Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.     

价值工程理论在沥青混合料碳排放减排措施中的应用

沥青混合料碳排放减排措施是降低碳排放的有效手段,而对减排措施的选择将直接影响工程的质量和经济效益。本文运用价值工程理论的基本原理与方法,论述价值工程在减排措施选择中的应用方法和步骤,并结合工程实例,对减排措施方案的选择进行研究。结果表明,运用价值工程理论的方法可以择优确定沥青混合料碳排放减排措施。     

SIR-20地质雷达在工程中的应用及图谱解释

介绍了地质雷达探测的基本原理,并结合工程实例和模拟试验说明了地质雷达的具体应用。通过对地质雷达检测图谱的分析和归类处理,找出目标体的地质雷达图谱特征,为地质雷达在工程中的应用提供了判别依据。     

A logit-based model for measuring the effects of transportation infrastructure on land value

Mutual interactions between transportation and land use have long been debated. Despite progress made in computational technology, the study of these interactions is not adequately developed. The most important aspect of such interactions is given by the changes in land values due to changes in transportation infrastructures. We consider the behavioural features of these interactions along with the constraints on the land and/or zoning restrictions and propose a reliable model for the first time to predict land value changes with respect to changes in transportation facilities and accessibility. The proposed model is a logit-based mathematical programming methodology where the relative price of land is predicted with respect to transportation accessibility, neighbourhood amenities, location premium, availability of land, and zoning regulations. A real-world case study is used to exhibit the applicability of the proposed methodology and demonstrate the efficacy of the algorithms and procedures.     

An adaptive information fusion model to predict the short-term link travel time distribution in dynamic traffic networks

As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions.     

On the income elasticity of the value of travel time

Transport infrastructure is long-term and in appraisal it is necessary to value travel time savings for future years. This requires knowing how the value of time (VTT) will develop over time as incomes grow. This paper investigates if the cross-sectional income elasticity of the VTT is equal to inter-temporal income elasticity. The study is based on two identical stated choice experiments conducted with a 13 year interval. Results indicate that the relationship between income and the VTT in the cross-section has remained unchanged over time. As a consequence, the inter-temporal income elasticity of the VTT can be predicted based on cross-sectional income elasticity. However, the income elasticity of the VTT is not a constant but increases with income. For this reason, the average income elasticity of the VTT in the cross-sections has increased between the two survey years and can be expected to increase further over time.     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

交通职业技术学院学生职业价值观问题研究

市场经济所带来的多元化择业观念,使毕业生集体主义观念和社会责任感观念淡化,从而在就业选择上趋向于功利化、自我化。文章针对当前交通职业技术学院学生职业价值观的这一变化,分析学生现实型职业价值观与传统型职业价值观之旬的冲突,提出了交通职业技术学校在职业价值观教育方面应采取的措施。     

隧道数字化火灾预警系统的在线量化评估

为检查和评价隧道及地下空间火灾预警系统的实际功能,需要一套可行的在线评估手段。根据近年来国内外全尺寸隧道火灾发展曲线的试验结果,提出隧道火情的定义依据;引用运营隧道内准分布式光纤光栅感温火灾探测器的实测数据,证明运营中隧道报警系统的个性化现象;提出合格的数字化报警系统应存在一个在统计学意义上使漏报率和误报率同时达到期望值的合理阈值取值区间;建议以该区间的尺度作为该系统功能完好性的评估指标;对日常隧道运行温度数据的统计分析可估计合理阈值取值区间的下限,对规定条件下的现场点火试验温度数据分析可估计合理阈值取值区间的上限。在隧道运营期该区间尺度可实时在线自动更新。     

A Pareto-improving hybrid rationing and pricing policy with multiclass network equilibria

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts.