Efficient missing data imputing for traffic flow by considering temporal and spatial dependence

The missing data problem remains as a difficulty in a diverse variety of transportation applications, e.g. traffic flow prediction and traffic pattern recognition. To solve this problem, numerous algorithms had been proposed in the last decade to impute the missed data. However, few existing studies had fully used the traffic flow information of neighboring detecting points to improve imputing performance. In this paper, probabilistic principle component analysis (PPCA) based imputing method, which had been proven to be one of the most effective imputing methods without using temporal or spatial dependence, is extended to utilize the information of multiple points. We systematically examine the potential benefits of multi-point data fusion and study the possible influence of measurement time lags. Tests indicate that the hidden temporal–spatial dependence is nonlinear and could be better retrieved by kernel probabilistic principle component analysis (KPPCA) based method rather than PPCA method. Comparison proves that imputing errors can be notably reduced, if temporal–spatial dependence has been appropriately considered.     

浅谈高速公路桥头跳车的因素及预防措施

桥头跳车一直是高速公路投入使用后普遍存在的问题,本文通过查阅各种资料及本人施工经验,归纳总结了桥头跳车问题产生的原因,提出了桥头跳车问题的预防措施,以便为今后类似工程的施工提供参考。     

Sensitivity-based uncertainty analysis of a combined travel demand model

Travel demand forecasting is subject to great uncertainties. A systematic uncertainty analysis can provide insights into the level of confidence on the model outputs, and also identify critical sources of uncertainty for enhancing the robustness of the travel demand model. In this paper, we develop a systematic framework for quantitative uncertainty analysis of a combined travel demand model (CTDM) using the analytical sensitivity-based method. The CTDM overcomes limitations of the sequential four-step procedure since it is based on a single unifying rationale. The analytical sensitivity-based method requires less computational effort than the sampling-based method. Meanwhile, the uncertainties stemming from inputs and parameters can be treated separately so that the individual and collective effects of uncertainty on the outputs can be clearly assessed and quantified. Numerical examples are finally used to demonstrate the proposed sensitivity-based uncertainty analysis method for the CTDM.     

改进振动法在地下工程动力时程计算中的应用

地下工程受到周围土体的约束作用,其动力反映与地面工程有所区别,如将源于地面工程的振动法用于地下工程的动力时程计算分析,需要进行相应的改进.文章通过计算分析发现,振动法用于地下工程动力时程计算时,在计算模型边界条件和波动传播时间效应方面不能反映波动对地下工程作用的实质；通过对比分析,在这两个方面对常规振动法进行了改进；提出了适用于地下工程动力时程计算的改进振动法.该方法的计算模型采用左右两侧粘弹性底部固定的人工边界条件,波动输入采用能够反映波动传播时间效应的分层加速度动态输入法,其计算分析结果与理论解吻合较好,适用于地下工程的动力时程计算分析.     

(Unintended) Transport impacts of an energy-environment policy: The case of CNG conversion of vehicles in Dhaka

Motor vehicles are one of the major sources of air pollution in Dhaka, the capital of Bangladesh. The government took various policies to convert the petroleum vehicles on road to run on compressed natural gas (CNG), which allows both air quality improvements and energy security benefits. One of the market friendly policies to encourage the fuel switch was to increase the price differential between CNG and petrol and diesel. This has allowed a wide-scale adoption of CNG as the fuel of choice. However, several years into the policy, there is now a widespread belief among the policymakers that the CNG conversion may have increased car ownership and car travel due to their lower running costs, resulting in more congestion and a reversal of the strategy is on the cards. It is therefore important to test the hypothesis whether CNG conversion had genuinely increased car ownership and car travel in Dhaka city. This paper presents the results of a questionnaire survey and an econometric intervention analysis to understand the impact of CNG conversion on car ownership and car travel in Dhaka. Attention is also given to disentangle the self-selection and price-induced travel effects of CNG conversion. Results show that ownership did not increase, but travel of on-road vehicles increased due to the CNG policy. However, additional congestion costs are still around one half of the health benefits brought about by the policy.     

Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.     

A dynamic model for marginal cost pricing of port infrastructures

ABSTRACT

A dynamic model for marginal cost pricing of port infrastructures links costs to system performance by combining a power-law function with time-dependent queueing analysis. Additionally, the model incorporates the marginal cost of capacity, including the effects of economies of scale. This allows the calculation of the marginal cost price under a dynamic framework. The model accounts for nonlinear behaviour of port demand, which is sensitive to price and service levels. The effects over time of cost and service levels on the port’s operational performance are quantified. The proposed model allows determining the optimal timing for capacity investment. The model is a starting point for the application of marginal cost pricing to ports. However, for practical application of such pricing method it is necessary to apply a system’s approach, as productivity and costs must be assessed at the terminal’s component level. This should allow the derivation of a marginal cost function at the terminal’s component level.     

Critical success factors of supply chain integration in container shipping: an application of resource-based view theory

ABSTRACT

The container shipping industry is receiving growing attention in driving the performance of global supply chains. This phenomenon has accelerated supply chain integration (SCI) within the industry. Although SCI could offer numerous benefits, it is often quoted to be implemented easier in theory than in practice. The high failure rate that is associated with SCI is often not addressed in the literature. Grounded on resource-based view (RBV) theory, this paper is aimed at identifying the critical success factors (CSFs) and examining their influence on SCI and supply chain performance (SCP). Survey questionnaires were administered on 164 container shipping firms. The constructs were validated empirically using confirmatory factor analysis and were subsequently analysed using structural equation modelling. The proposed CSFs in this study are found to be positively corelated with SCI, which, in turn, is positively correlated with SCP. This paper has contributed to both theory and practice by applying RBV theory to identify the key resources and capabilities that are necessary for SCI in the container shipping industry.     

基于集对分析的道路交通拥堵判定

基于集对分析原理提出了道路交通拥堵判定的新方法——集对分析法,给出了集对分析法的基本思路和交通拥堵判定步骤。该方法考虑了交通状态分级标准的模糊性,同时避免了差异不确定系数的取值,应用于成都市某路段交通拥堵状态的判定,结果表明,该方法概念清晰、结构简单、计算简单、易操作、可行有效。