Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.     

Subjective-utility travel time budget modeling in the stochastic traffic network assignment

ABSTRACT

In this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network.     

Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.     

中国TBM施工技术进展、挑战及对策

总结我国近30年来TBM设计与施工技术的发展历程,可归纳为以下5个阶段:1)研发探索和试用阶段;2)以国外施工承包商为主体,采用国外设计制造TBM施工我国隧道工程阶段;3)独立进行TBM招标采购和选型设计,并建立起自主的TBM施工队伍阶段;4)与国外厂家联合设计制造TBM,工程应用和自主施工快速发展阶段;5)实现TBM国产化,面向国内外TBM工程市场自主施工阶段。通过我国不同时期TBM施工的典型工程,介绍我国在复杂地质、大坡度、高海拔、不同直径、不同机型、超长隧洞TBM施工方面取得的经验、技术积累和业绩,展示我国TBM在穿越断层破碎带、软弱变形、岩爆、涌水等不良地质洞段取得的一系列施工新技术,以及最高月进尺1 868 m、平均月进尺超过600 m和掘进作业利用率超过40%的掘进技术水平。分析TBM在极硬岩、大断层破碎带、软弱大变形围岩、强岩爆围岩、涌水突泥洞段、高地热隧洞和超长隧洞工程中施工面临的风险和挑战,并提出一些相应的技术措施和对策,期望这些措施和对策在未来大量实际工程中进一步得到实践验证、优化和改进,不断积累和创新TBM设计与施工新技术。     

广东山区高速公路挖方边坡常见病害及防治策略

广东省山区高速公路发展迅速,但诸多挖方边坡在修建过程中就产生了不同程度的病害。这些病害产生的原因包括气候、地质条件和人为因素,给施工工期、造价及安全管理造成较大影响。鉴于塌方病害在广东地区山区高速公路挖方边坡中较为常见,根据破坏方式及影响范围的深度将其划分为浅层溜塌、浅层滑塌和深层滑塌(滑坡)。结合工程建设经验,提出了山区路堑边坡的防治策略,可为类似工程的设计、施工提供借鉴。     

波形钢腹板连续梁桥设计和施工相关问题探讨

大跨度波形钢腹板梁桥是一种新型桥梁结构,因其采用波形钢腹板替代混凝土腹板,相比传统的预应力混凝土连续梁桥,具有轻型、经济等诸多方面的特点。以前山河波形钢腹板连续梁桥为背景,针对设计和施工中的诸如内衬砼、剪力键、横隔板等相关问题进行了分析探讨。     

暗挖隧道装配式管片拼装技术研究

为解决目前暗挖隧道二次衬砌工序繁杂、施工进度慢、成形质量差等问题,结合盾构矿山法施工工艺及土压平衡盾构管片拼装原理,阐述暗挖隧道装配式管片拼装在施工中需重点解决的关键技术,并介绍配套的拼装设备结构组成及功能特点。     

基于BIM的公路隧道运维管理系统设计与开发

近年来,我国公路隧道建设里程快速增长,但在隧道运维管理中存在技术落后、管理人员配置不足等问题。针对管理中存在的问题,本文提出将BIM(building information modeling,建筑信息模型)引入公路隧道的运维管理,通过制定具体实施规划及设计系统架构,实现可视化的公路隧道运维管理。以浙江省41省道岭下隧道工程为依托,建立基于BIM的公路隧道运维管理平台,为公路隧道运维管理提供一种直观、便捷的管理方式,提高公路隧道的信息化管理水平。     

圆形隧道施工对不同深度地层沉降影响的模型试验研究

为了预测圆形隧道施工引起地表以下不同埋深地层沉降特征,首先,通过理论推导不同地层最大沉降位移与沉降槽宽度系数的函数关系;然后,建立包括试验台架、地层模型、圆形隧道开挖模型以及测量地层变形装置的平面应变模型试验系统。通过理论解析和模型试验可知:1)地表以下地层的最大沉降位移与沉降槽宽度系数成反比;2)不同深度地层的沉降位移随着地层埋深的增加而增大,且地表以下地层沉降槽曲线仍然符合正态分布;3)通过对模型试验数据进行回归分析,得到黏土地表以下不同深度地层沉降槽宽度系数的计算公式,从而为预测圆形隧道施工地表以下不同深度地层竖向位移提供了一种可靠的计算方法。     

南昌红谷沉管隧道短管节干坞内拉合对接施工技术

沉管隧道最终接头短管节在牵移和拉合过程中易发生偏移与倾斜,且GINA止水带压缩到设计值难度较大。以南昌红谷沉管隧道为例,从准备、牵移、拉合及后处理4个阶段介绍短管节对接拉合施工工艺。通过对底钢板打磨、涂抹黄油等,减小底部摩擦阻力。采用计算机控制液压同步提升系统、液压数据量测、钢端壳间距测量等措施,对短管节轴线及平面控制。实践表明:GINA止水带压缩量误差仅为+4 mm,短管节轴线及平面偏差均在可控范围内,短管节干坞内拉合对接操作可行、质量可靠。