A behavioural car-following model that captures traffic oscillations

This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers’ car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.

On selecting an optimal wavelet for detecting singularities in traffic and vehicular data

Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.

Public participation in infrastructure and construction projects in China: From an EIA-based to a whole-cycle process

Many governments world-wide are increasingly encouraging the involvement of interested individuals, groups and organisations in their publicinfrastructure and construction (PIC) projects as a means of improving the openness, transparency and accountability of the decision-making process and help improve the projects’ long-term viability and benefits to the community. In China, however, the current participatory mechanism at the project level exists only as part of the environmental impact assessment (EIA) process. With an increasing demand for PIC projects and social equality in China, this suggests a need to bring the participatory process into line with international practice. The aim of this paper, therefore, is to identify the weaknesses of EIA-basedpublicparticipation in China and the means by which it may be improved for the whole lifecycle of PIC schemes. To do this, the results of a series of interviews with a diverse group of experts is reported which analyse the nature and extent of existing problems of publicparticipation in EIA and suggestions for improvement. These indicate that the current level of participation in PIC projects is quite limited, particularly in the crucial earlier stages, primarily due to traditional culture and values, uneven progress in the adoption of participatory mechanisms, the risk of not meeting targets and lack of confidence in public competence. Finally, aprocess flowchart is proposed to guide construction practitioners and the community in general.

Updating and verification for multi-scale finite element model of structure behavior

The method on concurrent multi-scale model of structural behavior (CMSM-of-SB) for the purpose of structural health monitoring including model updating and validating has been studied. The detailed process of model updating and validating is discussed in terms of reduced scale specimen of the steel box girder in longitudinal stiffening truss of a long span bridge. Firstly, some influence factors affecting the accuracy of the CMSM-of-SB including the boundary restraint regidity, the geometry and material parameters on the toe of the weld and its neighbor are analyzed using sensitivity method. Then, sensitivity-based model updating technology is adopted to update the developed CMSM-of-SB and model verification is carried out through calculating and comparing stresses on different locations under various loading from dynamic characteristic and static response. It can be concluded that the CMSM-of-SB based on the substructure method is valid.

Fatigue crack growth and fatigue life evaluation for welded steel bridge members with initial crack

Initial crack widely exists in the welded members of steel bridge induced by the welding procedure or by the fatigue damage crack initiation. The behavior of crack growth with a view to fatigue damage accumulation on the tip of cracks is discussed. Fatigue life of welded components with initial crack in bridges under traffic loading is investigated. Based on existing fatigue experiment results of welded members with initial crack and the fatigue experiment results of welded bridge members under constant stress cycles, the crack would keep semi-elliptical shape with variable ratio of a/c during the crack propagation. Based on the concept of continuum damage accumulated on the tip of fatigue cracks,the fatigue damage law suitable for steel bridge members under traffic loading is modified to consider the crack growth.The virtual crack growth method and the semi-elliptical crack shape assumption are proposed in this paper to deduce a new model of fatigue crack growth rate for welded bridge members under traffic loading. And the calculated method of the stress intensity factor necessary for evaluation of the fatigue life of welded bridge members with cracks is discussed.The proposed fatigue crack growth model is then applied to calculate the crack growth and the fatigue life of existing welded members with fatigue experimental results. The fatigue crack propagation computation results show that the ratio of crack depth to the half crack surface length a/c is variable during crack propagation process and the stress cycle increases with the increase of a0/c0 with certain a0/t0 .The calculated and measured fatigue lives are generally in good agreement,at some initial conditions of cracking, for welded members widely used in steel bridges.

Damage quantification techniques in acoustic emission monitoring

Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

Developing tools to support complex infrastructure decision-making

Purpose – The rapidly changing role of capital city airports has placed demands on surrounding infrastructure. The need for infrastructure management and coordination is increasing as airports and cities grow and share common infrastructure frameworks. The purpose of this paper is to document the changing context in Australia, where the privatisation of airports has stimulated considerable land development with resulting pressures on surrounding infrastructure provision. It aims to describe a tool that is being developed to support decision-making between various stakeholders in the airport region. The use of planning support systems improves both communication and data transfer between stakeholders and provides a foundation for complex decisions on infrastructure. Design/methodology/approach – The research uses a case study approach and focuses on Brisbane International Airport and Brisbane City Council. The research is primarily descriptive and provides an empirical assessment of the challenges of developing and implementing planning support systems as a tool for governance and decision-making. Findings – The research assesses the challenges in implementing a common data platform for stakeholders. Agency data platforms and models, traditional roles in infrastructure planning, and integrating similar data platforms all provide barriers to sharing a common language. The use of a decision support system has to be shared by all stakeholders with a common platform that can be versatile enough to support scenarios and changing conditions. The use of iPadss for scenario modelling provides stakeholders the opportunity to interact, compare scenarios and views, and react with the modellers to explore other options. Originality/value – The research confirms that planning support systems have to be accessible and interactive by their users. The Airport City concept is a new and evolving focus for airport development and will place continuing pressure on infrastructure servicing. A coordinated and efficient approach to infrastructure decision-making is critical, and an interactive planning support system that can model infrastructure scenarios provides a sound tool for governance.

Modelling port water collision risk using traffic conflicts

Navigational collisions are one of the major safety concerns for many seaports. Despite the extent of work recently done on collision risk analysis in port waters, little is known about the influencing factors of the risk. This paper develops a technique for modeling collision risks in port waterways in order to examine the associations between the risks and the geometric, traffic, and regulatory control characteristics of waterways. A binomial logistic model, which accounts for the correlations in the risks of a particular fairway at different time periods, is derived from traffic conflicts and calibrated for the Singapore port fairways. Estimation results show that the fairways attached to shoreline, traffic intersection and international fairway attribute higher risks, whereas those attached to confined water and local fairway possess lower risks. Higher risks are also found in the fairways featuring higher degree of bend, lower depth of water, higher numbers of cardinal and isolated danger marks, higher density of moving ships and lower operating speed. The risks are also found to be higher for night-time conditions.

Sustainable urban transport : smart technology initiatives in Singapore

Achieving sustainability is one of the major goals of many urban transportation systems. Over the years, many innovative policies have been attempted to achieve an efficient, safe, and sustainable transport system. Those policies often require smart technologies to assist implementation process and enhance effectiveness. This paper discusses how sustainability can be promoted by embedding smart technologies in a modern transportation system. In particular, this paper studies the transport system of Singapore to address how this system is addressing sustainability through the use of smart technologies. Various technological initiatives in managing traffic flow, monitoring and enforcement, sharing real-time information, and managing revenues are discussed in light of their potentiality in addressing sustainability issues. The Singapore experience provides a useful reference for the cities intending to develop and promote a sustainable transport system.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

On the significance of omitted variables in intersection crash modeling

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causes and contributing factors—rest upon the pursuit of numerous lines of research inquiry. The research community has focused considerable attention on analytical methods development (negative binomial models, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might logically seek to know which lines of inquiry might provide the most significant improvements in understanding crash causation and/or prediction. It is the contention of this paper that the exclusion of important variables (causal or surrogate measures of causal variables) cause omitted variable bias in model estimation and is an important and neglected line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant opportunities to better understand contributing factors and/or causes of crashes. This study examines the role of important variables (other than Average Annual Daily Traffic (AADT)) that are generally omitted from intersection crash prediction models. In addition to the geometric and traffic regulatory information of intersection, the proposed model includes many spatial factors such as local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools—representing a mix of potential environmental and human factors that are theoretically important, but rarely used. Results suggest that these variables in addition to AADT have significant explanatory power, and their exclusion leads to omitted variable bias. Provided is evidence that variable exclusion overstates the effect of minor road AADT by as much as 40% and major road AADT by 14%.

Evaluation of the control of carbon emissions of construction facilities in Hong Kong

This paper investigates the policies and instruments adopted in Hong Kong to control the carbon emissions of construction facilities, including the whole building life cycle: production of material stage, construction stage, operation stage and demolition stage. This commences with a literature review comparing activities world-wide to those in Hong Kong to identify the main issues at stake, followed by a report on a series of local interviews to evaluate the present situation in Hong Kong, as well as future opportunities for local carbon mitigation. The interviewees included practitioners from engineering contracting firms, consulting firms, clients and energy provider, together with two university experts and a counsellor. A small case study is also provided of a building project in Hong Kong to illustrate some of the innovative design aspects being incorporated into buildings in Hong Kong as a result of the current emphasis on sustainability. The paper concludes with a summary of main findings and proposals for improvement in policy related to carbon mitigation and building sustainability in Hong Kong.

A high sensitive fiber Bragg grating strain sensor with automatic temperature compensation

A high sensitive fiber Bragg grating (FBG) strain sensor with automatic temperature compensation is demonstrated. FBG is axially linked with a stick and their free ends are fixed to the measured object. When the measured strain changes, the stick does not change in length, but the FBG does. When the temperature changes, the stick changes in length to pull the FBG to realize temperature compensation. In experiments, 1.45 times strain sensitivity of bare FBG with temperature compensation of less than 0.1 nm Bragg wavelength drift over 100 ◦C shift is achieved.

A high sensitive fiber Bragg grating cryogenic temperature sensor

At cryogenic temperature, a fiber Bragg grating (FBG) temperature sensor with controllable sensitivity and variable measurement range is demonstrated by using bimetal configuration. In experiments, sensitivities of -51.2, -86.4, and -520 pm/K are achieved by varying the lengths of the metals. Measurement ranges of 293-290.5, 283-280.5, and 259-256.5 K are achieved by shortening the distance of the gap among the metals.

Using fiber Bragg grating in geothermal monitoring

Earthquake precursor monitoring is the foundation of earthquake prediction and geothermal monitoring is one of the basic methods of earthquake precursor monitoring. High temperature well contains more information and therefore its monitoring is more important. However, electric sensors are hard to meet the monitoring requirements of high sensitivity and long lifetime. For a better observation of the earthquake precursor, a high sensitive fiber Bragg grating (FBG) temperature sensor is designed to monitoring a well at 87.5±1◦C. The performance of the FBG sensor demonstrates that it’s quite possible that applying FBG to high-sensitivity temperature-monitoring fields, such as geothermal monitoring. As far as we known, it is the first time that trying a high sensitive FBG temperature sensor in a practical application, let alone in the field of geothermal monitoring.