郑西客运专线大断面黄土隧道施工方法研究

文章结合郑西客运专线大断面黄土隧道设计、施工及科研情况,从沉降变形控制、施工进度、机械配套等方面对双侧壁导洞、CRD、CD、弧形导洞等4种工法进行了比选分析,提出了与不同工况相适应的工法以及施工要点,可供参考和借鉴。     

厦门翔安海底隧道CRD法中各施工部对拱顶下沉的影响分析

文章以厦门翔安海底隧道陆域段软弱地层大断面浅埋隧道CRD法施工为工程背景,结合现场位移监控量测和实际施工情况,对不同开挖顺序下CRD法中各施工部对拱顶下沉的影响进行了分析研究。研究结果表明,翔安隧道CRD法拱顶下沉为台阶状上升曲线,最后趋于稳定;各分部开挖引起的拱顶下沉量具有一定的比例关系,可用于对最终拱顶下沉量的预报和控制指示;各分部仰拱及时闭合是控制最终下沉量的关键;采用CRD1、3部超前施工比CRD1、2部超前对控制拱顶下沉较为有利;施工中应重点监测和控制最早开挖的CRD1部拱顶下沉。     

高原大跨段隧道CRD法施工技术研究

首先,对CRD法（Controlled Remote Displacement Method）的原理进行详细介绍,并分析其适用性和优势;其次,针对高原大跨段隧道的特点,提出CRD法在高原大跨段隧道施工中的具体应用方法;最后,通过实例分析,验证CRD法在高原大跨段隧道施工中的实际效果。研究结果表明,CRD法可以有效地解决高原大跨段隧道施工中的难题,提高施工效率,并保证施工质量和安全。因此,CRD法具有广泛的应用前景,并可为隧道工程的实际施工提供参考依据。     

超浅埋暗挖大跨隧道下穿既有隧道的沉降控制技术

文章基于成都博览城综合交通枢纽18号线西博城站超浅埋暗挖大跨隧道施工实例,针对原设计CRD法施工存在的不足,提出了超浅埋暗挖大跨隧道下穿既有隧道的沉降控制和CRD法施工优化技术方案,并在施工中采用旋喷桩、超前大管棚和超前小导管注浆等辅助措施进行地层加固,优化CRD小分部台阶开挖法及衬砌分部分块施工方案。实践证明,采用优化的CRD法施工方案和措施是有效的,减少了安全风险、加快了施工进度、降低了工程成本,可为今后类似工况条件下地铁区间暗挖大跨隧道下穿既有城市道路、隧道的施工和地表沉降控制提供借鉴。     

土质浅埋隧道CRD法施工中隔壁变形监测与分析

以天恒山隧道为工程依托,应用全站仪对边量测原理,对土质浅埋隧道CRD法施工中隔壁的变形情况进行现场监控量测,研究和分析了中隔壁的变形规律.研究结果表明:中隔壁的水平变形受CRD法前3部施工影响较大,第1部和第3部施工使中隔壁产生收敛变形,而第2部施工使中隔壁产生扩张变形;中隔壁的竖向变形受CRD法各部施工影响都较大,只有仰拱全部闭合后竖向变形才趋于缓和.     

地铁车站多工法施工关键技术数值模拟研究

本文结合具体实际工程,对车站CRD工法施工地铁进行了数值模拟和在施工2号线车站主体时运用PBA工法,对该车站主体也进行了数值分析模拟,模拟计算结果表明在CRD工法中的薄弱环节是拆除底部临时支撑施工二衬,本文还提出了"先上后下,先边后中"的最优化导洞开挖施工顺序,希望能给地铁车站施工提供经验借鉴。     

大断面浅埋偏压隧道CRD法施工工序研究

文章以良村隧道CRD法施工为工程背景,布设了变形监测点及内力测试元件,分析了CRD法施工隧道围岩变形情况及结构内力特征,并对CRD法施工隧道在不同开挖顺序下的开挖过程进行了数值模拟,分析比较了不同开挖顺序时的围岩位移、应力变化情况。结果表明:CRD法对各分部施工工序影响较大,且各分部对拱顶下沉的影响程度从大至小依次为1部、2部、3部和4部;隧道内侧围岩压力大于外侧,钢支撑内力均为压应力,且拱腰位置轴力大于其它部位。比较隧道开挖变形的差异以及结构的受力特点,结合数值分析结果,得出了山体外侧先开挖方案无论在围岩变形还是隧道结构受力方面相比于山体外侧后开挖都较小,安全系数相对较高。因此,合理的施工工序应该是先进行山体外侧开挖并施作初期支护,然后再在山体内侧开挖施工。     

公路隧道软弱围岩施工方法的探讨

文章根据当前软弱围岩中公路隧道的施工方法和施工特点,采用数值分析的方法,对台阶法、CD法、CRD法的施工力学特征和存在的问题进行了分析,并对各种施工方法进行了比较,提出了应用三种施工方法的建议。     

大跨浅埋公路隧道下穿既有建筑施工的沉降控制

厦门机场下穿34号楼隧道工程,隧顶到建筑结构底3 m,属浅埋大跨下穿既有建筑物连拱隧道工程.论文根据工程类比法,采用CRD法优化隧道施工步骤;借助数值分析方法,分析既有建筑的沉降规律,把握了CRD法重点施工步骤.根据现场实测及数值模拟结果,提出了超前注浆、地面硬化及补偿抬升注浆、洞内全断面帷幕注浆、大管棚超前支护等多种施工辅助措施.实践表明,施工过程中既有建筑结构沉降得到有效控制,最终沉降量小于40 mm.     

高陡边坡下隧道洞口区稳定性研究

为研究隧道开挖工法对高陡边坡下隧道洞口区稳定性的影响,文章依托某实际隧道工程,采用FLAC3D软件建立了相应的三维模型,对三台阶法、环形预留核心土法和CRD法开挖施工进行模拟分析,并与现场监测结果进行对比,得到如下结论:(1)对比三种工法开挖时隧道围岩和边坡变形可知,CRD法为最适宜,采用该工法开挖隧道时,洞口区围岩和边坡变形最小;(2)数值模拟所得围岩及边坡变形变化规律与现场监测结果基本一致,故采用数值法进行隧道施工优化具有一定的可行性;(3)为减少隧道开挖对洞口区边坡的影响,采用CRD法进行隧道开挖,结合锚索预加固可有效提高边坡稳定性。     

Short‐term prediction of traffic parameters—performance comparison of a data‐driven and less‐data‐required approaches

The travel decisions made by road users are more affected by the traffic conditions when they travel than the current conditions. Thus, accurate prediction of traffic parameters for giving reliable information about the future state of traffic conditions is very important. Mainly, this is an essential component of many advanced traveller information systems coming under the intelligent transportation systems umbrella. In India, the automated traffic data collection is in the beginning stage, with many of the cities still struggling with database generation and processing, and hence, a less‐data‐demanding approach will be attractive for such applications, if it is not going to reduce the prediction accuracy to a great extent. The present study explores this area and tries to answer this question using automated data collected from field. A data‐driven technique, namely, artificial neural networks (ANN), which is shown to be a good tool for prediction problems, is taken as an example for data‐driven approach. Grey model, GM(1,1), which is also reported as a good prediction tool, is selected as the less‐data‐demanding approach. Volume, classified volume, average speed and classified speed at a particular location were selected for the prediction. The results showed comparable performance by both the methods. However, ANN required around seven times data compared with GM for comparable performance. Thus, considering the comparatively lesser input requirement of GM, it can be considered over ANN in situations where the historic database is limited. Copyright © 2016 John Wiley & Sons, Ltd.     

A revised branch‐and‐price algorithm for dial‐a‐ride problems with the consideration of time‐dependent travel cost

Developing demand responsive transit systems are important with regard to meeting the travel needs for elderly people. Although Dial‐a‐ride Problems (DARP) have been discussed for several decades, most researchers have worked to develop algorithms with low computational cost under the minimal total travel costs, and fewer studies have considered how changes in travel time might affect the vehicle routes and service sequences. Ignoring such variations in travel time when design vehicle routes and schedules might lead to the production of inefficient vehicle routes, as well as incorrect actual vehicle arrival times at the related nodes. The purpose of this paper is to construct a DARP formulation with consideration of time‐dependent travel times and utilizes the traffic simulation software, DynaTAIWAN, to simulate the real traffic conditions in order to obtain the time‐dependent travel time matrices. The branch‐and‐price approach is introduced for the time‐dependent DARP and tested by examining the sub‐network of Kaohsiung City, Taiwan. The numerical results reveal that the length of the time window can significantly affect the vehicle routes and quantitative measurements. As the length of the time window increases, the objective value and the number of vehicles will reduce significantly. However, the CPU time, the average pickup delay time, the average delivery delay time and the average actual ride time (ART)/direct ride time (DRT) will increase significantly as the length of the time window increases. Designing the vehicle routes to reduce operating costs and satisfy the requirements of customers is a difficult task, and a trade‐off must be made between these goals. Copyright © 2014 John Wiley & Sons, Ltd.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

Improved waveform‐feature‐based vehicle classification using a single‐point magnetic sensor

Vehicle classification systems have important roles in applications related to real‐time traffic management. They also provide essential data and necessary information for traffic planning, pavement design, and maintenance. Among various classification techniques, the length‐based classification technique is widely used at present. However, the undesirable speed estimates provided by conventional data aggregation make it impossible to collect reliable length data from a single‐point sensor during real‐time operations. In this paper, an innovative approach of vehicle classification will be proposed, which achieved very satisfactory results on a single‐point sensor. This method has two essential parts. The first concerns with the procedure of smart feature extraction and selection according to the proposed filter–filter–wrapper model. The model of filter–filter–wrapper is adopted to make an evaluation on the extracted feature subsets. Meanwhile, the model will determine a nonredundant feature subset, which can make a complete reflection on the differences of various types of vehicles. In the second part, an algorithm for vehicle classification according to the theoretical basis of clustering support vector machines (C‐SVMs) was established with the selected optimal feature subset. The paper also uses particle swarm optimization (PSO), with the purpose of searching for an optimal kernel parameter and the slack penalty parameter in C‐SVMs. A total of 460 samples were tested through cross validation, and the result turned out that the classification accuracy was over 99%. In summary, the test results demonstrated that our vehicle classification method could enhance the efficiency of machine‐learning‐based data mining and the accuracy of vehicle classification. Copyright © 2014 John Wiley & Sons, Ltd.     

Modeling the evolutions of day‐to‐day route choice and year‐to‐year ATIS adoption with stochastic user equilibrium

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.     

Optimizing one‐way traffic network reconfiguration and lane‐based non‐diversion routing for evacuation

Unfortunately, situations such as flood, hurricanes, chemical accidents, and other events occur frequently more and more. To improve the efficiency and practicality of evacuation management plan, an integrated optimization model of one‐way traffic network reconfiguration and lane‐based non‐diversion routing with crossing elimination at intersection for evacuation is constructed in this paper. It is an integrated model aiming at minimizing the network clearance time based on Cell Transmission Model. A hybrid algorithm with modified genetic algorithm and tabu search method is devised for approximating optimal problem solutions. To verify the effectiveness of the proposed model and solving method, two cases are illustrated in this paper. Through the first example, it can be seen that the proposed model and algorithm can effectively solve the integrated problems, and compared with the objective value of the original network, the network clearance time of the final solution reduces by 47.4%. The calculation results for the realistic topology and size network of Ningbo in China, which locates on the east coast of the Pacific Ocean, justify the practical value of the model and solution method, and solutions under different settings of reduction amount of merging cell capacity embody obvious differences. Copyright © 2015 John Wiley & Sons, Ltd.     

Improved modeling of park‐and‐ride transfer time: Capturing the within‐day dynamics

An important factor that affects park‐and‐ride demand is transfer time. However, conventional park‐and‐ride demand models treat transfer time as a single value, without considering the time‐of‐day effect. Since early comers usually occupy spots closer to the entrance, their transfer times are shorter. Hence, there is a relationship between arrival time and transfer time. To analyze this relationship, a micro‐simulation model is developed. The model simulates the queuing system at the entrance and the pattern that parking spots are occupied in the parking lot over time. As expected, the model output illustrates an increasing relationship between arrival time and transfer time. This relationship has significant implication in mode choice models because it means that the attractiveness of park‐and‐ride depends on the time of arrival at the park‐and‐ride lot. This model of park‐and‐ride transfer time can potentially improve travel demand forecasting, as well as facilitate the operation and design of park‐and‐ride facilities.