with two alternative modes - auto and bus - which share the same roadway along this corridor. On the basis of an in-depth analysis of the demand and supply sides of the bimodal transportation system, the mode choice equilibrium of travelers along the continuum corridor is first presented and formulated as an equivalent variational inequality problem. The solution properties of the bimodal continuum equilibrium formulation are analytically explored. Two models, which account for different infrastructure/system regulatory regimes (public and private), are then proposed. In the public regulatory model, the road toll location and charge level are simultaneously optimized together with the bus service fare and frequency. In the private regulatory model, the fare and frequency of bus services, which are operated by a profit-driven private operator, are optimized for exogenously given toll pricing schemes. Finally, an illustrative example is given to demonstrate the application of the proposed models. Sensitivity analysis of residential/household distribution along the corridor is carried out together with a comparison of four different toll pricing schemes (no toll, first best, distance based, and location based). Insightful findings are reported on the interrelationships among modal competition, market regulatory regimes, toll pricing schemes, and urban configurations as well as their implications in practice.     

Social distancing in public transport: mobilising new technologies for demand management under the Covid-19 crisis

Dense urban areas are especially hardly hit by the Covid-19 crisis due to the limited availability of public transport, one of the most efficient means of mass mobility. In light of the Covid-19 pandemic, public transport operators are experiencing steep declines in demand and fare revenues due to the perceived risk of infection within vehicles and other facilities. The purpose of this paper is to explore the possibilities of implementing social distancing in public transport in line with epidemiological advice. Social distancing requires effective demand management to keep vehicle occupancy rates under a predefined threshold, both spatially and temporally. We review the literature of five demand management methods enabled by new information and ticketing technologies: (i) inflow control with queueing, (ii) time and space dependent pricing, (iii) capacity reservation with advance booking, (iv) slot auctioning, and (v) tradeable travel permit schemes. Thus the paper collects the relevant literature into a single point of reference, and provides interpretation from the viewpoint of practical applicability during and after the pandemic.

     

Modeling speed-flow relationship and merging behavior in work zone merging areas

This paper aims to investigate the speed-flow relationship and drivers’ merging behavior in work zone merging areas. It first proposes lane-based speed-flow models, incorporating traffic conflicts among the lanes. It proceeds to develop a desired merging location model determining where drivers start to consider merging and a binary logit model that is applied to estimate the probabilities that drivers will merge into current adjacent gaps. A merging distance model is also proposed to find the 85th percentile of the merging distance. Finally, real work zone traffic data in Singapore are used to calibrate and evaluate the developed models. The findings show that the speed-flow relationship in the through lane is affected by the merge lane traffic under uncongested circumstances. Satisfactory results indicate that the merging behavioral models can competently predict drivers’ merging behavior and that the merging distance model could provide accurate information for traffic engineers to calculate the merge lane length.     

Modeling household interactions in daily in-home and out-of-home maintenance activity participation

The activity travel patterns of individuals in a household are inter-related, and the realistic modeling of activity-travel behavior requires that these interdependencies be explicitly accommodated. This paper examines household interactions impacting weekday in-home and out-of-home maintenance activity generation in active, nuclear family, households. The in-home maintenance activity generation is modeled by examining the duration invested by the male and female household heads in household chores using a seemingly unrelated regression modeling system. The out-of-home maintenance activity generation is modeled in terms of the decision of the household to undertake shopping, allocation of the task to one or both household heads, and the duration of shopping for the person(s) allocated the responsibility. A joint mixed-logit hazard-duration model structure is developed and applied to the modeling of out-of-home maintenance activity generation. The results indicate that traditional gender roles continue to exist and, in particular, non-working women are more likely to share a large burden of the household maintenance tasks. The model for out-of-home maintenance activity generation indicates that joint activity participation in the case of shopping is motivated by resource (automobiles) constraints. Finally, women who have a higher propensity to shop are also found to be inherently more efficient shoppers.     

基于AUTOCAD的ANSYS几何建模初探

基于AutoCAD平台,用其自带的VBA开发应用程序,建立了从AutoCAD单线几何模型到ANSYS杆系模型的转换接口程序,该程序可将在AutoCAD环境下建立的复杂空间模型转换成ANSYS中的结构模型,方便快捷实现土木工程中复杂的几何建模功能,为工程计算和研究提供方便。通过自定义截面和空间网架建模两个实例验证了该方法的可行性和实用性。     

Modeling the bilateral micro‐searching behavior for urban taxi services using the absorbing markov chain approach

This paper develops a mathematical model that is based on the absorbing Markov chain approach to describe taxi movements, taking into account the stochastic searching processes of taxis in a network. The local searching behavior of taxis is specified by a logit form, and the O‐D demand of passengers is estimated as a logit model with a choice of taxi meeting point. The relationship between customer and taxi waiting times is modeled by a double‐ended queuing system. The problem is solved with a set of non‐linear equations, and some interesting results are presented. The research provides a novel and potentially useful formulation for describing the urban taxi services in a network.     

Modeling learning and adaptation processes in activity-travel choice A framework and numerical experiment

This paper develops a framework for modeling dynamic choice based on a theory of reinforcement learning and adaptation. According to this theory, individuals develop and continuously adapt choice rules while interacting with their environment. The proposed model framework specifies required components of learning systems including a reward function, incremental action value functions, and action selection methods. Furthermore, the system incorporates an incremental induction method that identifies relevant states based on reward distributions received in the past. The system assumes multi-stage decision making in potentially very large condition spaces and can deal with stochastic, non-stationary, and discontinuous reward functions. A hypothetical case is considered that combines route, destination, and mode choice for an activity under time-varying conditions of the activity schedule and road congestion probabilities. As it turns out, the system is quite robust for parameter settings and has good face validity. We therefore argue that it provides a useful and comprehensive framework for modeling learning and adaptation in the area of activity-travel choice.