模糊分析法在公路边坡稳定性评价中的应用

山区某高等级公路沿线存在大量挖方路堑高边坡,边些边坡的失稳问题已严重影响公路施工和后期的运营。运用模糊(fuzzy)分析理论对典型挖方边坡的稳定性进行了分析,得出的结论与现场观察的边坡变形破坏迹象相吻合。     

基于功效系数法的城市公交线网优化模型

城市公共交通线网优化是城市客运交通规划的重要部分之一。对现有公交线网进行优化,可以更有效地利用现有资源,解决城市交通问题。通过对城市公交线网优化的主要内容、优化模式、优化目标以及约束条件的分析,同时兼顾乘客出行时间、线网平均满载率、公交线网密度和公交线网的布局,对整个城市交通系统的影响提出优化目标的函数表达式及相应约束条件的数学表达式,建立公交线网优化的多目标模型。通过对模型的分析,提出可用功效系数法对模型进行寻优和评价。     

江西省高速公路路侧交通事故统计分析和路侧障碍物处理对策

通过调查江西省昌樟高速梅林段、梨温高速和泰井高速2006年至2007年单车路侧交通事故,详细记录并分析事故资料,总结出江西省高速公路单车路侧事故的特点以及相应路侧障碍物在路侧事故中的反应特点,提出13种常见路侧障碍物的处理对策。     

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.     

Are HOV/eco-lanes a sustainable option to reducing emissions in a medium-sized European city?

Innovative traffic management measures are needed to reduce transportation-related emissions. While in Europe, road lane management has focused mainly on introduction of bus lanes, the conversion to High Occupancy Vehicles (HOV) and eco-lanes (lanes dedicated to vehicles running on alternative fuels) has not been studied comprehensively. The objectives of this research are to: (1) Develop an integrated microscopic modeling platform calibrated with real world data to assess both traffic and emissions impacts of future Traffic Management Strategies (TMS) in an urban area; (2) Evaluate the introduction of HOV/eco-lanes in three different types of roads, freeway, arterial and urban routes, in an European medium-sized city and its effects in terms of emissions and traffic performance. The methodology consists of three distinct phases: (a) Traffic and road inventory data collection; (b) Traffic and emissions simulation using an integrated platform of microscopic simulation; and (c) Evaluation of scenarios. For the baseline scenario, the statistical analysis shows valid results. The results show that HOV and eco-lanes in a medium European city are feasible, and when the Average Occupancy of Vehicles (AOV) increases, on freeways, the majority of vehicles can reduce their travel time (2%) with a positive impact in terms of total emissions (−38% NO_x, −39% HC, −43% CO and −37% CO₂). On urban and arterial corridors, the reduction in emissions could be achieved only if the AOV increases from 1.50 to 1.70 passengers/vehicle. Total emissions of the corridor with an AOV of 1.70 passengers/vehicle can be reduced up to 35–36% for the urban route while the values can be reduced by 36–39% for the arterial road. With the introduction of Hybrid Electric Vehicles (HEV) and Electric Vehicles (EV) it is possible to reduce emissions, although the introduction of eco-lanes did not show significant reductions in emissions. When both policies are simulated together, an emissions improvement is observed for the arterial route and for two of the scenarios.     

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.     

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.